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      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
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      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
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      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
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      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
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      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
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      "kind": "documentation",
      "title": "Audit 2026 Technique Inventory",
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      "kind": "documentation",
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      "kind": "documentation",
      "title": "LLM distillation: methods, commands, and fair comparisons",
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      "id": "docs/techniques/evolution_strategies",
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      "md": "https://posttrainllm.com/docs/techniques/evolution_strategies.md",
      "kind": "documentation",
      "title": "Evolution Strategies — gradient-free training",
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    },
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      "id": "docs/techniques/galore_and_stability",
      "url": "https://posttrainllm.com/docs/techniques/galore_and_stability/",
      "md": "https://posttrainllm.com/docs/techniques/galore_and_stability.md",
      "kind": "documentation",
      "title": "GaLore + training-stability bells (Tier 2)",
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    },
    {
      "id": "docs/techniques/interpretability",
      "url": "https://posttrainllm.com/docs/techniques/interpretability/",
      "md": "https://posttrainllm.com/docs/techniques/interpretability.md",
      "kind": "documentation",
      "title": "Interpretability tools — what is the model thinking?",
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      "id": "docs/techniques/lora_guide",
      "url": "https://posttrainllm.com/docs/techniques/lora_guide/",
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      "kind": "documentation",
      "title": "LoRA guide — fine-tuning the tiny model",
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      "url": "https://posttrainllm.com/docs/techniques/method-vs-recipe/",
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      "kind": "documentation",
      "title": "Method vs Recipe | PostTrainLLM reference",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/techniques/moe",
      "url": "https://posttrainllm.com/docs/techniques/moe/",
      "md": "https://posttrainllm.com/docs/techniques/moe.md",
      "kind": "documentation",
      "title": "Mixture-of-Experts — more capacity per byte of weight",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
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      "id": "docs/techniques/mtp",
      "url": "https://posttrainllm.com/docs/techniques/mtp/",
      "md": "https://posttrainllm.com/docs/techniques/mtp.md",
      "kind": "documentation",
      "title": "Multi-Token Prediction — better training signal per step",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
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      "id": "docs/techniques/needle2-baseline-review",
      "url": "https://posttrainllm.com/docs/techniques/needle2-baseline-review/",
      "md": "https://posttrainllm.com/docs/techniques/needle2-baseline-review.md",
      "kind": "documentation",
      "title": "Needle 2 baseline review | PostTrainLLM reference",
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    },
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      "id": "docs/techniques/needle2-successor-factorial",
      "url": "https://posttrainllm.com/docs/techniques/needle2-successor-factorial/",
      "md": "https://posttrainllm.com/docs/techniques/needle2-successor-factorial.md",
      "kind": "documentation",
      "title": "Needle 45M successor factorial",
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    },
    {
      "id": "docs/techniques/optimizers",
      "url": "https://posttrainllm.com/docs/techniques/optimizers/",
      "md": "https://posttrainllm.com/docs/techniques/optimizers.md",
      "kind": "documentation",
      "title": "Optimizers | PostTrainLLM reference",
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    },
    {
      "id": "docs/techniques/parakeet-wgsl-browser-smoke",
      "url": "https://posttrainllm.com/docs/techniques/parakeet-wgsl-browser-smoke/",
      "md": "https://posttrainllm.com/docs/techniques/parakeet-wgsl-browser-smoke.md",
      "kind": "documentation",
      "title": "parakeet.wgsl browser smoke | PostTrainLLM reference",
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    },
    {
      "id": "docs/techniques/peft_variants",
      "url": "https://posttrainllm.com/docs/techniques/peft_variants/",
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      "kind": "documentation",
      "title": "PEFT Variants in posttrainllm technical documentation",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/techniques/precision",
      "url": "https://posttrainllm.com/docs/techniques/precision/",
      "md": "https://posttrainllm.com/docs/techniques/precision.md",
      "kind": "documentation",
      "title": "Numerics and precision — the gate framework",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/techniques/pruning",
      "url": "https://posttrainllm.com/docs/techniques/pruning/",
      "md": "https://posttrainllm.com/docs/techniques/pruning.md",
      "kind": "documentation",
      "title": "Pruning — magnitude masks and structured surgery",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/techniques/quantization_expansion",
      "url": "https://posttrainllm.com/docs/techniques/quantization_expansion/",
      "md": "https://posttrainllm.com/docs/techniques/quantization_expansion.md",
      "kind": "documentation",
      "title": "Quantization Expansion | PostTrainLLM reference",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/techniques/speculative_heads",
      "url": "https://posttrainllm.com/docs/techniques/speculative_heads/",
      "md": "https://posttrainllm.com/docs/techniques/speculative_heads.md",
      "kind": "documentation",
      "title": "Speculative-decoding heads: Medusa + EAGLE-2",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/techniques/sql-technique-backlog",
      "url": "https://posttrainllm.com/docs/techniques/sql-technique-backlog/",
      "md": "https://posttrainllm.com/docs/techniques/sql-technique-backlog.md",
      "kind": "documentation",
      "title": "SQL Technique Lineage — Closed",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/techniques/streaming_llm_kivi",
      "url": "https://posttrainllm.com/docs/techniques/streaming_llm_kivi/",
      "md": "https://posttrainllm.com/docs/techniques/streaming_llm_kivi.md",
      "kind": "documentation",
      "title": "StreamingLLM + KIVI — long-context decode without growing…",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/techniques/trainloop-teardown",
      "url": "https://posttrainllm.com/docs/techniques/trainloop-teardown/",
      "md": "https://posttrainllm.com/docs/techniques/trainloop-teardown.md",
      "kind": "documentation",
      "title": "TrainLoop Teardown | PostTrainLLM reference",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/tool_call_extractor",
      "url": "https://posttrainllm.com/docs/tool_call_extractor/",
      "md": "https://posttrainllm.com/docs/tool_call_extractor.md",
      "kind": "documentation",
      "title": "Tool-call extractor (mini-router)",
      "description": "Design + training recipe for posttrainllm's tiny encoder model that picks which tool a user query needs, before the full LM forward pass."
    },
    {
      "id": "docs/training",
      "url": "https://posttrainllm.com/docs/training/",
      "md": "https://posttrainllm.com/docs/training.md",
      "kind": "documentation",
      "title": "The three phases of training — pretrain, SFT, DPO",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/training/dpo",
      "url": "https://posttrainllm.com/docs/training/dpo/",
      "md": "https://posttrainllm.com/docs/training/dpo.md",
      "kind": "documentation",
      "title": "DPO training: direct preference optimization for LLMs",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/training/nightly",
      "url": "https://posttrainllm.com/docs/training/nightly/",
      "md": "https://posttrainllm.com/docs/training/nightly.md",
      "kind": "documentation",
      "title": "PostTrainLLM — nightly training queue",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/training/pretrain",
      "url": "https://posttrainllm.com/docs/training/pretrain/",
      "md": "https://posttrainllm.com/docs/training/pretrain.md",
      "kind": "documentation",
      "title": "Pretraining | PostTrainLLM reference",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "docs/training/sft",
      "url": "https://posttrainllm.com/docs/training/sft/",
      "md": "https://posttrainllm.com/docs/training/sft.md",
      "kind": "documentation",
      "title": "Supervised fine-tuning (SFT) | PostTrainLLM reference",
      "description": "Mac-local LLM factory documentation — training, inference, evals, systems notes, and learning paths."
    },
    {
      "id": "download",
      "url": "https://posttrainllm.com/download",
      "md": "https://posttrainllm.com/download.md",
      "kind": "application",
      "title": "PostTrainLLM for Mac — release status",
      "description": "Verified release status for the native PostTrainLLM app on Apple Silicon. The signed, notarized, stapled DMG is published with its SHA-256."
    },
    {
      "id": "eval-leaderboard",
      "url": "https://posttrainllm.com/eval-leaderboard",
      "md": "https://posttrainllm.com/eval-leaderboard.md",
      "kind": "application",
      "title": "posttrainllm — eval leaderboard",
      "description": "Drop E0 eval JSONL files to compare models, checkpoints, and tasks in the browser."
    },
    {
      "id": "evaluate-local-llm",
      "url": "https://posttrainllm.com/evaluate-local-llm",
      "md": "https://posttrainllm.com/evaluate-local-llm.md",
      "kind": "application",
      "title": "How to evaluate a local LLM | PTLLM",
      "description": "Evaluate a local LLM with a pinned generation recipe, raw outputs and regression checks. Validate report files offline without loading a model."
    },
    {
      "id": "experiments",
      "url": "https://posttrainllm.com/experiments",
      "md": "https://posttrainllm.com/experiments.md",
      "kind": "application",
      "title": "Every experiment — posttrainllm",
      "description": "The complete PostTrainLLM experiment archive: every worked, failed, regressed, inconclusive, superseded, and rejected attempt with evidence and a reusable…"
    },
    {
      "id": "experiments/a1-tool-caller-harness",
      "url": "https://posttrainllm.com/experiments/a1-tool-caller-harness",
      "md": "https://posttrainllm.com/experiments/a1-tool-caller-harness.md",
      "kind": "experiment-record",
      "title": "A1 first tool-calling specialist harness | PTLLM",
      "description": "Reusable infrastructure can be superseded by stronger downstream evidence even when its first named model run never happened. Retained outcome: superseded."
    },
    {
      "id": "experiments/apple-foundation-models-action-grounding",
      "url": "https://posttrainllm.com/experiments/apple-foundation-models-action-grounding",
      "md": "https://posttrainllm.com/experiments/apple-foundation-models-action-grounding.md",
      "kind": "experiment-record",
      "title": "Apple on-device Foundation Models action-grounding probe | PTLLM",
      "description": "Apple Foundation Models are useful as a free routing floor and intel source, not as the core capability dependency. Retained outcome: failed."
    },
    {
      "id": "experiments/autocorrect-ordinary-loss-pilot",
      "url": "https://posttrainllm.com/experiments/autocorrect-ordinary-loss-pilot",
      "md": "https://posttrainllm.com/experiments/autocorrect-ordinary-loss-pilot.md",
      "kind": "experiment-record",
      "title": "Autocorrect FLAN-T5-small ordinary-loss pilot (2026-07-25) | PTLLM",
      "description": "Minimum-edit repair is a narrow band between copying everything and rewriting everything Retained outcome: regressed."
    },
    {
      "id": "experiments/autocorrect-tiny-overfit-gate",
      "url": "https://posttrainllm.com/experiments/autocorrect-tiny-overfit-gate",
      "md": "https://posttrainllm.com/experiments/autocorrect-tiny-overfit-gate.md",
      "kind": "experiment-record",
      "title": "Autocorrect FLAN-T5-small tiny-overfit gate (2026-07-25) | PTLLM",
      "description": "A memorization gate needs more than one distinct target Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/b1-sql-eval-infra",
      "url": "https://posttrainllm.com/experiments/b1-sql-eval-infra",
      "md": "https://posttrainllm.com/experiments/b1-sql-eval-infra.md",
      "kind": "experiment-record",
      "title": "B1 SQL eval infrastructure | PostTrainLLM",
      "description": "Execution accuracy over SQLite is the right reusable gate; infra alone is not a specialist result. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/browser-default-corpus-fix",
      "url": "https://posttrainllm.com/experiments/browser-default-corpus-fix",
      "md": "https://posttrainllm.com/experiments/browser-default-corpus-fix.md",
      "kind": "experiment-record",
      "title": "Browser default corpus fix | PostTrainLLM",
      "description": "Default data is part of the product claim; a training demo's default corpus must produce non-memorized samples. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/browser-generation-streaming-kv-cache",
      "url": "https://posttrainllm.com/experiments/browser-generation-streaming-kv-cache",
      "md": "https://posttrainllm.com/experiments/browser-generation-streaming-kv-cache.md",
      "kind": "experiment-record",
      "title": "Browser generation streaming and KV cache | PTLLM",
      "description": "A typewriter animation over an already-complete response is not true streaming. Retained outcome: rejected."
    },
    {
      "id": "experiments/browser-lr-default-drift",
      "url": "https://posttrainllm.com/experiments/browser-lr-default-drift",
      "md": "https://posttrainllm.com/experiments/browser-lr-default-drift.md",
      "kind": "experiment-record",
      "title": "Browser learning-rate default drift | PostTrainLLM",
      "description": "Reference defaults are part of correctness, not just documentation. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/browser-memory64-large-presets",
      "url": "https://posttrainllm.com/experiments/browser-memory64-large-presets",
      "md": "https://posttrainllm.com/experiments/browser-memory64-large-presets.md",
      "kind": "experiment-record",
      "title": "Browser Memory64 large-preset runs | PostTrainLLM",
      "description": "A reproducer must match the production host and call path before it can explain a browser-only WASM failure. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/browser-speedup-headline-curve",
      "url": "https://posttrainllm.com/experiments/browser-speedup-headline-curve",
      "md": "https://posttrainllm.com/experiments/browser-speedup-headline-curve.md",
      "kind": "experiment-record",
      "title": "Browser speedup headline curve | PostTrainLLM",
      "description": "Qualify performance one frozen shape and machine at a time; a retained adapter identity plus alternated paired timings can convert one point without…"
    },
    {
      "id": "experiments/browser-webgpu-export-serialization",
      "url": "https://posttrainllm.com/experiments/browser-webgpu-export-serialization",
      "md": "https://posttrainllm.com/experiments/browser-webgpu-export-serialization.md",
      "kind": "experiment-record",
      "title": "Browser WebGPU export serialization | PostTrainLLM",
      "description": "Long-running browser training is not product-complete until the smallest export path is smoke-tested before the long run. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/browser-webgpu-training-loop",
      "url": "https://posttrainllm.com/experiments/browser-webgpu-training-loop",
      "md": "https://posttrainllm.com/experiments/browser-webgpu-training-loop.md",
      "kind": "experiment-record",
      "title": "Browser WebGPU training loop | PostTrainLLM",
      "description": "Hardware-qualified browser WebGPU can deliver a double-digit training-step win while preserving the frozen numerical-loss gate. Retained outcome: worked."
