Backlog — Sprint Retrospectives¶
Generated by the FAIRE backlog agent (agents/src/frontier_agents/retrospective.py). Each section is one cycle's scrum-style retro: ✓ = auto-applied, ⏳ = queued for next cycle, ○ = deferred to human review. Newest first. Distinct from the per-page Agent Changelog and the human-written Learnings Log.
Cycle — 2026-05-27 08:13 UTC — Retrospective¶
Runs analyzed: 30 · Approved: 23 · Errored: 4 · Avg conf: 0.77 · First-try: 60%
🟢 What went well¶
- Overall approval rate strong: 23/30 runs approved (76.7%), indicating solid content quality and reviewer alignment.
- First-try approval rate of 60% — a healthy proportion of pages met standards without revision overhead.
- Average confidence across the cycle is 0.769, showing generally consistent model certainty in accepted pages.
- Several tracks produce high-confidence pages: 06-reinforcement-learning (0.834) and 09-algorithms-systems-for-ai (0.792) demonstrating strong topic coverage and critic alignment.
- Critics are catching architecture/information issues reliably — critic-info-architecture surfaced the same missing sections consistently, which shows the critic is active and enforcing schema expectations.
🔴 What went wrong¶
- Four runs errored — investigate root causes for pipeline failures to prevent wasted authoring attempts.
- Recurring critic failures around core-concept structure: 'Where this concept appears' and 'Connected topics' are repeatedly missing (critic-info-architecture reported 9–11 occurrences).
- critic-beginner-onramp flagged that prerequisites are present only in frontmatter but not explained in-page (6 occurrences), reducing accessibility for beginners.
- Heading drift observed: '## Mathematical foundations' (3 occurrences) and '## In production' (2 occurrences) — headings are diverging from canonical structure.
- Ten unresolved wikilinks remain referenced across the corpus, creating navigation and discovery gaps.
- Track 08 (causal-statistical-inference) shows weakest cohesion (critic-cohesion avg 0.0) and the lowest avg_confidence (0.6); this is a regression risk for that subject area.
🟡 What needs depth¶
- Several tracks have very small surface area (1–3 pages): 01-ai (1), 08-causal-statistical-inference (1), 03-representation-learning (2), 04-neural-networks-deep-learning (2). These should be expanded to improve coverage and cross-link density.
- critic-info-architecture is the weakest dimension across multiple tracks (notably 03, 04, 09) — pages are frequently missing 'Where this concept appears' and 'Connected topics', indicating shallow contextualization.
- 05-statistical-probabilistic-ml shows a low build-nudge score (0.333) — practical guidance / scaffolding for readers appears underdeveloped.
- Citation coverage: 38 unique arXiv ids across 21 pages — several pages still lack citations; the top-cited arXiv (2604.15469) is heavily reused (8 references) suggesting opportunity to diversify or create an author/anchor page for highly-cited works.
- Multiple system/ops topics in 09 reference the same missing infrastructure stubs (quantization-related, mixed-precision, distributed-training) — these are recurring missing concepts that block cohesive system-level docs.
- Heading drift cluster around 'Mathematical foundations' and 'In production' suggests some pages are misaligned on intended audience/perspective and need rework for consistent sectioning.
➕ What to add (auto-applies marked ✓, others queued for review)¶
- ✓ Create a stub page for 'normalization' in the neural networks track
- evidence: Referenced 3 times by multiple 04-neural-networks-deep-learning pages (residual-connections, optimization)
- refs:
04-neural-networks-deep-learning/residual-connections,04-neural-networks-deep-learning/optimization - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'potential-outcomes' in the causal inference track
- evidence: Referenced twice by 08-causal-statistical-inference pages (instrumental-variables, counterfactuals)
- refs:
08-causal-statistical-inference/instrumental-variables,08-causal-statistical-inference/counterfactuals - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'data-augmentation' in representation learning
- evidence: Referenced twice in 03-representation-learning (simclr, contrastive-learning)
- refs:
03-representation-learning/simclr,03-representation-learning/contrastive-learning - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'transformer-architecture' in neural networks
- evidence: Referenced by both 04-neural-networks-deep-learning/residual-connections and 09-algorithms-systems-for-ai/tensor-parallelism
- refs:
04-neural-networks-deep-learning/residual-connections,09-algorithms-systems-for-ai/tensor-parallelism - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'gradient-descent' in neural networks
- evidence: Referenced twice by 04-neural-networks-deep-learning/optimization
- refs:
04-neural-networks-deep-learning/optimization,04-neural-networks-deep-learning/optimization - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'attention-mechanisms' in systems/algorithms
- evidence: Referenced twice by 09-algorithms-systems-for-ai pages (tensor-parallelism, flash-attention)
- refs:
09-algorithms-systems-for-ai/tensor-parallelism,09-algorithms-systems-for-ai/flash-attention - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'post-training-quantization' in systems/algorithms
- evidence: Referenced twice by 09-algorithms-systems-for-ai/quantization
- refs:
09-algorithms-systems-for-ai/quantization,09-algorithms-systems-for-ai/quantization - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'mixed-precision-training' in systems/algorithms
- evidence: Referenced twice by 09-algorithms-systems-for-ai/quantization
- refs:
09-algorithms-systems-for-ai/quantization,09-algorithms-systems-for-ai/quantization - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'llm-architecture-optimizations' in systems/algorithms
- evidence: Referenced twice by 09-algorithms-systems-for-ai/quantization
- refs:
09-algorithms-systems-for-ai/quantization,09-algorithms-systems-for-ai/quantization - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'distributed-training-arc' in systems/algorithms
- evidence: Referenced twice by 09-algorithms-systems-for-ai/data-parallelism
- refs:
09-algorithms-systems-for-ai/data-parallelism,09-algorithms-systems-for-ai/data-parallelism - risk:
safe· auto_apply:True· type:stub-seed - ⏳ Increase queue priority for review/rewrites in 08-causal-statistical-inference to HIGH
- evidence: Track has lowest avg_confidence (0.6) and critic-cohesion average 0.0, indicating urgent cohesion/content needs
- refs:
08-causal-statistical-inference,critic-cohesion - risk:
safe· auto_apply:True· type:queue-priority-bump
⚙️ Process improvements (human review)¶
- Add a schema-enforced requirement and explicit guidance for core-concept pages to include both 'Where this concept appears' and 'Connected topics' sections; have critic-info-architecture escalate from warnings to blockers if absent for core pages.
- Refine critic-beginner-onramp to check both frontmatter and in-body explicit prerequisite explanations; when prerequisites live only in frontmatter, prompt an in-page 'How to prepare' subsection example.
- Tune critic deduplication: collapse repeated identical messages into single actionable report per page to reduce noise and improve triage efficiency (we observed many near-duplicate critic-info-architecture reports).
- Add a heading-canonicalization check that flags drift from approved section headings (reduce 'Mathematical foundations' / 'In production' divergence) and suggest the canonical headings for the track.
- Introduce a post-run health check that extracts unresolved wikilinks and auto-queues stub-seed actions (already proposed) but include a human-review gate for ambiguous cross-track references.
- Improve error diagnostics and telemetry for the 4 errored runs (capture stack + input snapshot) so pipeline errors are actionable and reproducible for the infra team.
Data appendix — Phase A signals