    },
    {
      "id": "experiments/character-2048-frontier-screen",
      "url": "https://posttrainllm.com/experiments/character-2048-frontier-screen",
      "md": "https://posttrainllm.com/experiments/character-2048-frontier-screen.md",
      "kind": "experiment-record",
      "title": "Character 2048 frontier benchmark screen (2026-08-04) | PTLLM",
      "description": "Validate the teacher and interface before spending compute on a specialist; a failed ruler should stop training. Retained outcome: rejected."
    },
    {
      "id": "experiments/character-chess-44m-masked-10k-pilot",
      "url": "https://posttrainllm.com/experiments/character-chess-44m-masked-10k-pilot",
      "md": "https://posttrainllm.com/experiments/character-chess-44m-masked-10k-pilot.md",
      "kind": "experiment-record",
      "title": "Character Chess 44.53M masked 10k pilot (2026-08-05) | PTLLM",
      "description": "Legal constrained decoding and lower move-prediction loss are not game intelligence; require full-game transfer before scaling a tiny specialist. Retained…"
    },
    {
      "id": "experiments/character-chess-benchmark-candidate",
      "url": "https://posttrainllm.com/experiments/character-chess-benchmark-candidate",
      "md": "https://posttrainllm.com/experiments/character-chess-benchmark-candidate.md",
      "kind": "experiment-record",
      "title": "Character Chess benchmark candidate audit (2026-08-22) | PTLLM",
      "description": "A benchmark candidate set is not a benchmark until the frontier ceiling validates the ruler. Retained outcome: rejected."
    },
    {
      "id": "experiments/character-game-arena-candidate",
      "url": "https://posttrainllm.com/experiments/character-game-arena-candidate",
      "md": "https://posttrainllm.com/experiments/character-game-arena-candidate.md",
      "kind": "experiment-record",
      "title": "Character game arena candidate report (2026-08-05) | PTLLM",
      "description": "A rating calculation is not a public rating until each underlying competition family passes its qualification contract. Retained outcome: rejected."
    },
    {
      "id": "experiments/cold-start-bundle",
      "url": "https://posttrainllm.com/experiments/cold-start-bundle",
      "md": "https://posttrainllm.com/experiments/cold-start-bundle.md",
      "kind": "experiment-record",
      "title": "Cold-start bundle | PostTrainLLM",
      "description": "mmap and direct byte construction are good scaling levers, but large-model cold-start claims need large-model measurements. Retained outcome: worked with…"
    },
    {
      "id": "experiments/cpu-speedup-bundle",
      "url": "https://posttrainllm.com/experiments/cpu-speedup-bundle",
      "md": "https://posttrainllm.com/experiments/cpu-speedup-bundle.md",
      "kind": "experiment-record",
      "title": "CPU speedup bundle | PostTrainLLM",
      "description": "The big win was fused accumulation inside the compiled trace; individual CPU tweaks need isolation before being credited. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/data-perf-sample-packing-bpe-dropout",
      "url": "https://posttrainllm.com/experiments/data-perf-sample-packing-bpe-dropout",
      "md": "https://posttrainllm.com/experiments/data-perf-sample-packing-bpe-dropout.md",
      "kind": "experiment-record",
      "title": "Data-side sample packing and BPE-dropout | PTLLM",
      "description": "Data-pipeline regularizers need behavioral evals, not just stable loss curves, before being treated as quality improvements. Retained outcome: worked with…"
    },
    {
      "id": "experiments/factory-run-schema",
      "url": "https://posttrainllm.com/experiments/factory-run-schema",
      "md": "https://posttrainllm.com/experiments/factory-run-schema.md",
      "kind": "experiment-record",
      "title": "Factory run schema | PostTrainLLM",
      "description": "A schema is necessary but not sufficient; publish checks must enforce complete run folders. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/fileops-qwen3-4b-distilled",
      "url": "https://posttrainllm.com/experiments/fileops-qwen3-4b-distilled",
      "md": "https://posttrainllm.com/experiments/fileops-qwen3-4b-distilled.md",
      "kind": "experiment-record",
      "title": "Qwen3-4B file-ops distilled specialist | PostTrainLLM",
      "description": "The artifact is useful only with routed-only positioning; it should not be sold as a general planner. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/fileops-qwen3-4b-multibackend-distilled",
      "url": "https://posttrainllm.com/experiments/fileops-qwen3-4b-multibackend-distilled",
      "md": "https://posttrainllm.com/experiments/fileops-qwen3-4b-multibackend-distilled.md",
      "kind": "experiment-record",
      "title": "Qwen3-4B multibackend distilled variant | PostTrainLLM",
      "description": "Multi-backend distillation can over-specialize and needs breadth gates by default. Retained outcome: regressed."
    },
    {
      "id": "experiments/fileops-qwen3-4b-rest-fused",
      "url": "https://posttrainllm.com/experiments/fileops-qwen3-4b-rest-fused",
      "md": "https://posttrainllm.com/experiments/fileops-qwen3-4b-rest-fused.md",
      "kind": "experiment-record",
      "title": "Qwen3-4B ReST fused breadth recovery variant | PTLLM",
      "description": "ReST produced a real depth-and-safety specialist, not breadth recovery; routing is the win and general replacement is the failed hypothesis. Retained…"
    },
    {
      "id": "experiments/gradient-checkpointing-mac-training",
      "url": "https://posttrainllm.com/experiments/gradient-checkpointing-mac-training",
      "md": "https://posttrainllm.com/experiments/gradient-checkpointing-mac-training.md",
      "kind": "experiment-record",
      "title": "Gradient checkpointing Mac training | PostTrainLLM",
      "description": "Activation recompute is a scale-dependent lever; it should stay opt-in for models where memory, not step time, is the blocker. Retained outcome: worked with…"
    },
    {
      "id": "experiments/kv-cache-optimization-bundle",
      "url": "https://posttrainllm.com/experiments/kv-cache-optimization-bundle",
      "md": "https://posttrainllm.com/experiments/kv-cache-optimization-bundle.md",
      "kind": "experiment-record",
      "title": "KV cache optimization bundle | PostTrainLLM",
      "description": "Reuse of prefilled KV is the user-visible win; cache storage policy changes need composition gates before becoming defaults. Retained outcome: worked with…"
    },
    {
      "id": "experiments/measurement-gate-audit-20261025",
      "url": "https://posttrainllm.com/experiments/measurement-gate-audit-20261025",
      "md": "https://posttrainllm.com/experiments/measurement-gate-audit-20261025.md",
      "kind": "experiment-record",
      "title": "Frozen gate held-out readback | PostTrainLLM",
      "description": "A frontier ceiling is necessary but does not make a simple smoke discriminating; a zero fixed-list side-effect counter also does not prove complete safety.…"
    },
    {
      "id": "experiments/mlxfast-sdpa-tied-embedding-audit",
      "url": "https://posttrainllm.com/experiments/mlxfast-sdpa-tied-embedding-audit",
      "md": "https://posttrainllm.com/experiments/mlxfast-sdpa-tied-embedding-audit.md",
      "kind": "experiment-record",
      "title": "MLXFast SDPA and tied-embedding audit | PostTrainLLM",
      "description": "The suspected SDPA mask/contiguity and tied-embedding duplication issues were not present. Retained outcome: worked."
    },
    {
      "id": "experiments/moe-dense-compute-smoke",
      "url": "https://posttrainllm.com/experiments/moe-dense-compute-smoke",
      "md": "https://posttrainllm.com/experiments/moe-dense-compute-smoke.md",
      "kind": "experiment-record",
      "title": "MoE dense-compute smoke | PostTrainLLM",
      "description": "MoE is a capacity feature until sparse gather/scatter or grouped matmul lands; it should not be marketed as a compute-saving win yet. Retained outcome:…"
    },
    {
      "id": "experiments/needle2-base-public-gate",
      "url": "https://posttrainllm.com/experiments/needle2-base-public-gate",
      "md": "https://posttrainllm.com/experiments/needle2-base-public-gate.md",
      "kind": "experiment-record",
      "title": "Needle 2 base public tool-selection gate (2026-08-31) | PTLLM",
      "description": "Tiny packaging and fast decode do not make a tool selector safe enough for action routing. Retained outcome: failed."
    },
    {
      "id": "experiments/needle2-successor-factorial",
      "url": "https://posttrainllm.com/experiments/needle2-successor-factorial",
      "md": "https://posttrainllm.com/experiments/needle2-successor-factorial.md",
      "kind": "experiment-record",
      "title": "Needle 45M distractor-and-safety successor factorial (2026-09-03) | PTLLM",
      "description": "Tiny overfit proves wiring, not capacity; the interaction treatment recovered only two cases over plain training and could not learn destructive…"
    },
    {
      "id": "experiments/needle2-task-catalog-ablation",
      "url": "https://posttrainllm.com/experiments/needle2-task-catalog-ablation",
      "md": "https://posttrainllm.com/experiments/needle2-task-catalog-ablation.md",
      "kind": "experiment-record",
      "title": "Needle 2 task-specific catalog ablation (2026-09-01) | PTLLM",
      "description": "Catalog restriction is a latency lever, not a capability or safety rescue for this base model. Retained outcome: regressed."
    },
    {
      "id": "experiments/offhours-context-saturation",
      "url": "https://posttrainllm.com/experiments/offhours-context-saturation",
      "md": "https://posttrainllm.com/experiments/offhours-context-saturation.md",
      "kind": "experiment-record",
      "title": "OffHours context-saturation boundary (2026-08-21) | PTLLM",
      "description": "The supported result is a neutral context-volume boundary, not a psychological or family-tension effect. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/offhours-persistent-tension",
      "url": "https://posttrainllm.com/experiments/offhours-persistent-tension",
      "md": "https://posttrainllm.com/experiments/offhours-persistent-tension.md",
      "kind": "experiment-record",
      "title": "OffHours persistent-tension pilot (2026-08-21) | PTLLM",
      "description": "Unresolved narrative tension did not degrade measured work quality under the exercised conditions; a null result is a valid result. Retained outcome: worked…"
    },
    {
      "id": "experiments/offhours-stress-validation",
      "url": "https://posttrainllm.com/experiments/offhours-stress-validation",
      "md": "https://posttrainllm.com/experiments/offhours-stress-validation.md",
      "kind": "experiment-record",
      "title": "OffHours Devin stress validation (2026-08-21) | PTLLM",
      "description": "A complete run is still inconclusive when the clean frontier calibration misses its preregistered gate. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/openkernel-attention-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel fused attention preparation | PostTrainLLM",
      "description": "Fusion must preserve BF16 rounding, the exact RoPE table, cache slot writes and non-unit scale fallbacks. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/openkernel-attention-bn256-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-bn256-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-bn256-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel wider attention key tile | PostTrainLLM",
      "description": "Large full-decode kernels used 255 registers and 96 spills; wider tiles regressed. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-attention-fixedq-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-fixedq-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-fixedq-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel fixed-query FA3 scheduling | PostTrainLLM",
      "description": "Below selected joint-head attention; preserve the existing FA3 fallback. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-attention-fp8-load-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-fp8-load-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-fp8-load-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel split-K attention FP8 load compilation | PTLLM",
      "description": "Python syntax and lint checks do not validate Triton backend types; masked FP8 loads need a compatible floating-point fill value. Retained outcome: failed."