**Per-track health** | Track | Pages | Avg conf | Weakest critic | |---|---|---|---| | `01-ai` | 1 | 0.74 | `critic-info-architecture` (0.50) | | `03-representation-learning` | 2 | 0.77 | `critic-info-architecture` (0.50) | | `04-neural-networks-deep-learning` | 2 | 0.73 | `critic-info-architecture` (0.60) | | `05-statistical-probabilistic-ml` | 3 | 0.72 | `critic-build-nudge` (0.33) | | `06-reinforcement-learning` | 2 | 0.83 | `critic-info-architecture` (0.68) | | `08-causal-statistical-inference` | 1 | 0.60 | `critic-cohesion` (0.00) | | `09-algorithms-systems-for-ai` | 6 | 0.79 | `critic-info-architecture` (0.65) | **Heading drift (v1 forbidden headings)** - `## Mathematical foundations` × 3 - `## In production` × 2 **Unresolved wikilinks (stub-seed candidates)** - `[[normalization]]` × 3 refs (from 04-neural-networks-deep-learning/residual-connections, 04-neural-networks-deep-learning/optimization, 04-neural-networks-deep-learning/optimization) - `[[potential-outcomes]]` × 2 refs (from 08-causal-statistical-inference/instrumental-variables, 08-causal-statistical-inference/counterfactuals) - `[[data-augmentation]]` × 2 refs (from 03-representation-learning/simclr, 03-representation-learning/contrastive-learning) - `[[transformer-architecture]]` × 2 refs (from 04-neural-networks-deep-learning/residual-connections, 09-algorithms-systems-for-ai/tensor-parallelism) - `[[gradient-descent]]` × 2 refs (from 04-neural-networks-deep-learning/optimization, 04-neural-networks-deep-learning/optimization) - `[[attention-mechanisms]]` × 2 refs (from 09-algorithms-systems-for-ai/tensor-parallelism, 09-algorithms-systems-for-ai/flash-attention) - `[[post-training-quantization]]` × 2 refs (from 09-algorithms-systems-for-ai/quantization, 09-algorithms-systems-for-ai/quantization) - `[[mixed-precision-training]]` × 2 refs (from 09-algorithms-systems-for-ai/quantization, 09-algorithms-systems-for-ai/quantization) - `[[llm-architecture-optimizations]]` × 2 refs (from 09-algorithms-systems-for-ai/quantization, 09-algorithms-systems-for-ai/quantization) - `[[distributed-training-arc]]` × 2 refs (from 09-algorithms-systems-for-ai/data-parallelism, 09-algorithms-systems-for-ai/data-parallelism) **Recurring critic issues (top 5)** - × 11 — critic-info-architecture: The page is a core-concept page but lacks a 'Where this concept appears' section - × 9 — critic-info-architecture: The 'Connected topics' section is missing entirely, failing the requirement for - × 9 — critic-info-architecture: The page is missing a 'Where this concept appears' section, which is required fo - × 9 — critic-info-architecture: The 'Connected topics' section is missing entirely, which is required for core-c - × 6 — critic-beginner-onramp: The prerequisites are listed in the frontmatter, but the page does not explicitlCycle — 2026-05-27 07:28 UTC — Retrospective¶
Runs analyzed: 30 · Approved: 25 · Errored: 4 · Avg conf: 0.77 · First-try: 73%
🟢 What went well¶
- Overall approval rate strong: 25/30 runs approved (~83%).
- First-try approval rate healthy at 73% — many pages land without iteration.
- Average confidence across the cycle is good (0.766), with multiple tracks producing high-confidence pages (05-statistical-probabilistic-ml 0.794, 07-attention-memory-reasoning-continual 0.805, 04-neural-networks-deep-learning 0.781, 02-generative-modeling 0.787).
- Citation pipeline produced substantial coverage: 56 unique arXiv IDs and 22 pages with arXiv references, and clear hotspots (arXiv 2603.01761 appears 6×).
- Critics are catching structural problems (info-architecture and beginner-onramp), demonstrating the validation layer is active and finding consistent gaps to fix.
🔴 What went wrong¶
- Four runs errored (4/30) — investigate causes to reduce run failures.
- Recurring, high-frequency failures from critic-info-architecture: missing 'Where this concept appears' and missing 'Connected topics' sections across many pages (12, 10, 8, 8 counts).
- critic-beginner-onramp flagged pages that list prerequisites only in frontmatter (6 occurrences) — ambiguity between metadata and visible on-page guidance.
- Several unresolved wikilinks point to missing core pages (policy-evaluation, reward-modeling, representation-learning, quantization-aware-training, pipeline-parallelism) and are referenced multiple times, leaving broken navigation.
- Low weakest_critic_avg on a few tracks (03-representation-learning 0.333, 01-ai beginner-onramp 0.25) indicates some pages are missing critical structural/prerequisite content.
🟡 What needs depth¶
- Tracks with very few pages should be expanded: 02-generative-modeling (1 page) and 10-complexity-cognition-natural-intelligence (1 page) need additional topic pages.
- Several mid-sized tracks have shallow coverage and should be expanded: 03-representation-learning (3 pages), 09-algorithms-systems-for-ai (3 pages), 08-causal-statistical-inference (2 pages), 01-ai (2 pages).
- Info-architecture weaknesses are pervasive across tracks — many pages lack connective/contextual sections (Where this concept appears / Connected topics), indicating shallow concept scaffolding.
- Citation coverage gap: 8 of ~30 pages lack arXiv citations; also top-3 arXiv IDs account for a notable share of citations, suggesting some concentration risk and opportunity to diversify sources.