    },
    {
      "id": "experiments/openkernel-attention-joint-heads-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-joint-heads-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-joint-heads-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel joint-head FP8 paged attention | PTLLM",
      "description": "Loading both contiguous KV heads in one CTA improves this measured decode regime. This result does not establish a general FP8 advantage: the separate-head…"
    },
    {
      "id": "experiments/openkernel-attention-joint-verify-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-joint-verify-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-joint-verify-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel shared-load verification attention | PTLLM",
      "description": "254-255 registers with no spills; shared loading did not make this mapping faster. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-attention-merge-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-merge-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-merge-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel attention merge/norm/gate fusion | PTLLM",
      "description": "Below the selected joint-head attention; epilogue fusion alone did not win. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-attention-more-splits-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-more-splits-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-more-splits-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel additional full-context attention splits | PTLLM",
      "description": "Doubling the full-context split target preserves correctness but does not establish a meaningful aggregate gain. Diagnostic profiles place 97.1 and 98.6…"
    },
    {
      "id": "experiments/openkernel-attention-native-fp8-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-native-fp8-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-native-fp8-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel native FP8 QK and PV attention | PTLLM",
      "description": "Lower operand precision does not guarantee lower latency; layout conversion and dependent gathers are hypotheses until compiler or hardware evidence…"
    },
    {
      "id": "experiments/openkernel-attention-splitk-broad-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-splitk-broad-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-splitk-broad-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel broad paged split-K attention | PTLLM",
      "description": "A custom attention kernel can help decoding while losing verification; compare each dispatch regime with the current incumbent as well as the official…"
    },
    {
      "id": "experiments/openkernel-attention-splitk-narrow-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-attention-splitk-narrow-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-attention-splitk-narrow-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel narrow paged split-K attention | PTLLM",
      "description": "Use measured dispatch boundaries to retain custom attention wins and avoid verification regressions; preserve live cache metadata, legal keys and FP32…"
    },
    {
      "id": "experiments/openkernel-decoder-layer-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-decoder-layer-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-decoder-layer-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel combined decoder layer | PostTrainLLM",
      "description": "Measure attention and MoE together while preserving the full layer router precision and stream ordering; component speedups do not multiply into a layer…"
    },
    {
      "id": "experiments/openkernel-decoder-layer-narrow-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-decoder-layer-narrow-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-decoder-layer-narrow-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel decoder layer with conservative MoE dispatch | PTLLM",
      "description": "Use combined-layer evidence to narrow component optimizations, and rerun correctness and timing after restoring fallbacks. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/openkernel-dense-gemv-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-dense-gemv-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-dense-gemv-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel single-token dense GEMV | PostTrainLLM",
      "description": "A single streaming GEMV can remove split-reduction overhead for one-token projections while retaining existing dispatch for other shapes. Retained outcome:…"
    },
    {
      "id": "experiments/openkernel-dense-large-pooler-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-dense-large-pooler-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-dense-large-pooler-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel large-tile dense pooler | PostTrainLLM",
      "description": "Larger pooler tiles did not beat selected dense. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-dense-lossless-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-dense-lossless-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-dense-lossless-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel lossless single-token dense pooler | PTLLM",
      "description": "Below selected dense despite a lossless weight/layout treatment. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-dense-router-whole-row-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-dense-router-whole-row-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-dense-router-whole-row-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel whole-row FP32 tiny-router reduction | PTLLM",
      "description": "One whole-row FP32 reduction removes the cast launch for the one-token router and shows a substantial measured case gain. The diagnostic profile contains…"
    },
    {
      "id": "experiments/openkernel-dense-splitk-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-dense-splitk-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-dense-splitk-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel small-batch dense split-K and native tiny router | PTLLM",
      "description": "Separate public-shape regimes before composing improvements; more splits add a reduction launch and may lose despite sufficient parallel work. Retained…"
    },
    {
      "id": "experiments/openkernel-dense-whole-row-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-dense-whole-row-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-dense-whole-row-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel whole-row single-token dense and router reductions | PTLLM",
      "description": "Whole-row FP32 reductions improve the measured long single-token projections while retaining the short O-projection path. QKV, pooler, unpooler and router…"
    },
    {
      "id": "experiments/openkernel-final-composition-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-final-composition-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-final-composition-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel final valid-local expert decoder composition | PTLLM",
      "description": "Final layer is 10.01 percent faster by aggregate speedup ratio than the previous scored layer, but rank 283/749 missed the top-100 target. Component…"
    },
    {
      "id": "experiments/openkernel-layer-compose-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-layer-compose-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-layer-compose-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel decoder-layer GEMV and attention composition | PTLLM",
      "description": "Compose qualified components while preserving FP32 router input, stream ordering, cache semantics and normalization boundaries. Retained outcome: worked…"
    },
    {
      "id": "experiments/openkernel-layer-fused-norm-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-layer-fused-norm-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-layer-fused-norm-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel decoder layer with fused small-batch expert norm | PTLLM",
      "description": "A wrapper-level fusion can carry into the full layer, but retain the layer router precision, stream ordering and measured MoE tile fallback. Retained…"
    },
    {
      "id": "experiments/openkernel-layer-joint-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-layer-joint-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-layer-joint-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel joint-head attention layer integration | PTLLM",
      "description": "Only 2.30 percent over the scored layer with overlapping intervals; failed the prior promotion gate. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/openkernel-layer-local-ids-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-layer-local-ids-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-layer-local-ids-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel layer local expert-ID mapping | PTLLM",
      "description": "Point estimate improved but reported interval overlaps the previous scored layer. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/openkernel-layer-m128-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-layer-m128-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-layer-m128-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel layer M128 expert tile | PostTrainLLM",
      "description": "The global-density M128 tile change did not improve the aggregate. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-layer-norm-ids-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-layer-norm-ids-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-layer-norm-ids-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel layer normalization and ID-map fusion | PTLLM",
      "description": "Best prior layer check; not scored separately. Included in the final composition. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/openkernel-moe-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-moe-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-moe-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel global-expert MoE block sizing | PTLLM",
      "description": "Use the global expert count for routing density; do not confuse that heuristic with local expert IDs used by alignment. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/openkernel-moe-bf16-decode-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-moe-bf16-decode-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-moe-bf16-decode-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel grouped BF16-decoded NVFP4 experts | PTLLM",
      "description": "96 registers and zero spills do not explain the large regression; grouped GEMMs still dominate. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-moe-direct-dot-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-moe-direct-dot-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-moe-direct-dot-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel single-token direct tensor-core experts | PTLLM",
      "description": "The direct tensor-core path did not beat the selected Marlin implementation. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-moe-direct-fast-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-moe-direct-fast-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-moe-direct-fast-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel single-token NVFP4 bit decoding and vector accumulation | PTLLM",
      "description": "Bit decoding and one final reduction per output improve the earlier direct GEMV's 271.789-microsecond result, but still lose to Marlin. Unchanged…"
    },
    {
      "id": "experiments/openkernel-moe-direct-gemv-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-moe-direct-gemv-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-moe-direct-gemv-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel single-token direct packed NVFP4 SIMT GEMV | PTLLM",
      "description": "Removing route alignment is insufficient when serial unpack, scaling and repeated reductions dominate; register spilling or occupancy was not measured.…"
    },
    {
      "id": "experiments/openkernel-moe-fused-norm-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-moe-fused-norm-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-moe-fused-norm-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel fused small-batch expert norm | PTLLM",
      "description": "Profile wrapper dispatch as well as kernel arithmetic: the existing fused norm kernel removed several small-batch framework launches while preserving FP32…"
    },
    {
      "id": "experiments/openkernel-moe-grouped-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-moe-grouped-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-moe-grouped-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel raw grouped NVFP4 tensor-core experts | PTLLM",
      "description": "Correct tensor-core math does not establish an efficient implementation. The measured regression is inside GEMMs; unpacking cost, resource pressure and…"
    },
    {
      "id": "experiments/openkernel-moe-grouped-bitdecode-20261024",
      "url": "https://posttrainllm.com/experiments/openkernel-moe-grouped-bitdecode-20261024",
      "md": "https://posttrainllm.com/experiments/openkernel-moe-grouped-bitdecode-20261024.md",
      "kind": "experiment-record",
      "title": "Open Kernel grouped NVFP4 experts with bit decoding | PTLLM",
      "description": "Cheaper bit decoding improves the earlier grouped implementation at 0.2087x but leaves every custom multi-token case slower than SGLang. The one-token…"
    },
    {
      "id": "experiments/openkernel-router-broad-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-router-broad-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-router-broad-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel broad split-K router | PostTrainLLM",
      "description": "A fused kernel needs a measured dispatch range; correctness alone does not qualify a performance change. Retained outcome: regressed."
    },
    {
      "id": "experiments/openkernel-router-large-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-router-large-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-router-large-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel large-token router tile | PostTrainLLM",
      "description": "Keep per-shape improvements separate from demonstrated aggregate gains. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/openkernel-router-narrow-20261023",
      "url": "https://posttrainllm.com/experiments/openkernel-router-narrow-20261023",
      "md": "https://posttrainllm.com/experiments/openkernel-router-narrow-20261023.md",
      "kind": "experiment-record",
      "title": "Open Kernel narrow split-K router | PostTrainLLM",
      "description": "Preserve tiny-token and large-token baseline paths, and judge tile choices using both target-shape timing and aggregate uncertainty. Retained outcome:…"
    },
    {
      "id": "experiments/pace-clarify-v1-qwen4b-lora",
      "url": "https://posttrainllm.com/experiments/pace-clarify-v1-qwen4b-lora",
      "md": "https://posttrainllm.com/experiments/pace-clarify-v1-qwen4b-lora.md",
      "kind": "experiment-record",
      "title": "Pace clarify-v1 Qwen3-4B LoRA | PostTrainLLM",
      "description": "Fine-tuning a strong base on a thin behavior slice requires coverage for every dimension that must not regress. Retained outcome: regressed."
    },
    {
      "id": "experiments/pace-gemma-3-12b-drill-winner",
      "url": "https://posttrainllm.com/experiments/pace-gemma-3-12b-drill-winner",
      "md": "https://posttrainllm.com/experiments/pace-gemma-3-12b-drill-winner.md",
      "kind": "experiment-record",
      "title": "Pace Gemma-3-12B unhappy-path drill winner | PTLLM",
      "description": "A stronger zero-shot base beat the local fine-tunes, but model-selection evidence can be superseded by later broader gates. Retained outcome: worked with…"
    },
    {
      "id": "experiments/pace-intent-router-v8-sealed",
      "url": "https://posttrainllm.com/experiments/pace-intent-router-v8-sealed",
      "md": "https://posttrainllm.com/experiments/pace-intent-router-v8-sealed.md",
      "kind": "experiment-record",
      "title": "Pace intent router v8 sealed rejection | PostTrainLLM",
      "description": "A fast classifier can learn the generator rather than the action policy. Retained outcome: rejected."
    },
    {
      "id": "experiments/pace-next-step-apple-fm-20261005",
      "url": "https://posttrainllm.com/experiments/pace-next-step-apple-fm-20261005",
      "md": "https://posttrainllm.com/experiments/pace-next-step-apple-fm-20261005.md",
      "kind": "experiment-record",
      "title": "Pace next-step Apple FM availability blocker | PTLLM",
      "description": "Separate tool choice, stateful stopping, input-format compatibility, and acceptance evidence. Retained outcome: blocked."
    },
    {
      "id": "experiments/pace-next-step-gliner-20261004",
      "url": "https://posttrainllm.com/experiments/pace-next-step-gliner-20261004",
      "md": "https://posttrainllm.com/experiments/pace-next-step-gliner-20261004.md",
      "kind": "experiment-record",
      "title": "Pace next-step GLiNER zero-shot rejection | PTLLM",
      "description": "Zero-shot label matching does not establish stateful next-step control. Retained outcome: rejected."
    },
    {
      "id": "experiments/pace-next-step-jeff-base-20261005",
      "url": "https://posttrainllm.com/experiments/pace-next-step-jeff-base-20261005",
      "md": "https://posttrainllm.com/experiments/pace-next-step-jeff-base-20261005.md",
      "kind": "experiment-record",
      "title": "Pace next-step Jeff v1.2 base rejection | PostTrainLLM",
      "description": "Jeff base latency did not preserve clarification, action choice or stopping; qualify each behavior before choosing a fast router. Retained outcome: rejected."