- Pages that reference unresolved wikilinks (for example multiple references to policy-evaluation) show functional gaps that block readers and downstream linking; those topics should be prioritized for content seeding.
➕ What to add (auto-applies marked ✓, others queued for review)¶
- ✓ Create a stub page for 'policy-evaluation' in the causal/statistical inference track to resolve multiple unresolved links.
- evidence: Unresolved wikilinks: 'policy-evaluation' referenced 3× by 08-causal-statistical-inference/do-calculus.
- refs:
policy-evaluation - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'representation-learning' under the representation-learning track to satisfy cross-track references.
- evidence: Unresolved wikilinks: 'representation-learning' referenced by two pages in other tracks.
- refs:
representation-learning - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'quantization-aware-training' in the algorithms/systems track to resolve cross-references and support model compression topics.
- evidence: Unresolved wikilinks: 'quantization-aware-training' referenced by scaling and quantization pages (04 and 09).
- refs:
quantization-aware-training - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'pipeline-parallelism' in the algorithms/systems track to close references from distributed training and model-parallelism pages.
- evidence: Unresolved wikilinks: 'pipeline-parallelism' referenced 2× by 09-algorithms-systems-for-ai pages.
- refs:
pipeline-parallelism - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'reward-modeling' in the AI track to satisfy references from alignment and RLHF pages.
- evidence: Unresolved wikilinks: 'reward-modeling' referenced 2× by 01-ai/alignment-safety and 01-ai/rlhf.
- refs:
reward-modeling - risk:
safe· auto_apply:True· type:stub-seed - ⏳ Bump queue priority for '08-causal-statistical-inference/do-calculus' to high to force a quick fix for broken policy-evaluation links.
- evidence: Do-calculus pages reference 'policy-evaluation' three times; unresolved link is blocking readers.
- refs:
policy-evaluation - risk:
safe· auto_apply:True· type:queue-priority-bump - ○ Propose an arc for 05-statistical-probabilistic-ml to consolidate core probabilistic ML concepts and ensure consistent 'Where this concept appears' and 'Connected topics' sections across pages.
- evidence: Per-track health: 05 has 5 pages and a repeated weakest-critic deficit (critic-info-architecture avg 0.5), indicating need for cohesive connective structure.
- refs:
05-statistical-probabilistic-ml,critic-info-architecture - risk:
moderate· auto_apply:False· type:arc-proposal - ○ Seed an author-page for the author(s) of the most-cited arXiv (2603.01761) to anchor citation discoverability and author-level navigation.
- evidence: Citation health: arXiv 2603.01761 is the most-cited ID (6 occurrences), suggesting an author or work page would improve discoverability.
- refs:
2603.01761 - risk:
moderate· auto_apply:False· type:author-page-seed
⚙️ Process improvements (human review)¶
- Add a schema enforcement rule: core-concept pages must include visible 'Where this concept appears' and 'Connected topics' sections; make this a hard requirement for critic-info-architecture.
- Clarify critic-beginner-onramp rules: if prerequisites are listed only in frontmatter, require an explicit on-page 'Prerequisites' section or an equivalent visible statement to satisfy beginner readers.
- Auto-generate stub-seed tasks from unresolved wikilinks at end of each cycle (configurable trim knob) to reduce navigation breakage and speed repairs.
- Increase severity and provide concrete remediation steps in critic-info-architecture messages (example templates for the missing sections) to reduce back-and-forth edits.
- Add a preflight check that fails the run with an actionable message when unresolved wikilinks are present, and optionally auto-bump priority for pages that reference high-frequency unresolved slugs.
- Deduplicate and normalize critic output strings so recurring complaints are grouped (reduce noise where similar messages differ only in wording).
- Instrument a short failure triage flow for errored runs (capture logs and assign to a small ops queue) to reduce the 4 errored runs per cycle.