    },
    {
      "id": "experiments/pace-next-step-jeff-tools-20261005",
      "url": "https://posttrainllm.com/experiments/pace-next-step-jeff-tools-20261005",
      "md": "https://posttrainllm.com/experiments/pace-next-step-jeff-tools-20261005.md",
      "kind": "experiment-record",
      "title": "Pace next-step Jeff v1.2 tools rejection | PTLLM",
      "description": "Jeff tools with the existing label contract remained weak on clarification and step control; a tool-oriented model is not a qualified policy replacement.…"
    },
    {
      "id": "experiments/pace-next-step-jeff-tools-native-20261005",
      "url": "https://posttrainllm.com/experiments/pace-next-step-jeff-tools-native-20261005",
      "md": "https://posttrainllm.com/experiments/pace-next-step-jeff-tools-native-20261005.md",
      "kind": "experiment-record",
      "title": "Pace next-step Jeff documented tools-format rejection | PTLLM",
      "description": "Jeff documented wording did not repair progress awareness; native format compatibility must be tested separately from DONE and task completion. Retained…"
    },
    {
      "id": "experiments/pace-next-step-jeff-tools-smoke-20261005",
      "url": "https://posttrainllm.com/experiments/pace-next-step-jeff-tools-smoke-20261005",
      "md": "https://posttrainllm.com/experiments/pace-next-step-jeff-tools-smoke-20261005.md",
      "kind": "experiment-record",
      "title": "Pace next-step Jeff frozen synthetic smoke rejection | PTLLM",
      "description": "The frozen Jeff synthetic smoke retained ambiguous and progress failures; disputed generator and teacher labels cannot establish acceptance. Retained…"
    },
    {
      "id": "experiments/pace-next-step-jev-20261004",
      "url": "https://posttrainllm.com/experiments/pace-next-step-jev-20261004",
      "md": "https://posttrainllm.com/experiments/pace-next-step-jev-20261004.md",
      "kind": "experiment-record",
      "title": "Pace next-step Jev teacher development baseline | PTLLM",
      "description": "Use the teacher as offline comparison evidence; runtime integration requires an on-device candidate. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/pace-next-step-qwen-20261004",
      "url": "https://posttrainllm.com/experiments/pace-next-step-qwen-20261004",
      "md": "https://posttrainllm.com/experiments/pace-next-step-qwen-20261004.md",
      "kind": "experiment-record",
      "title": "Pace next-step Qwen development baseline | PTLLM",
      "description": "Compare identical simulated loops and argument extractors rather than model-card scores. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/pace-next-step-qwen-20261005",
      "url": "https://posttrainllm.com/experiments/pace-next-step-qwen-20261005",
      "md": "https://posttrainllm.com/experiments/pace-next-step-qwen-20261005.md",
      "kind": "experiment-record",
      "title": "Pace next-step Qwen reproduced development baseline | PTLLM",
      "description": "Separate tool choice, stateful stopping, input-format compatibility, and acceptance evidence. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/pace-next-step-qwen-policy-20261008",
      "url": "https://posttrainllm.com/experiments/pace-next-step-qwen-policy-20261008",
      "md": "https://posttrainllm.com/experiments/pace-next-step-qwen-policy-20261008.md",
      "kind": "experiment-record",
      "title": "Pace frozen generated policy Qwen comparison | PTLLM",
      "description": "Preserve raw failures, generated provenance and unknown calibration/hardware measures; a fast or rules-perfect result does not qualify a planner…"
    },
    {
      "id": "experiments/pace-next-step-student-v1-20261004",
      "url": "https://posttrainllm.com/experiments/pace-next-step-student-v1-20261004",
      "md": "https://posttrainllm.com/experiments/pace-next-step-student-v1-20261004.md",
      "kind": "experiment-record",
      "title": "Pace next-step ModernBERT student v1 | PostTrainLLM",
      "description": "Student v1 left single-target clicks weak; label policy and independent evaluation must precede further teacher distillation. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/pace-next-step-student-v2-20261004",
      "url": "https://posttrainllm.com/experiments/pace-next-step-student-v2-20261004",
      "md": "https://posttrainllm.com/experiments/pace-next-step-student-v2-20261004.md",
      "kind": "experiment-record",
      "title": "Pace next-step ModernBERT student v2 | PostTrainLLM",
      "description": "Agreement filtering lowered student v2 full pass to 53.7%; agreement alone does not repair a disputed action policy. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/pace-next-step-student-v3-20261004",
      "url": "https://posttrainllm.com/experiments/pace-next-step-student-v3-20261004",
      "md": "https://posttrainllm.com/experiments/pace-next-step-student-v3-20261004.md",
      "kind": "experiment-record",
      "title": "Pace next-step ModernBERT student v3 | PostTrainLLM",
      "description": "Goal-phrased training improved student v3 clicks but regressed RESPOND; report per-class gates alongside aggregate full pass. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/pace-planner-v1-v4-early",
      "url": "https://posttrainllm.com/experiments/pace-planner-v1-v4-early",
      "md": "https://posttrainllm.com/experiments/pace-planner-v1-v4-early.md",
      "kind": "experiment-record",
      "title": "Pace planner v1-v4 early versions | PostTrainLLM",
      "description": "An unmeasured version is indistinguishable from a version that never ran. Four consecutive attempts left no score behind. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/pace-planner-v10",
      "url": "https://posttrainllm.com/experiments/pace-planner-v10",
      "md": "https://posttrainllm.com/experiments/pace-planner-v10.md",
      "kind": "experiment-record",
      "title": "Pace planner v10 parameterized actions | PostTrainLLM",
      "description": "v10 repeated v6's move of changing the output representation, and because it was never measured the v6 regression could not be checked for recurrence. Its…"
    },
    {
      "id": "experiments/pace-planner-v11",
      "url": "https://posttrainllm.com/experiments/pace-planner-v11",
      "md": "https://posttrainllm.com/experiments/pace-planner-v11.md",
      "kind": "experiment-record",
      "title": "Pace planner v11 ship-gate run | PostTrainLLM",
      "description": "Train loss 0.001 alongside 0% on out-of-scope and ambiguous inputs is the capacity ceiling stated plainly. The one-shot fixed gate was what finally ended…"
    },
    {
      "id": "experiments/pace-planner-v5",
      "url": "https://posttrainllm.com/experiments/pace-planner-v5",
      "md": "https://posttrainllm.com/experiments/pace-planner-v5.md",
      "kind": "experiment-record",
      "title": "Pace planner v5 hand-crafted gold + teacher paraphrase | PTLLM",
      "description": "A high score on a fixture a deterministic endpoint can also ace is a measurement of the harness, not the model. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/pace-planner-v6",
      "url": "https://posttrainllm.com/experiments/pace-planner-v6",
      "md": "https://posttrainllm.com/experiments/pace-planner-v6.md",
      "kind": "experiment-record",
      "title": "Pace planner v6 label-based output | PostTrainLLM",
      "description": "Changing the output representation is a capability change, not a formatting change. Retained outcome: regressed."
    },
    {
      "id": "experiments/pace-planner-v6-1",
      "url": "https://posttrainllm.com/experiments/pace-planner-v6-1",
      "md": "https://posttrainllm.com/experiments/pace-planner-v6-1.md",
      "kind": "experiment-record",
      "title": "Pace planner v6.1 four-adapter repair sweep | PTLLM",
      "description": "A four-way score collapse traced to prompt mismatch between training and serving. Pin the prompt, schema, and grammar triple across train, serve, and eval…"
    },
    {
      "id": "experiments/pace-planner-v7",
      "url": "https://posttrainllm.com/experiments/pace-planner-v7",
      "md": "https://posttrainllm.com/experiments/pace-planner-v7.md",
      "kind": "experiment-record",
      "title": "Pace planner v7 tools-in-prompt | PostTrainLLM",
      "description": "v7 is a numbering gap, not a training version. The eleven-version count includes a version that was never trained. Retained outcome: superseded."
    },
    {
      "id": "experiments/pace-planner-v8",
      "url": "https://posttrainllm.com/experiments/pace-planner-v8",
      "md": "https://posttrainllm.com/experiments/pace-planner-v8.md",
      "kind": "experiment-record",
      "title": "Pace planner v8 augmented corpus | PostTrainLLM",
      "description": "The 73% phantom. A score is only a score if the prompt, schema, and grammar it was measured under are recorded with it. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/pace-planner-v9",
      "url": "https://posttrainllm.com/experiments/pace-planner-v9",
      "md": "https://posttrainllm.com/experiments/pace-planner-v9.md",
      "kind": "experiment-record",
      "title": "Pace planner v9 compose | PostTrainLLM",
      "description": "Winning the happy-path fixture says nothing about ambiguous, out-of-scope, or destructive inputs, which is where the product actually needed the planner.…"
    },
    {
      "id": "experiments/pace-qwen35-challenger-round",
      "url": "https://posttrainllm.com/experiments/pace-qwen35-challenger-round",
      "md": "https://posttrainllm.com/experiments/pace-qwen35-challenger-round.md",
      "kind": "experiment-record",
      "title": "Pace Qwen3.5 challenger round | PostTrainLLM",
      "description": "Single-dimension wins do not justify a planner swap when another required dimension regresses. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/pace-thinking-models-unhappy-path",
      "url": "https://posttrainllm.com/experiments/pace-thinking-models-unhappy-path",
      "md": "https://posttrainllm.com/experiments/pace-thinking-models-unhappy-path.md",
      "kind": "experiment-record",
      "title": "Pace reasoning-model unhappy-path drill | PostTrainLLM",
      "description": "Reasoning models need adequate max tokens and a stop-on-think strategy before interpreting planner scores. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/pace-two-stage-ambiguity-shim-v2",
      "url": "https://posttrainllm.com/experiments/pace-two-stage-ambiguity-shim-v2",
      "md": "https://posttrainllm.com/experiments/pace-two-stage-ambiguity-shim-v2.md",
      "kind": "experiment-record",
      "title": "Pace two-stage ambiguity detector shim v2 | PTLLM",
      "description": "Rule wrappers can expose the missing behavior, but they still need the same regression gates as model updates. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/parakeet-wgsl-browser-asr-smoke",
      "url": "https://posttrainllm.com/experiments/parakeet-wgsl-browser-asr-smoke",
      "md": "https://posttrainllm.com/experiments/parakeet-wgsl-browser-asr-smoke.md",
      "kind": "experiment-record",
      "title": "Parakeet WGSL browser-ASR paired validation (2026-09-02) | PTLLM",
      "description": "Browser WebGPU ASR can beat a native large-model incumbent on both bounded WER and latency while still failing an absolute throughput target; short-clip…"
    },
    {
      "id": "experiments/public-artifact-registry",
      "url": "https://posttrainllm.com/experiments/public-artifact-registry",
      "md": "https://posttrainllm.com/experiments/public-artifact-registry.md",
      "kind": "experiment-record",
      "title": "Public artifact registry | PostTrainLLM",
      "description": "Public artifacts and blockers are first-class. Retained outcome: worked."
    },
    {
      "id": "experiments/speculative-heads-medusa-eagle-smoke",
      "url": "https://posttrainllm.com/experiments/speculative-heads-medusa-eagle-smoke",
      "md": "https://posttrainllm.com/experiments/speculative-heads-medusa-eagle-smoke.md",
      "kind": "experiment-record",
      "title": "Speculative-decoding heads Medusa/EAGLE smoke | PTLLM",
      "description": "Speculative heads are a valid local speed path, but the production recipe is data/training heavy rather than a quick sidecar smoke. Retained outcome: worked…"
    },
    {
      "id": "experiments/sql-blended-public-synthetic-v1",
      "url": "https://posttrainllm.com/experiments/sql-blended-public-synthetic-v1",
      "md": "https://posttrainllm.com/experiments/sql-blended-public-synthetic-v1.md",
      "kind": "experiment-record",
      "title": "Blended public+synthetic SFT | PostTrainLLM",
      "description": "Mixing domains is not automatically regularization; it can reduce both capabilities. Retained outcome: failed."
    },
    {
      "id": "experiments/sql-candidate-selection",
      "url": "https://posttrainllm.com/experiments/sql-candidate-selection",
      "md": "https://posttrainllm.com/experiments/sql-candidate-selection.md",
      "kind": "experiment-record",
      "title": "SQL candidate selection | PostTrainLLM",
      "description": "Candidate selection remains a plausible future method, but an unfrozen recipe is not unfinished evidence for this project. Retained outcome: rejected."
    },
    {
      "id": "experiments/sql-controlled-lora-rank-sweep",
      "url": "https://posttrainllm.com/experiments/sql-controlled-lora-rank-sweep",
      "md": "https://posttrainllm.com/experiments/sql-controlled-lora-rank-sweep.md",
      "kind": "experiment-record",
      "title": "Controlled SQL LoRA rank sweep | PostTrainLLM",
      "description": "Hyperparameter sweeps are valid only inside one frozen experiment contract; they are not project-completion chores. Retained outcome: rejected."
    },
    {
      "id": "experiments/sql-expanded-synthetic-sft-r4",
      "url": "https://posttrainllm.com/experiments/sql-expanded-synthetic-sft-r4",
      "md": "https://posttrainllm.com/experiments/sql-expanded-synthetic-sft-r4.md",
      "kind": "experiment-record",
      "title": "Expanded synthetic SQL SFT | PostTrainLLM",
      "description": "The synthetic SQL adapter is the current synthetic incumbent, but joins remain weaker than single-table rows. Retained outcome: worked."
    },
    {
      "id": "experiments/sql-factory-run-renderer",
      "url": "https://posttrainllm.com/experiments/sql-factory-run-renderer",
      "md": "https://posttrainllm.com/experiments/sql-factory-run-renderer.md",
      "kind": "experiment-record",
      "title": "SQL factory run renderer | PostTrainLLM",
      "description": "Rendered reports made SQL publishable, but the factory still needs command-level automation. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/sql-hygiene-dpo-higher-pressure",
      "url": "https://posttrainllm.com/experiments/sql-hygiene-dpo-higher-pressure",
      "md": "https://posttrainllm.com/experiments/sql-hygiene-dpo-higher-pressure.md",
      "kind": "experiment-record",
      "title": "Hygiene DPO higher-pressure retry (2026-07-11) | PTLLM",
      "description": "Composed DPO cannot fix output-format hygiene here Retained outcome: failed."
    },
    {
      "id": "experiments/sql-hygiene-dpo-refanchored",
      "url": "https://posttrainllm.com/experiments/sql-hygiene-dpo-refanchored",
      "md": "https://posttrainllm.com/experiments/sql-hygiene-dpo-refanchored.md",
      "kind": "experiment-record",
      "title": "Hygiene DPO reference-anchored retry (2026-07-11) | PTLLM",
      "description": "Reference-anchored DPO is the correct fix for the SimPO collapse Retained outcome: failed."
    },
    {
      "id": "experiments/sql-hygiene-simpo-dpo",
      "url": "https://posttrainllm.com/experiments/sql-hygiene-simpo-dpo",
      "md": "https://posttrainllm.com/experiments/sql-hygiene-simpo-dpo.md",
      "kind": "experiment-record",
      "title": "Hygiene SimPO/DPO | PostTrainLLM",
      "description": "Preference tuning needs reference anchoring, smaller updates, and composed-eval checks. Retained outcome: failed."
    },
    {
      "id": "experiments/sql-offline-rollout-oapl",
      "url": "https://posttrainllm.com/experiments/sql-offline-rollout-oapl",
      "md": "https://posttrainllm.com/experiments/sql-offline-rollout-oapl.md",
      "kind": "experiment-record",
      "title": "Offline rollout / OAPL-style SQL update | PostTrainLLM",
      "description": "Offline policy updates are downstream of reward validation; skipping the prerequisite is not a useful experiment. Retained outcome: rejected."
    },
    {
      "id": "experiments/sql-public-bmc2-v1",
      "url": "https://posttrainllm.com/experiments/sql-public-bmc2-v1",
      "md": "https://posttrainllm.com/experiments/sql-public-bmc2-v1.md",
      "kind": "experiment-record",
      "title": "Public b-mc2 v1 | PostTrainLLM",
      "description": "Public benchmark adaptation needs more coverage before tuning knobs matter. Retained outcome: failed."
    },
    {
      "id": "experiments/sql-public-bmc2-v2",
      "url": "https://posttrainllm.com/experiments/sql-public-bmc2-v2",
      "md": "https://posttrainllm.com/experiments/sql-public-bmc2-v2.md",
      "kind": "experiment-record",
      "title": "Public b-mc2 v2 | PostTrainLLM",
      "description": "Do not change data volume, rank, and training length in one uncontrolled jump. Retained outcome: failed."
    },
    {
      "id": "experiments/sql-public-bmc2-v3",
      "url": "https://posttrainllm.com/experiments/sql-public-bmc2-v3",
      "md": "https://posttrainllm.com/experiments/sql-public-bmc2-v3.md",
      "kind": "experiment-record",
      "title": "Public b-mc2 v3 | PostTrainLLM",
      "description": "The public recipe was directionally better, but not enough for a win. Retained outcome: failed."
    },
    {
      "id": "experiments/sql-public-bmc2-v4",
      "url": "https://posttrainllm.com/experiments/sql-public-bmc2-v4",
      "md": "https://posttrainllm.com/experiments/sql-public-bmc2-v4.md",
      "kind": "experiment-record",
      "title": "Public b-mc2 v4 | PostTrainLLM",
      "description": "A narrow public exact-match win can still damage the incumbent specialist behavior. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/sql-public-v4-synthetic-regression",
      "url": "https://posttrainllm.com/experiments/sql-public-v4-synthetic-regression",
      "md": "https://posttrainllm.com/experiments/sql-public-v4-synthetic-regression.md",
      "kind": "experiment-record",
      "title": "Public v4 synthetic regression check | PostTrainLLM",
      "description": "Every public benchmark gain needs a breadth/regression gate before packaging. Retained outcome: regressed."
    },
    {
      "id": "experiments/sql-routed-v1",
      "url": "https://posttrainllm.com/experiments/sql-routed-v1",
      "md": "https://posttrainllm.com/experiments/sql-routed-v1.md",
      "kind": "experiment-record",
      "title": "Routed public + synthetic adapters | PostTrainLLM",
      "description": "Routing preserves both measured slices, but artifact status still depends on public execution and performance evidence. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/sql-static-multilora-composition",
      "url": "https://posttrainllm.com/experiments/sql-static-multilora-composition",
      "md": "https://posttrainllm.com/experiments/sql-static-multilora-composition.md",
      "kind": "experiment-record",
      "title": "Static multi-LoRA composition | PostTrainLLM",
      "description": "Static composition cannot solve domain conflict when the right behavior depends on input type. Retained outcome: failed."
    },
    {
      "id": "experiments/sql-toy-sft-r4",
      "url": "https://posttrainllm.com/experiments/sql-toy-sft-r4",
      "md": "https://posttrainllm.com/experiments/sql-toy-sft-r4.md",
      "kind": "experiment-record",
      "title": "Toy SQL SFT | PostTrainLLM",
      "description": "The SFT loop mechanics work, but eval splits must be frozen before claiming quality. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/streamingllm-kivi-cache-compression",
      "url": "https://posttrainllm.com/experiments/streamingllm-kivi-cache-compression",
      "md": "https://posttrainllm.com/experiments/streamingllm-kivi-cache-compression.md",
      "kind": "experiment-record",
      "title": "StreamingLLM + KIVI cache compression | PostTrainLLM",
      "description": "KV compression can preserve greedy decode locally, but storage format and quality gates matter before making long-context claims. Retained outcome: worked…"
    },
    {
      "id": "experiments/technique-registry",
      "url": "https://posttrainllm.com/experiments/technique-registry",
      "md": "https://posttrainllm.com/experiments/technique-registry.md",
      "kind": "experiment-record",
      "title": "Technique registry | PostTrainLLM",
      "description": "Method names are not enough; recipes need failure mode, data, eval, slice gate, and stop rule. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/trainloop-style-tooling",
      "url": "https://posttrainllm.com/experiments/trainloop-style-tooling",
      "md": "https://posttrainllm.com/experiments/trainloop-style-tooling.md",
      "kind": "experiment-record",
      "title": "TrainLoop-style tooling | PostTrainLLM",
      "description": "Discipline is valuable only when enforced in every reported run. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/vibethinker-3b-agentic-distilled",
      "url": "https://posttrainllm.com/experiments/vibethinker-3b-agentic-distilled",
      "md": "https://posttrainllm.com/experiments/vibethinker-3b-agentic-distilled.md",
      "kind": "experiment-record",
      "title": "VibeThinker 3B agentic distilled variant | PTLLM",
      "description": "Preserved weights are not a ship decision. Retained outcome: inconclusive."
    },
    {
      "id": "experiments/wasm-backward-da-blocking",
      "url": "https://posttrainllm.com/experiments/wasm-backward-da-blocking",
      "md": "https://posttrainllm.com/experiments/wasm-backward-da-blocking.md",
      "kind": "experiment-record",
      "title": "WASM backward_dA blocking | PostTrainLLM",
      "description": "Training speed follows the backward-pass bottleneck; forward-only wins are capped until dA and dB are addressed. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/wasm-backward-scratch-reuse",
      "url": "https://posttrainllm.com/experiments/wasm-backward-scratch-reuse",
      "md": "https://posttrainllm.com/experiments/wasm-backward-scratch-reuse.md",
      "kind": "experiment-record",
      "title": "WASM backward-scratch reuse | PostTrainLLM",
      "description": "Hot-path hygiene is not the same as a performance win; measure the real step time before claiming speedup. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/wasm-register-cache-blocked-matmul",
      "url": "https://posttrainllm.com/experiments/wasm-register-cache-blocked-matmul",
      "md": "https://posttrainllm.com/experiments/wasm-register-cache-blocked-matmul.md",
      "kind": "experiment-record",
      "title": "WASM register/cache-blocked matmul | PostTrainLLM",
      "description": "Optimize and report on the real workload, not only on isolated single-kernel microbenches. Retained outcome: worked with caveat."
    },
    {
      "id": "experiments/wasm-simd-training-speedup",
      "url": "https://posttrainllm.com/experiments/wasm-simd-training-speedup",
      "md": "https://posttrainllm.com/experiments/wasm-simd-training-speedup.md",
      "kind": "experiment-record",
      "title": "WASM SIMD training speedup | PostTrainLLM",
      "description": "Emscripten/LLVM autovectorization was the right browser-training speed lever before hand-written kernels. Retained outcome: worked."
    },
    {
      "id": "experiments/yoco-cache-halving-smoke",
      "url": "https://posttrainllm.com/experiments/yoco-cache-halving-smoke",
      "md": "https://posttrainllm.com/experiments/yoco-cache-halving-smoke.md",
      "kind": "experiment-record",
      "title": "YOCO cache-halving smoke | PostTrainLLM",
      "description": "YOCO is a long-context memory lever, not an immediate short-context speedup. Retained outcome: worked with caveat."
    },
    {
      "id": "fine-tune-llm-on-mac",
      "url": "https://posttrainllm.com/fine-tune-llm-on-mac",
      "md": "https://posttrainllm.com/fine-tune-llm-on-mac.md",
      "kind": "application",
      "title": "How to train and fine-tune your own LLM on a Mac | PTLLM",
      "description": "Practical guide to train your own specialist LLM on Apple Silicon: define a target, LoRA/QLoRA post-train, evaluate against a frozen baseline, and package…"
    },
    {
      "id": "how-to-train-your-own-llm",
      "url": "https://posttrainllm.com/how-to-train-your-own-llm",
      "md": "https://posttrainllm.com/how-to-train-your-own-llm.md",
      "kind": "application",
      "title": "How to train your own LLM (without a GPU cluster) | PTLLM",
      "description": "What “train your own LLM” usually means in 2026: post-train a base model with LoRA/QLoRA, evaluate honestly, and ship a specialist. Includes Mac-local paths…"
    },
    {
      "id": "inference",
      "url": "https://posttrainllm.com/inference",
      "md": "https://posttrainllm.com/inference.md",
      "kind": "application",
      "title": "posttrainllm — in-browser inference",
      "description": "Run real LLMs fully client-side in your browser via WebGPU (transformers.js). Pull any ONNX model from Hugging Face by id, or pick a curated one — no…"
    },
    {
      "id": "inspiration",
      "url": "https://posttrainllm.com/inspiration",
      "md": "https://posttrainllm.com/inspiration.md",
      "kind": "application",
      "title": "Inspiration: the projects behind PostTrainLLM",
      "description": "A public thank-you to the tools and projects that shaped PostTrainLLM, with source links, local lessons, evidence, and clear boundaries."
    },
    {
      "id": "inspiration/apple-foundation-models",
      "url": "https://posttrainllm.com/inspiration/apple-foundation-models",
      "md": "https://posttrainllm.com/inspiration/apple-foundation-models.md",
      "kind": "inspiration",
      "title": "Apple Foundation Models: an inspiration for PostTrainLLM",
      "description": "Apple's on-device model gave us a useful floor to measure. Its limits on our action-grounding tasks clarified why the lab keeps its own weights and…"
    },
    {
      "id": "inspiration/aster",
      "url": "https://posttrainllm.com/inspiration/aster",
      "md": "https://posttrainllm.com/inspiration/aster.md",
      "kind": "inspiration",
      "title": "Aster AI Labs: an inspiration for PostTrainLLM",
      "description": "Aster's distributed research search is useful for understanding what massive parallel experimentation buys. We study the method and boundary without trying…"
    },
    {
      "id": "inspiration/baseten",
      "url": "https://posttrainllm.com/inspiration/baseten",
      "md": "https://posttrainllm.com/inspiration/baseten.md",
      "kind": "inspiration",
      "title": "Baseten: an inspiration for PostTrainLLM",
      "description": "Baseten's account of post-training helped us see the work as a full system: data, reward, performance, evaluation, and delivery. We translated that frame…"
    },
    {
      "id": "inspiration/bonsai-2",
      "url": "https://posttrainllm.com/inspiration/bonsai-2",
      "md": "https://posttrainllm.com/inspiration/bonsai-2.md",
      "kind": "inspiration",
      "title": "Bonsai 2: an inspiration for PostTrainLLM",
      "description": "Bonsai sharpened our habit of separating weight-file size from peak runtime memory and capability retained. A fair same-Mac comparison remains a proposed…"
    },
    {
      "id": "inspiration/castform",
      "url": "https://posttrainllm.com/inspiration/castform",
      "md": "https://posttrainllm.com/inspiration/castform.md",
      "kind": "inspiration",
      "title": "Castform: an inspiration for PostTrainLLM",
      "description": "Castform's trace and reward framing helped us draw a more inspectable route from an agent failure to training data. The local translation remains…"
    },
    {
      "id": "inspiration/cline",
      "url": "https://posttrainllm.com/inspiration/cline",
      "md": "https://posttrainllm.com/inspiration/cline.md",
      "kind": "inspiration",
      "title": "Cline: an inspiration for PostTrainLLM",
      "description": "Cline's explicit tool and context boundaries helped us reason about structured actions. We retained the lesson while leaving a new coding-agent product parked."