Data appendix — Phase A signals
**Per-track health** | Track | Pages | Avg conf | Weakest critic | |---|---|---|---| | `01-ai` | 2 | 0.75 | `critic-beginner-onramp` (0.25) | | `02-generative-modeling` | 1 | 0.79 | `critic-info-architecture` (0.50) | | `03-representation-learning` | 3 | 0.72 | `critic-info-architecture` (0.33) | | `04-neural-networks-deep-learning` | 4 | 0.78 | `critic-info-architecture` (0.50) | | `05-statistical-probabilistic-ml` | 5 | 0.79 | `critic-info-architecture` (0.50) | | `06-reinforcement-learning` | 5 | 0.75 | `critic-info-architecture` (0.50) | | `07-attention-memory-reasoning-continual` | 4 | 0.81 | `critic-info-architecture` (0.59) | | `08-causal-statistical-inference` | 2 | 0.77 | `critic-info-architecture` (0.50) | | `09-algorithms-systems-for-ai` | 3 | 0.71 | `critic-info-architecture` (0.57) | | `10-complexity-cognition-natural-intelligence` | 1 | 0.77 | `critic-info-architecture` (0.50) | **Unresolved wikilinks (stub-seed candidates)** - `[[policy-evaluation]]` × 3 refs (from 08-causal-statistical-inference/do-calculus, 08-causal-statistical-inference/do-calculus, 08-causal-statistical-inference/do-calculus) - `[[representation-learning]]` × 2 refs (from 10-complexity-cognition-natural-intelligence/compositionality, 01-ai/mechanistic-interpretability) - `[[quantization-aware-training]]` × 2 refs (from 04-neural-networks-deep-learning/scaling-laws, 09-algorithms-systems-for-ai/quantization) - `[[pipeline-parallelism]]` × 2 refs (from 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/model-parallelism) - `[[reward-modeling]]` × 2 refs (from 01-ai/alignment-safety, 01-ai/rlhf) **Recurring critic issues (top 5)** - × 12 — critic-info-architecture: The page is missing a 'Where this concept appears' section, which is required fo - × 10 — critic-info-architecture: The 'Connected topics' section is missing entirely, failing the requirement for - × 8 — critic-info-architecture: The page is a core-concept page but lacks a 'Where this concept appears' section - × 8 — critic-info-architecture: The 'Connected topics' section is missing entirely, which is required for core-c - × 6 — critic-beginner-onramp: The prerequisites are listed in the frontmatter, but the page does not explicitlCycle — 2026-05-27 07:04 UTC — Retrospective¶
Runs analyzed: 30 · Approved: 25 · Errored: 4 · Avg conf: 0.76 · First-try: 73%
🟢 What went well¶
- Overall approval rate strong: 25 approved out of 30 runs (83%).
- First-try approval rate solid at 73% — most pages pass initial review without rework.
- Several tracks produced high-confidence pages (07-attention-memory-reasoning-continual avg_confidence=0.805; 02-generative-modeling=0.787; 04-neural-networks-deep-learning=0.781).
- Critics are detecting structural issues consistently (critic-info-architecture and critic-beginner-onramp flagged missing sections), indicating the critic pipeline is functioning and catching common authoring gaps.
- Citation diversity: 63 unique arXiv IDs cited across the cycle showing good breadth of sources.
🔴 What went wrong¶
- Four errored runs (4/30) — investigate causes to avoid repeat failures.
- Recurring failures from critic-info-architecture: many pages missing a required 'Where this concept appears' section and/or a 'Connected topics' section (multiple counts totaling 13/11/8/7).
- critic-beginner-onramp flagged prerequisites missing from page body (6 occurrences) despite frontmatter entries.
- Multiple unresolved wikilinks remain (10 distinct slugs), creating navigation gaps and blocking concept resolution.
- Track-level weak points: 03-representation-learning shows the lowest avg_confidence (0.723) and weakest info-architecture score (0.375), indicating rework needed for structure and clarity.
- Nearly 27% of pages required at least one revision (1 - first_try_approval_rate = 0.27) — indicates room to improve first-pass completeness.
🟡 What needs depth¶
- Tracks with very few pages likely under-covered: 02-generative-modeling (1 page) and 10-complexity-cognition-natural-intelligence (1 page) — consider expanding core concept coverage.
- Track 01-ai has low weakest-critic (critic-beginner-onramp avg 0.25) — onramp / prerequisite material is too shallow or missing from page bodies.
- 03-representation-learning requires depth and structure fixes (avg_confidence=0.723; weakest_critic_avg=0.375) — likely multiple pages need rework to meet info-architecture standards.
- Unresolved high-value wikilinks indicate missing topic pages that are referenced repeatedly (e.g., causal-representation-learning referenced 5x; bayesian-neural-networks and expectation-maximization referenced 3x each) — these are creating cross-track friction.
- Citation surface could be improved on pages without arXiv references: only 22 pages contain arXiv links despite 30 runs — surface canonical citations or author pages for frequently-cited works.