    },
    {
      "id": "inspiration/coreml-llm",
      "url": "https://posttrainllm.com/inspiration/coreml-llm",
      "md": "https://posttrainllm.com/inspiration/coreml-llm.md",
      "kind": "inspiration",
      "title": "CoreML-LLM: an inspiration for PostTrainLLM",
      "description": "CoreML-LLM is a community example of taking owned weights toward Apple's Neural Engine. It informs our research boundary; it is not a shipped PostTrainLLM…"
    },
    {
      "id": "inspiration/gigatoken",
      "url": "https://posttrainllm.com/inspiration/gigatoken",
      "md": "https://posttrainllm.com/inspiration/gigatoken.md",
      "kind": "inspiration",
      "title": "Gigatoken: an inspiration for PostTrainLLM",
      "description": "Gigatoken is a reminder to profile the boring first pass. Fast bulk tokenization can matter on a large corpus, though we have not found a current bottleneck…"
    },
    {
      "id": "inspiration/halo",
      "url": "https://posttrainllm.com/inspiration/halo",
      "md": "https://posttrainllm.com/inspiration/halo.md",
      "kind": "inspiration",
      "title": "Halo: an inspiration for PostTrainLLM",
      "description": "Halo brings pre-training, SFT, preference work, and RL into one training framework that spans a GPU and clusters. For this lab it is a map of the single-Mac…"
    },
    {
      "id": "inspiration/hugging-face",
      "url": "https://posttrainllm.com/inspiration/hugging-face",
      "md": "https://posttrainllm.com/inspiration/hugging-face.md",
      "kind": "inspiration",
      "title": "Hugging Face: an inspiration for PostTrainLLM",
      "description": "The model hub made small public SQL specialists available as real baselines. Those models helped us ask whether a local result survives comparison on the…"
    },
    {
      "id": "inspiration/mlx",
      "url": "https://posttrainllm.com/inspiration/mlx",
      "md": "https://posttrainllm.com/inspiration/mlx.md",
      "kind": "inspiration",
      "title": "MLX: an inspiration for PostTrainLLM",
      "description": "MLX is a foundational Mac-local reference for training and inference. We study its implementation and use the platform where it fits while keeping our own…"
    },
    {
      "id": "inspiration/needle-2",
      "url": "https://posttrainllm.com/inspiration/needle-2",
      "md": "https://posttrainllm.com/inspiration/needle-2.md",
      "kind": "inspiration",
      "title": "Needle 2: an inspiration for PostTrainLLM",
      "description": "Needle 2's tiny tool-calling package deserved a direct Mac test. The result was negative on our gate, and keeping that result visible is part of the credit…"
    },
    {
      "id": "inspiration/omlx",
      "url": "https://posttrainllm.com/inspiration/omlx",
      "md": "https://posttrainllm.com/inspiration/omlx.md",
      "kind": "inspiration",
      "title": "oMLX: an inspiration for PostTrainLLM",
      "description": "oMLX is a reference for the serving problems that appear on a single Mac: memory tiers, KV management, and concurrent requests. We keep it as a comparison…"
    },
    {
      "id": "inspiration/parakeet-wgsl",
      "url": "https://posttrainllm.com/inspiration/parakeet-wgsl",
      "md": "https://posttrainllm.com/inspiration/parakeet-wgsl.md",
      "kind": "inspiration",
      "title": "parakeet.wgsl: an inspiration for PostTrainLLM",
      "description": "Public kernels, a package format, and a reproducible browser run made parakeet.wgsl a concrete runtime lesson. We verified execution locally without…"
    },
    {
      "id": "inspiration/prime-intellect",
      "url": "https://posttrainllm.com/inspiration/prime-intellect",
      "md": "https://posttrainllm.com/inspiration/prime-intellect.md",
      "kind": "inspiration",
      "title": "Prime Intellect: an inspiration for PostTrainLLM",
      "description": "Prime Intellect helps us map the work that distributed training can absorb and the coordination a single machine never sees. That is a learning boundary,…"
    },
    {
      "id": "inspiration/qorl",
      "url": "https://posttrainllm.com/inspiration/qorl",
      "md": "https://posttrainllm.com/inspiration/qorl.md",
      "kind": "inspiration",
      "title": "QORL: an inspiration for PostTrainLLM",
      "description": "QORL helped us ask a harder database question: does offline search still win after a native planner baseline, held-out parameters, routing overhead, and…"
    },
    {
      "id": "inspiration/savante-aryabhata",
      "url": "https://posttrainllm.com/inspiration/savante-aryabhata",
      "md": "https://posttrainllm.com/inspiration/savante-aryabhata.md",
      "kind": "inspiration",
      "title": "Savante and Aryabhata: an inspiration for PostTrainLLM",
      "description": "Their mathematics specialist is a useful study of curated data, filtered traces, and verifiable rewards as one recipe. We have studied the published work,…"
    },
    {
      "id": "inspiration/splash",
      "url": "https://posttrainllm.com/inspiration/splash",
      "md": "https://posttrainllm.com/inspiration/splash.md",
      "kind": "inspiration",
      "title": "Splash: an inspiration for PostTrainLLM",
      "description": "Splash shows what a model-specific Mac engine can gain by specializing kernels, weights, cache, and startup memory. Its published numbers are the team's…"
    },
    {
      "id": "inspiration/sqlcoder",
      "url": "https://posttrainllm.com/inspiration/sqlcoder",
      "md": "https://posttrainllm.com/inspiration/sqlcoder.md",
      "kind": "inspiration",
      "title": "SQLCoder and Arctic Text2SQL: an inspiration for PostTrainLLM",
      "description": "These SQL projects raised the standard of evidence. A query that resembles the reference text is less useful than a query that executes correctly against a…"
    },
    {
      "id": "inspiration/teale-petals",
      "url": "https://posttrainllm.com/inspiration/teale-petals",
      "md": "https://posttrainllm.com/inspiration/teale-petals.md",
      "kind": "inspiration",
      "title": "teale and Petals: an inspiration for PostTrainLLM",
      "description": "These decentralized inference projects make the latency cost of sharding a model across machines tangible. The comparison helps explain why a single-Mac…"
    },
    {
      "id": "inspiration/trainloop-ai",
      "url": "https://posttrainllm.com/inspiration/trainloop-ai",
      "md": "https://posttrainllm.com/inspiration/trainloop-ai.md",
      "kind": "inspiration",
      "title": "TrainLoop AI: an inspiration for PostTrainLLM",
      "description": "TrainLoop made us pay attention to the attempts that failed, the slices that changed, and the traces behind a score. That discipline shaped how this small…"
    },
    {
      "id": "inspiration/transformer-explainer",
      "url": "https://posttrainllm.com/inspiration/transformer-explainer",
      "md": "https://posttrainllm.com/inspiration/transformer-explainer.md",
      "kind": "inspiration",
      "title": "Transformer Explainer: an inspiration for PostTrainLLM",
      "description": "A live, inspectable GPT-2 in the browser gives learners something to manipulate after a forward-pass walkthrough. It sets a useful bar for explanations that…"
    },
    {
      "id": "inspiration/vllm",
      "url": "https://posttrainllm.com/inspiration/vllm",
      "md": "https://posttrainllm.com/inspiration/vllm.md",
      "kind": "inspiration",
      "title": "vLLM: an inspiration for PostTrainLLM",
      "description": "vLLM makes scheduling, paged KV, and batching legible as serving problems. We study that architecture to understand which constraints carry over to one Mac…"
    },
    {
      "id": "inspiration/weco",
      "url": "https://posttrainllm.com/inspiration/weco",
      "md": "https://posttrainllm.com/inspiration/weco.md",
      "kind": "inspiration",
      "title": "Weco AI: an inspiration for PostTrainLLM",
      "description": "Weco's traceable, steerable autoresearch loop is a candidate to study when we have a concrete target, frozen evaluation, and fixed cost budget. It is on our…"
    },
    {
      "id": "leaderboard",
      "url": "https://posttrainllm.com/leaderboard",
      "md": "https://posttrainllm.com/leaderboard.md",
      "kind": "application",
      "title": "posttrainllm — leaderboard",
      "description": "Browser-trained, browser-runnable LLMs ranked on small benchmarks. Pareto views by params and by training compute."
    },
    {
      "id": "learn",
      "url": "https://posttrainllm.com/learn",
      "md": "https://posttrainllm.com/learn.md",
      "kind": "application",
      "title": "Mac-local LLM specialist factory | PostTrainLLM",
      "description": "Follow the source-linked loop from target and data through post-training, evaluation, packaging, and an honest ship, retry, or reject report."
    },
    {
      "id": "learn/artifacts/browser-asr-case",
      "url": "https://posttrainllm.com/learn/artifacts/browser-asr-case",
      "md": "https://posttrainllm.com/learn/artifacts/browser-asr-case.md",
      "kind": "learning-artifact",
      "title": "Parakeet browser ASR receipt | PostTrainLLM",
      "description": "A paired browser/native ASR lab: Parakeet wins bounded WER and latency while a frozen 50x short-clip throughput gate catches fixed dispatch cost."
    },
    {
      "id": "learn/artifacts/browser-tinygpt",
      "url": "https://posttrainllm.com/learn/artifacts/browser-tinygpt",
      "md": "https://posttrainllm.com/learn/artifacts/browser-tinygpt.md",
      "kind": "learning-artifact",
      "title": "Browser-trained TinyGPT | PostTrainLLM",
      "description": "The same learning loop made visible through loss, sampling, presets, workers, WASM, and WebGPU-capable browser surfaces."
    },
    {
      "id": "learn/artifacts/byte-tinygpt",
      "url": "https://posttrainllm.com/learn/artifacts/byte-tinygpt",
      "md": "https://posttrainllm.com/learn/artifacts/byte-tinygpt.md",
      "kind": "learning-artifact",
      "title": "Byte-level TinyGPT | PostTrainLLM",
      "description": "A readable ~0.8M-parameter transformer whose byte tokenizer, architecture, loss, and checkpoint format are all inspectable."
    },
    {
      "id": "learn/artifacts/causal-probe-dossier",
      "url": "https://posttrainllm.com/learn/artifacts/causal-probe-dossier",
      "md": "https://posttrainllm.com/learn/artifacts/causal-probe-dossier.md",
      "kind": "learning-artifact",
      "title": "Causal probe dossier | PostTrainLLM",
      "description": "A logit lens, linear probe, activation patch, causal trace, or sparse autoencoder investigation with negative controls and an intervention claim."
    },
    {
      "id": "learn/artifacts/distilled-tool-caller",
      "url": "https://posttrainllm.com/learn/artifacts/distilled-tool-caller",
      "md": "https://posttrainllm.com/learn/artifacts/distilled-tool-caller.md",
      "kind": "learning-artifact",
      "title": "Distilled tool-calling specialist | PostTrainLLM",
      "description": "A real lineage where narrow file-operation depth reached 100% while breadth regressed, proving why routing is part of the artifact."
    },
    {
      "id": "learn/artifacts/factory-report-card",
      "url": "https://posttrainllm.com/learn/artifacts/factory-report-card",
      "md": "https://posttrainllm.com/learn/artifacts/factory-report-card.md",
      "kind": "learning-artifact",
      "title": "Specialist factory report card | PostTrainLLM",
      "description": "A run directory that binds target, data, candidate, frozen evaluation, packaging evidence, resource measurements, and a terminal ship/retry/reject decision."
    },
    {
      "id": "learn/artifacts/kernel-parity-receipt",
      "url": "https://posttrainllm.com/learn/artifacts/kernel-parity-receipt",
      "md": "https://posttrainllm.com/learn/artifacts/kernel-parity-receipt.md",
      "kind": "learning-artifact",
      "title": "Kernel parity and speed receipt | PostTrainLLM",
      "description": "A numerical and performance comparison that keeps reference math, optimized kernel, dispatch geometry, and end-to-end effect separate."
    },
    {
      "id": "learn/artifacts/local-tool-agent",
      "url": "https://posttrainllm.com/learn/artifacts/local-tool-agent",
      "md": "https://posttrainllm.com/learn/artifacts/local-tool-agent.md",
      "kind": "learning-artifact",
      "title": "Local tool-using agent | PostTrainLLM",
      "description": "An OpenAI-compatible local model server plus a multi-turn tool loop with schema validation and explicit execution policy."
    },
    {
      "id": "learn/artifacts/lora-specialist",
      "url": "https://posttrainllm.com/learn/artifacts/lora-specialist",
      "md": "https://posttrainllm.com/learn/artifacts/lora-specialist.md",
      "kind": "learning-artifact",
      "title": "LoRA specialist adapter | PostTrainLLM",
      "description": "A narrow adapter built from a frozen base, traceable data, explicit LoRA geometry, and a held-out task gate."
    },
    {
      "id": "learn/artifacts/mac-runtime-boundary-map",
      "url": "https://posttrainllm.com/learn/artifacts/mac-runtime-boundary-map",
      "md": "https://posttrainllm.com/learn/artifacts/mac-runtime-boundary-map.md",
      "kind": "learning-artifact",
      "title": "Mac runtime boundary map | PostTrainLLM",
      "description": "A comparison of owned MLX weights, Core ML deployment, Apple Foundation Models, and browser runtimes grounded in measured capability limits."
    },
    {
      "id": "learn/artifacts/mlx-specialist-package",
      "url": "https://posttrainllm.com/learn/artifacts/mlx-specialist-package",
      "md": "https://posttrainllm.com/learn/artifacts/mlx-specialist-package.md",
      "kind": "learning-artifact",
      "title": "Validated MLX specialist package | PostTrainLLM",
      "description": "A model or adapter exported with identity, tensors, tokenizer, prompt contract, and evidence that the consumer can load it correctly."
    },
    {
      "id": "learn/artifacts/needle-selection-ruler",
      "url": "https://posttrainllm.com/learn/artifacts/needle-selection-ruler",
      "md": "https://posttrainllm.com/learn/artifacts/needle-selection-ruler.md",
      "kind": "learning-artifact",
      "title": "Needle 2 selection ruler | PostTrainLLM",
      "description": "A complete tiny-model journey from catalog ablation through a 2x2 distractor-and-safety training factorial, ending at a measured 45M capacity boundary."
    },
    {
      "id": "learn/artifacts/tiny-overfit-receipt",
      "url": "https://posttrainllm.com/learn/artifacts/tiny-overfit-receipt",
      "md": "https://posttrainllm.com/learn/artifacts/tiny-overfit-receipt.md",
      "kind": "learning-artifact",
      "title": "Tiny-overfit correctness receipt | PostTrainLLM",
      "description": "A minimal proof that data loading, forward pass, backpropagation, optimizer state, sampling, and checkpoint reload agree."
    },
    {
      "id": "learn/paths/architecture-and-kernels",
      "url": "https://posttrainllm.com/learn/paths/architecture-and-kernels",
      "md": "https://posttrainllm.com/learn/paths/architecture-and-kernels.md",
      "kind": "learning-path",
      "title": "Architecture and kernel execution | PostTrainLLM",
      "description": "Match one optimized attention or matmul path against the readable reference and identify the real bottleneck with a measured curve. Mastery is demonstrated…"
    },
    {
      "id": "learn/paths/browser-and-mac-runtime",
      "url": "https://posttrainllm.com/learn/paths/browser-and-mac-runtime",
      "md": "https://posttrainllm.com/learn/paths/browser-and-mac-runtime.md",
      "kind": "learning-path",
      "title": "Browser, WASM, WebGPU, MLX, and Apple runtime | PTLLM",
      "description": "Compare the historical unqualified WebGPU curve and its missing receipt, Memory64 limit, Apple action-grounding result, and Parakeet browser receipt as four…"
    },
    {
      "id": "learn/paths/evaluation-and-factory",
      "url": "https://posttrainllm.com/learn/paths/evaluation-and-factory",
      "md": "https://posttrainllm.com/learn/paths/evaluation-and-factory.md",
      "kind": "learning-path",
      "title": "Evaluation, evidence, and the specialist factory | PTLLM",
      "description": "Audit Needle, Chess, and 2048 and explain how the ruler or safety gate changed the decision before integration or training. Mastery is demonstrated when the…"
    },
    {
      "id": "learn/paths/foundations",
      "url": "https://posttrainllm.com/learn/paths/foundations",
      "md": "https://posttrainllm.com/learn/paths/foundations.md",
      "kind": "learning-path",
      "title": "Foundations to transformer | PostTrainLLM",
      "description": "Complete the toy calculation or implementation in Modules 1-7 and explain its tensor shapes aloud. Mastery is demonstrated when the learner can trace text…"
    },
    {
      "id": "learn/paths/interpretability",
      "url": "https://posttrainllm.com/learn/paths/interpretability",
      "md": "https://posttrainllm.com/learn/paths/interpretability.md",
      "kind": "learning-path",
      "title": "Interpretability with causal discipline | PostTrainLLM",
      "description": "Take one behavioral failure and write a probe hypothesis, negative control, intervention, and decision-changing prediction. Mastery is demonstrated when the…"
    },
    {
      "id": "learn/paths/post-training",
      "url": "https://posttrainllm.com/learn/paths/post-training",
      "md": "https://posttrainllm.com/learn/paths/post-training.md",
      "kind": "learning-path",
      "title": "SFT, adapters, preference tuning, and distillation | PTLLM",
      "description": "Reconstruct the SQL and file-ops lineages, including the variable changed, target gain, regression, and decision at each step. Mastery is demonstrated when…"
    },
    {
      "id": "learn/paths/quantization-and-packaging",
      "url": "https://posttrainllm.com/learn/paths/quantization-and-packaging",
      "md": "https://posttrainllm.com/learn/paths/quantization-and-packaging.md",
      "kind": "learning-path",
      "title": "Quantization, pruning, and artifact packaging | PTLLM",
      "description": "Audit one int4 or pruned artifact from source weights through file size, load parity, quality, RAM, and runtime measurement. Mastery is demonstrated when…"
    },
    {
      "id": "learn/paths/runtime-and-agents",
      "url": "https://posttrainllm.com/learn/paths/runtime-and-agents",
      "md": "https://posttrainllm.com/learn/paths/runtime-and-agents.md",
      "kind": "learning-path",
      "title": "Inference, serving, tools, and long context | PTLLM",
      "description": "Calculate KV memory, compare cold versus reused-prefill latency, and trace one tool request through model output, validation, and execution policy. Mastery…"
    },
    {
      "id": "learn/paths/training-mechanics",
      "url": "https://posttrainllm.com/learn/paths/training-mechanics",
      "md": "https://posttrainllm.com/learn/paths/training-mechanics.md",
      "kind": "learning-path",
      "title": "Training mechanics and stability | PostTrainLLM",
      "description": "Inspect one successful tiny-overfit and one failed ordinary run, then diagnose data, optimization, capacity, and evaluation separately. Mastery is…"
    },
    {
      "id": "learn/session",
      "url": "https://posttrainllm.com/learn/session",
      "md": "https://posttrainllm.com/learn/session.md",
      "kind": "application",
      "title": "Learn language models from first principles | PostTrainLLM",
      "description": "Learn parameters, gradients, tensors, transformers, post-training, and evaluation through public lessons, browser-local exercises, and delayed recall."
    },
    {
      "id": "mlx-lora-fine-tuning",
      "url": "https://posttrainllm.com/mlx-lora-fine-tuning",
      "md": "https://posttrainllm.com/mlx-lora-fine-tuning.md",
      "kind": "application",
      "title": "MLX LoRA fine-tuning on Apple Silicon | PTLLM",
      "description": "Learn the MLX LoRA and QLoRA workflow on Apple Silicon, from JSONL data and bounded training to evaluation, fusion, and evidence."
    },
    {
      "id": "playground",
      "url": "https://posttrainllm.com/playground",
      "md": "https://posttrainllm.com/playground.md",
      "kind": "application",
      "title": "posttrainllm — train a real transformer in your browser tab",
      "description": "Train a real GPT-2 from scratch in your browser tab with hand-written, parity-tested WASM and WebGPU backends. A paired Apple M5 Pro receipt verifies 10.67x…"
    },
    {
      "id": "posttrainllm-vs-axolotl",
      "url": "https://posttrainllm.com/posttrainllm-vs-axolotl",
      "md": "https://posttrainllm.com/posttrainllm-vs-axolotl.md",
      "kind": "application",
      "title": "PostTrainLLM vs Axolotl for LLM fine-tuning | PTLLM",
      "description": "Compare PostTrainLLM's Apple Silicon specialist-model workflow with Axolotl's configuration-driven LLM fine-tuning framework."
    },
    {
      "id": "posttrainllm-vs-unsloth",
      "url": "https://posttrainllm.com/posttrainllm-vs-unsloth",
      "md": "https://posttrainllm.com/posttrainllm-vs-unsloth.md",
      "kind": "application",
      "title": "PostTrainLLM vs Unsloth for local LLM fine-tuning | PTLLM",
      "description": "Compare PostTrainLLM's Apple Silicon specialist-model factory with Unsloth's optimized LLM training and inference framework."
    },
    {
      "id": "recipes",
      "url": "https://posttrainllm.com/recipes",
      "md": "https://posttrainllm.com/recipes.md",
      "kind": "application",
      "title": "posttrainllm — recipes",
      "description": "The recipe log: named post-training and packaging recipes for posttrainllm. Each names a failure mode, its data, an eval gate, and a stop rule — not just…"
    },
    {
      "id": "recipes/constrained-generation",
      "url": "https://posttrainllm.com/recipes/constrained-generation",
      "md": "https://posttrainllm.com/recipes/constrained-generation.md",
      "kind": "recipe",
      "title": "Constrained generation | PostTrainLLM",
      "description": "Structured tool calls, SQL, and schema-bound outputs. A capable model emits invalid syntax or forbidden output shapes."
    },
    {
      "id": "recipes/distillation",
      "url": "https://posttrainllm.com/recipes/distillation",
      "md": "https://posttrainllm.com/recipes/distillation.md",
      "kind": "recipe",
      "title": "Specialist distillation | PostTrainLLM",
      "description": "Compress a frontier or larger-model capability into a routed Mac-local specialist.. A small base lacks a narrow behavior that a qualified teacher can…"
    },
    {
      "id": "recipes/evolution-strategies",
      "url": "https://posttrainllm.com/recipes/evolution-strategies",
      "md": "https://posttrainllm.com/recipes/evolution-strategies.md",
      "kind": "recipe",
      "title": "Evolution strategies | PostTrainLLM",
      "description": "Gradient-free optimization when rewards are evaluable but differentiation is unavailable.. The objective cannot provide useful gradients or the model/policy…"
    },
    {
      "id": "recipes/galore-stability",
      "url": "https://posttrainllm.com/recipes/galore-stability",
      "md": "https://posttrainllm.com/recipes/galore-stability.md",
      "kind": "recipe",
      "title": "GaLore and training stability | PostTrainLLM",
      "description": "Reduce optimizer memory or stabilize deep training.. Optimizer state or unstable gradients block an otherwise valid training recipe."
    },
    {
      "id": "recipes/interpretability",
      "url": "https://posttrainllm.com/recipes/interpretability",
      "md": "https://posttrainllm.com/recipes/interpretability.md",
      "kind": "recipe",
      "title": "Interpretability probes | PostTrainLLM",
      "description": "Diagnose a measured model failure without treating a visualization as causal proof.. Aggregate scores cannot explain which layers, tokens, or…"
    },
    {
      "id": "recipes/lora",
      "url": "https://posttrainllm.com/recipes/lora",
      "md": "https://posttrainllm.com/recipes/lora.md",
      "kind": "recipe",
      "title": "LoRA, DoRA, and adapter geometry | PostTrainLLM",
      "description": "Adapt a frozen Mac-local base to one narrow behavior.. The base misses a bounded task and full fine-tuning is unnecessary or too costly."
    },
    {
      "id": "recipes/moe",
      "url": "https://posttrainllm.com/recipes/moe",
      "md": "https://posttrainllm.com/recipes/moe.md",
      "kind": "recipe",
      "title": "Sparse mixture of experts | PostTrainLLM",
      "description": "Increase conditional capacity while keeping active compute bounded.. A dense model lacks capacity and a true sparse execution path is available."
    },
    {
      "id": "recipes/mtp",
      "url": "https://posttrainllm.com/recipes/mtp",
      "md": "https://posttrainllm.com/recipes/mtp.md",
      "kind": "recipe",
      "title": "Multi-token prediction | PostTrainLLM",
      "description": "Improve training signal or support speculative multi-token heads.. Single-token supervision or decode throughput is the measured bottleneck."
    },
    {
      "id": "recipes/needle2-evaluation",
      "url": "https://posttrainllm.com/recipes/needle2-evaluation",
      "md": "https://posttrainllm.com/recipes/needle2-evaluation.md",
      "kind": "recipe",
      "title": "Needle 45M successor factorial | PostTrainLLM",
      "description": "Test whether distractor-rich selection data and explicit refusal/confirmation examples can make a 45M tool selector safe and more accurate than stock.. Tiny…"
    },
    {
      "id": "recipes/optimizers",
      "url": "https://posttrainllm.com/recipes/optimizers",
      "md": "https://posttrainllm.com/recipes/optimizers.md",
      "kind": "recipe",
      "title": "Optimizer and schedule selection | PostTrainLLM",
      "description": "Make a correct training recipe converge stably within Mac memory and time bounds.. Loss spikes, under-updating, or optimizer memory blocks a frozen recipe."
    },
    {
      "id": "recipes/parakeet-browser-asr",
      "url": "https://posttrainllm.com/recipes/parakeet-browser-asr",
      "md": "https://posttrainllm.com/recipes/parakeet-browser-asr.md",
      "kind": "recipe",
      "title": "Parakeet WGSL browser ASR | PostTrainLLM",
      "description": "Test whether long-form ASR can run locally in Chrome through WebGPU.. Browser audio ingestion may be too slow, too large, nondeterministic, or…"
    },
    {
      "id": "recipes/peft-variants",
      "url": "https://posttrainllm.com/recipes/peft-variants",
      "md": "https://posttrainllm.com/recipes/peft-variants.md",
      "kind": "recipe",
      "title": "Parameter-efficient fine-tuning variants | PTLLM",
      "description": "Trade adapter capacity, initialization, and storage for one narrow fine-tuning target.. Plain LoRA has a measured geometry, capacity, quantization, or…"
    },
    {
      "id": "recipes/precision",
      "url": "https://posttrainllm.com/recipes/precision",
      "md": "https://posttrainllm.com/recipes/precision.md",
      "kind": "recipe",
      "title": "Precision and numerical gates | PostTrainLLM",
      "description": "Reduce memory or improve throughput without invalidating model math.. Precision choice causes overflow, drift, excess memory, or slow execution."
    },
    {
      "id": "recipes/pruning",
      "url": "https://posttrainllm.com/recipes/pruning",
      "md": "https://posttrainllm.com/recipes/pruning.md",
      "kind": "recipe",
      "title": "Unstructured and structured pruning | PostTrainLLM",
      "description": "Reduce stored or executed model structure after capability is proven.. Artifact size or dense topology is the measured deployment bottleneck."
    },
    {
      "id": "recipes/quantization",
      "url": "https://posttrainllm.com/recipes/quantization",
      "md": "https://posttrainllm.com/recipes/quantization.md",
      "kind": "recipe",
      "title": "Quantization and storage formats | PostTrainLLM",
      "description": "Reduce model download, RAM, or execution cost on Mac and browser runtimes.. Full precision exceeds the target's distribution or memory budget."
    },
    {
      "id": "recipes/speculative-heads",
      "url": "https://posttrainllm.com/recipes/speculative-heads",
      "md": "https://posttrainllm.com/recipes/speculative-heads.md",
      "kind": "recipe",
      "title": "Speculative heads and decoding | PostTrainLLM",
      "description": "Increase local decode throughput after model quality is accepted.. Autoregressive decode latency is the measured user-visible bottleneck."
    },
    {
      "id": "recipes/sql-lineage",
      "url": "https://posttrainllm.com/recipes/sql-lineage",
      "md": "https://posttrainllm.com/recipes/sql-lineage.md",
      "kind": "recipe",
      "title": "SQL specialist lineage | PostTrainLLM",
      "description": "Generate or select executable SQL on frozen schemas.. Small-model SQL gains fail to generalize across public and synthetic domains or emit prose wrappers."
    },
    {
      "id": "recipes/streaming-kivi",
      "url": "https://posttrainllm.com/recipes/streaming-kivi",
      "md": "https://posttrainllm.com/recipes/streaming-kivi.md",
      "kind": "recipe",
      "title": "StreamingLLM and KIVI cache compression | PostTrainLLM",
      "description": "Bound or compress KV memory for long local contexts.. KV cache growth, not model weights, is the measured memory blocker."