➕ What to add (auto-applies marked ✓, others queued for review)¶
- ✓ Create a stub page for 'causal-representation-learning' under the causal/statistical inference track.
- evidence: Referenced 5 times by multiple pages in 08-causal-statistical-inference (instrumental-variables, mediation-analysis, do-calculus).
- refs:
causal-representation-learning - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'bayesian-neural-networks' in statistical/probabilistic ML.
- evidence: Referenced 3 times by variational-inference pages in 05-statistical-probabilistic-ml.
- refs:
bayesian-neural-networks - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'expectation-maximization' in statistical/probabilistic ML.
- evidence: Referenced 3 times by variational-inference pages in 05-statistical-probabilistic-ml.
- refs:
expectation-maximization - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'tensor-parallelism' in algorithms/systems for AI.
- evidence: Referenced 3 times across distributed-training and model-parallelism pages in 09-algorithms-systems-for-ai.
- refs:
tensor-parallelism - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'data-parallelism' in algorithms/systems for AI.
- evidence: Referenced twice by distributed-training pages in 09-algorithms-systems-for-ai.
- refs:
data-parallelism - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'model-based-reinforcement-learning' in reinforcement learning.
- evidence: Referenced by world-models and actor-critic pages in 06-reinforcement-learning (2 references).
- refs:
model-based-reinforcement-learning - risk:
safe· auto_apply:True· type:stub-seed - ✓ Create a stub page for 'policy-gradients' in reinforcement learning to resolve cross-track links.
- evidence: Referenced twice (06-reinforcement-learning/ppo and 01-ai/rlhf).
- refs:
policy-gradients - risk:
safe· auto_apply:True· type:stub-seed - ⏳ Bump queue priority for 08-causal-statistical-inference/do-calculus to HIGH to resolve multiple unresolved links (policy-evaluation, causal-representation-learning).
- evidence: do-calculus pages reference unresolved concepts repeatedly and are blocking navigation (multiple references in 08-causal-statistical-inference).
- refs:
causal-representation-learning,policy-evaluation,08-causal-statistical-inference/do-calculus - risk:
safe· auto_apply:True· type:queue-priority-bump - ○ Seed an author/works page for arXiv:2603.01761 to anchor repeated citations and improve citation discoverability.
- evidence: arXiv 2603.01761 is the most-cited single ID in this cycle (6 citations).
- refs:
2603.01761 - risk:
moderate· auto_apply:False· type:author-page-seed - ○ Propose an arc for 05-statistical-probabilistic-ml to connect variational inference, Bayesian NN, and EM content into a focused learning arc.
- evidence: 05 has multiple related unresolved topics (bayesian-neural-networks, expectation-maximization) and the track has 4 pages—suitable for an arc proposal.
- refs:
05-statistical-probabilistic-ml,bayesian-neural-networks,expectation-maximization - risk:
moderate· auto_apply:False· type:arc-proposal
⚙️ Process improvements (human review)¶
- Tighten critic-info-architecture guidance: require explicit 'Where this concept appears' and 'Connected topics' for core-concept pages and fail earlier in the pipeline if absent.
- Adjust critic-beginner-onramp checks to require prerequisites be present in the page body (not just frontmatter) and provide template wording snippets for authors.
- Introduce an automated stub-seed creation rule for unresolved wikilinks referenced >=3 times (configurable trim-knob) to reduce cross-track blocking.
- Add a reviewer queue filter for pages with weakest_critic_avg < 0.5 so editors can prioritize structural fixes (start with 03-representation-learning pages).
- Surface top-cited arXiv IDs automatically in the author/citation staging area so maintainers can create author pages or canonical citation shortpages.
- Increase telemetry for errored runs to collect stack/context so we can triage the 4 errored pages (capture error type, stage, and input page slug).
- Refine writer persona prompts to explicitly instruct adding 'Connected topics' and in-body prerequisites for core-concept and onramp pages.
- Consider a queue-priority policy that temporarily elevates pages which reference unresolved high-frequency slugs (e.g., causal-representation-learning) until stubs exist.