    },
    {
      "id": "report-cards/qwen06-sql-routed-v1",
      "url": "https://posttrainllm.com/report-cards/qwen06-sql-routed-v1",
      "md": "https://posttrainllm.com/report-cards/qwen06-sql-routed-v1.md",
      "kind": "report-card",
      "title": "Fine-Tune Report Card — sql-routed-specialist-poc — routed-sft-lora",
      "description": "Retry — eval: The routed setup is the current best SQL candidate and passes the current public exact plus synthetic execution gates, but it is not a shipped…"
    },
    {
      "id": "report-cards/qwen3-4b-file-ops-distilled",
      "url": "https://posttrainllm.com/report-cards/qwen3-4b-file-ops-distilled",
      "md": "https://posttrainllm.com/report-cards/qwen3-4b-file-ops-distilled.md",
      "kind": "report-card",
      "title": "Fine-Tune Report Card — Qwen3-4B File-Ops Distilled",
      "description": "Shipped: ship only as a routed file-ops specialist; do not use as the general planner"
    },
    {
      "id": "report-cards/qwen3-4b-rest-fused",
      "url": "https://posttrainllm.com/report-cards/qwen3-4b-rest-fused",
      "md": "https://posttrainllm.com/report-cards/qwen3-4b-rest-fused.md",
      "kind": "report-card",
      "title": "Fine-Tune Report Card — Qwen3-4B ReST Fused",
      "description": "Shipped: retain only as a routed file-operations specialist; reject as a general successor and do not use as the Pace default planner"
    },
    {
      "id": "roadmap",
      "url": "https://posttrainllm.com/roadmap",
      "md": "https://posttrainllm.com/roadmap.md",
      "kind": "application",
      "title": "posttrainllm — the performance journey",
      "description": "The performance journey of posttrainllm — every speed lever, what's shipped, what's blocked, and why."
    },
    {
      "id": "sae-timeline",
      "url": "https://posttrainllm.com/sae-timeline",
      "md": "https://posttrainllm.com/sae-timeline.md",
      "kind": "application",
      "title": "posttrainllm — SAE timeline",
      "description": "Drop a posttrainllm SAE timeline JSONL to see reconstruction error and sparse-feature activity over checkpoints."
    },
    {
      "id": "speedup",
      "url": "https://posttrainllm.com/speedup",
      "md": "https://posttrainllm.com/speedup.md",
      "kind": "application",
      "title": "posttrainllm — verified WebGPU speed on one Mac",
      "description": "A paired Apple M5 Pro WebGPU-versus-WASM receipt verifies 10.67x on the Large preset; the older multi-preset curve remains historical."
    },
    {
      "id": "studies",
      "url": "https://posttrainllm.com/studies",
      "md": "https://posttrainllm.com/studies.md",
      "kind": "application",
      "title": "Studied projects and research | PostTrainLLM",
      "description": "Canonical, source-linked evidence dossiers for every external product, model, platform, technical writeup, and industry case study retained by PostTrainLLM."
    },
    {
      "id": "studies/apple-on-device-foundation-models",
      "url": "https://posttrainllm.com/studies/apple-on-device-foundation-models",
      "md": "https://posttrainllm.com/studies/apple-on-device-foundation-models.md",
      "kind": "study",
      "title": "Apple on-device Foundation Models | PostTrainLLM",
      "description": "Apple's system model is a free and private routing floor, but its context and action-grounding limits make it unsuitable as the core capability dependency…"
    },
    {
      "id": "studies/baseten-post-training",
      "url": "https://posttrainllm.com/studies/baseten-post-training",
      "md": "https://posttrainllm.com/studies/baseten-post-training.md",
      "kind": "study",
      "title": "Baseten post-training positioning | PostTrainLLM",
      "description": "Post-training is a system of custom data, reward shaping, performance work, infrastructure, evaluation, and packaging rather than a generic fine-tuning…"
    },
    {
      "id": "studies/bonsai-2-27b",
      "url": "https://posttrainllm.com/studies/bonsai-2-27b",
      "md": "https://posttrainllm.com/studies/bonsai-2-27b.md",
      "kind": "study",
      "title": "Bonsai 2 27B | PostTrainLLM",
      "description": "Ternary representation, packing overhead, activation transforms, kernel support, artifact size, runtime memory, and capability retention can rank a model…"
    },
    {
      "id": "studies/castform-rl-finetune",
      "url": "https://posttrainllm.com/studies/castform-rl-finetune",
      "md": "https://posttrainllm.com/studies/castform-rl-finetune.md",
      "kind": "study",
      "title": "Castform RL fine-tune platform | PostTrainLLM",
      "description": "Composite rewards, trace-driven data loops, reasoning-depth classification, and explicit environment contracts make reinforcement-style fine-tuning more…"
    },
    {
      "id": "studies/cline-context-hierarchy",
      "url": "https://posttrainllm.com/studies/cline-context-hierarchy",
      "md": "https://posttrainllm.com/studies/cline-context-hierarchy.md",
      "kind": "study",
      "title": "Cline and agent context hierarchy research | PTLLM",
      "description": "Structured-output enforcement and an explicit context hierarchy can reduce ambiguous agent actions and make tool boundaries easier to inspect. The research…"
    },
    {
      "id": "studies/defog-sqlcoder-arctic-text2sql",
      "url": "https://posttrainllm.com/studies/defog-sqlcoder-arctic-text2sql",
      "md": "https://posttrainllm.com/studies/defog-sqlcoder-arctic-text2sql.md",
      "kind": "study",
      "title": "Defog SQLCoder and Arctic Text2SQL class models | PTLLM",
      "description": "Strong SQL systems report execution accuracy on substantial SQL benchmarks rather than relying on exact string match alone. External category scores remain…"
    },
    {
      "id": "studies/gigatoken",
      "url": "https://posttrainllm.com/studies/gigatoken",
      "md": "https://posttrainllm.com/studies/gigatoken.md",
      "kind": "study",
      "title": "Gigatoken | PostTrainLLM",
      "description": "SIMD and cache-heavy bulk BPE can make first-pass tokenization much faster on large corpora, including Qwen tokenizers on Apple Silicon. No current…"
    },
    {
      "id": "studies/halo",
      "url": "https://posttrainllm.com/studies/halo",
      "md": "https://posttrainllm.com/studies/halo.md",
      "kind": "study",
      "title": "Halo / White Circle | PostTrainLLM",
      "description": "HF-native training and portable checkpoints, independent expert/context/tensor/data parallelism, faithful multi-turn trajectories, operation-specific model…"
    },
    {
      "id": "studies/hugging-face-sql-specialists",
      "url": "https://posttrainllm.com/studies/hugging-face-sql-specialists",
      "md": "https://posttrainllm.com/studies/hugging-face-sql-specialists.md",
      "kind": "study",
      "title": "Hugging Face model hub and SQL specialists | PTLLM",
      "description": "Small public SQL models provide realistic baselines and expose how much benchmark, model size, and serving format affect apparently similar claims.…"
    },
    {
      "id": "studies/inside-vllm",
      "url": "https://posttrainllm.com/studies/inside-vllm",
      "md": "https://posttrainllm.com/studies/inside-vllm.md",
      "kind": "study",
      "title": "Inside vLLM | PostTrainLLM",
      "description": "Admission control, scheduling, paged KV allocation, prefill, decode, continuous batching, caching, and distributed execution explain why a serving engine…"
    },
    {
      "id": "studies/needle-2",
      "url": "https://posttrainllm.com/studies/needle-2",
      "md": "https://posttrainllm.com/studies/needle-2.md",
      "kind": "study",
      "title": "Needle 2 | PostTrainLLM",
      "description": "A compact call-only model combines top-five tool retrieval, constrained decoding, confidence escalation, bounded context, quantization, and a small packaged…"
    },
    {
      "id": "studies/parakeet-wgsl",
      "url": "https://posttrainllm.com/studies/parakeet-wgsl",
      "md": "https://posttrainllm.com/studies/parakeet-wgsl.md",
      "kind": "study",
      "title": "parakeet.wgsl | PostTrainLLM",
      "description": "Raw WebGPU plus SIMD-WASM can run Parakeet TDT browser inference with public kernels, a package format, cache behavior, a converter, and a benchmark…"
    },
    {
      "id": "studies/qorl",
      "url": "https://posttrainllm.com/studies/qorl",
      "md": "https://posttrainllm.com/studies/qorl.md",
      "kind": "study",
      "title": "QORL | PostTrainLLM",
      "description": "Parameter-aware query optimization needs equal search budgets, fresh held-out measurement, SQL-equivalence checks, and a native-planner baseline before an…"
    },
    {
      "id": "studies/savante-aryabhata",
      "url": "https://posttrainllm.com/studies/savante-aryabhata",
      "md": "https://posttrainllm.com/studies/savante-aryabhata.md",
      "kind": "study",
      "title": "Savante and Aryabhata | PostTrainLLM",
      "description": "Curated domain data, filtered reasoning traces, supervised fine-tuning, model merging, and verifiable-reward reinforcement learning combine in a JEE…"
    },
    {
      "id": "studies/splash-mac-inference",
      "url": "https://posttrainllm.com/studies/splash-mac-inference",
      "md": "https://posttrainllm.com/studies/splash-mac-inference.md",
      "kind": "study",
      "title": "Splash model-specific Mac inference | PostTrainLLM",
      "description": "Shape-specific Metal kernels, a model-specific speculative draft, packed weights, cache reuse, and a startup memory plan trade generic model support for…"
    },
    {
      "id": "studies/trainloop-ai",
      "url": "https://posttrainllm.com/studies/trainloop-ai",
      "md": "https://posttrainllm.com/studies/trainloop-ai.md",
      "kind": "study",
      "title": "TrainLoop AI | PostTrainLLM",
      "description": "Failed-attempt accounting, slice metrics, trace review, candidate selection, batch-first post-training, policy lag, and LoRA update geometry make…"
    },
    {
      "id": "studies/trainloop-lora-geometry",
      "url": "https://posttrainllm.com/studies/trainloop-lora-geometry",
      "md": "https://posttrainllm.com/studies/trainloop-lora-geometry.md",
      "kind": "study",
      "title": "TrainLoop LoRA geometry writeup | PostTrainLLM",
      "description": "Effective update geometry, layer placement, and controlled rank analysis can explain why two adapters with similar parameter counts behave differently.…"
    },
    {
      "id": "studies/trainloop-mercor-coding-agent",
      "url": "https://posttrainllm.com/studies/trainloop-mercor-coding-agent",
      "md": "https://posttrainllm.com/studies/trainloop-mercor-coding-agent.md",
      "kind": "study",
      "title": "TrainLoop Mercor coding-agent post | PostTrainLLM",
      "description": "File-native and code-native harnesses may fit knowledge-work agents better than bespoke tool APIs because the environment already exposes durable state and…"
    },
    {
      "id": "studies/trainloop-nollamd",
      "url": "https://posttrainllm.com/studies/trainloop-nollamd",
      "md": "https://posttrainllm.com/studies/trainloop-nollamd.md",
      "kind": "study",
      "title": "TrainLoop NollaMD case study | PostTrainLLM",
      "description": "Candidate-selection framing can make a sparse task measurable when unconstrained generation is too difficult or too ambiguous to grade reliably. The framing…"
    },
    {
      "id": "studies/trainloop-oapl",
      "url": "https://posttrainllm.com/studies/trainloop-oapl",
      "md": "https://posttrainllm.com/studies/trainloop-oapl.md",
      "kind": "study",
      "title": "TrainLoop OAPL writeup | PostTrainLLM",
      "description": "Batch rollouts, offline scoring, and compact updates can make a post-training loop easier to inspect, while policy lag can stabilize learning under some…"
    },
    {
      "id": "training-dashboard",
      "url": "https://posttrainllm.com/training-dashboard",
      "md": "https://posttrainllm.com/training-dashboard.md",
      "kind": "application",
      "title": "posttrainllm — training run dashboard",
      "description": "Drop a .jsonl training log to see loss, LR, val, step-rate, and spike markers — overlay multiple runs to compare."
    },
    {
      "id": "webgpu-test",
      "url": "https://posttrainllm.com/webgpu-test",
      "md": "https://posttrainllm.com/webgpu-test.md",
      "kind": "application",
      "title": "posttrainllm — WebGPU kernel tests",
      "description": "Mac-local LLM specialist factory — post-training and runtime that fits on one Mac, plus WebGPU playground."
    }
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      "kind": "feed",
      "url": "https://posttrainllm.com/devlog/rss.xml",
      "description": "Devlog RSS feed"
    },
    {
      "kind": "mac-release-json",
      "url": "https://posttrainllm.com/releases/mac.json",
      "description": "Native Mac release record — verified and downloadable"
    },
    {
      "kind": "report-card-json",
      "url": "https://posttrainllm.com/report-cards/qwen06-sql-routed-v1.json",
      "description": "Validated fine-tune report-card payload"
    },
    {
      "kind": "report-card-json",
      "url": "https://posttrainllm.com/report-cards/qwen3-4b-file-ops-distilled.json",
      "description": "Validated fine-tune report-card payload"
    },
    {
      "kind": "report-card-json",
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      "description": "Validated fine-tune report-card payload"
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    "public": true,
    "notes": "Only public site output is indexed. Local factory runs, models, private artifacts, and unpublished evidence are excluded; decision.json remains the terminal quality and product authority."
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}