Data appendix — Phase A signals
**Per-track health** | Track | Pages | Avg conf | Weakest critic | |---|---|---|---| | `01-ai` | 2 | 0.75 | `critic-beginner-onramp` (0.25) | | `02-generative-modeling` | 1 | 0.79 | `critic-info-architecture` (0.50) | | `03-representation-learning` | 4 | 0.72 | `critic-info-architecture` (0.38) | | `04-neural-networks-deep-learning` | 4 | 0.78 | `critic-info-architecture` (0.50) | | `05-statistical-probabilistic-ml` | 4 | 0.78 | `critic-info-architecture` (0.50) | | `06-reinforcement-learning` | 5 | 0.75 | `critic-info-architecture` (0.50) | | `07-attention-memory-reasoning-continual` | 4 | 0.81 | `critic-info-architecture` (0.59) | | `08-causal-statistical-inference` | 2 | 0.78 | `critic-info-architecture` (0.50) | | `09-algorithms-systems-for-ai` | 3 | 0.71 | `critic-info-architecture` (0.57) | | `10-complexity-cognition-natural-intelligence` | 1 | 0.77 | `critic-info-architecture` (0.50) | **Unresolved wikilinks (stub-seed candidates)** - `[[causal-representation-learning]]` × 5 refs (from 08-causal-statistical-inference/instrumental-variables, 08-causal-statistical-inference/mediation-analysis, 08-causal-statistical-inference/do-calculus) - `[[bayesian-neural-networks]]` × 3 refs (from 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference) - `[[expectation-maximization]]` × 3 refs (from 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference) - `[[policy-evaluation]]` × 3 refs (from 08-causal-statistical-inference/do-calculus, 08-causal-statistical-inference/do-calculus, 08-causal-statistical-inference/do-calculus) - `[[tensor-parallelism]]` × 3 refs (from 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/model-parallelism) - `[[model-based-reinforcement-learning]]` × 2 refs (from 06-reinforcement-learning/world-models, 06-reinforcement-learning/actor-critic) - `[[policy-gradients]]` × 2 refs (from 06-reinforcement-learning/ppo, 01-ai/rlhf) - `[[representation-learning]]` × 2 refs (from 10-complexity-cognition-natural-intelligence/compositionality, 01-ai/mechanistic-interpretability) - `[[quantization-aware-training]]` × 2 refs (from 04-neural-networks-deep-learning/scaling-laws, 09-algorithms-systems-for-ai/quantization) - `[[data-parallelism]]` × 2 refs (from 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/distributed-training) **Recurring critic issues (top 5)** - × 13 — critic-info-architecture: The page is missing a 'Where this concept appears' section, which is required fo - × 11 — critic-info-architecture: The 'Connected topics' section is missing entirely, failing the requirement for - × 8 — critic-info-architecture: The page is a core-concept page but lacks a 'Where this concept appears' section - × 7 — critic-info-architecture: The 'Connected topics' section is missing entirely, which is required for core-c - × 6 — critic-beginner-onramp: The prerequisites are listed in the frontmatter, but the page does not explicitlCycle — 2026-05-27 07:03 UTC — Retrospective¶
Runs analyzed: 30 · Approved: 25 · Errored: 4 · Avg conf: 0.76 · First-try: 73%
🟢 What went well¶
(no observations this cycle)
🔴 What went wrong¶
(none flagged)
🟡 What needs depth¶
(coverage feels adequate)
➕ What to add (auto-applies marked ✓, others queued for review)¶
(no additions proposed)
⚙️ Process improvements (human review)¶
- (LLM proposer failed: LengthFinishReasonError: Could not parse response content as the length limit was reached - CompletionUsage(completion_tokens=4080, prompt_tokens=3284, total_tokens=7364, completion_tok)
Data appendix — Phase A signals
**Per-track health** | Track | Pages | Avg conf | Weakest critic | |---|---|---|---| | `01-ai` | 2 | 0.75 | `critic-beginner-onramp` (0.25) | | `02-generative-modeling` | 1 | 0.79 | `critic-info-architecture` (0.50) | | `03-representation-learning` | 4 | 0.72 | `critic-info-architecture` (0.38) | | `04-neural-networks-deep-learning` | 4 | 0.78 | `critic-info-architecture` (0.50) | | `05-statistical-probabilistic-ml` | 4 | 0.78 | `critic-info-architecture` (0.50) | | `06-reinforcement-learning` | 5 | 0.75 | `critic-info-architecture` (0.50) | | `07-attention-memory-reasoning-continual` | 4 | 0.81 | `critic-info-architecture` (0.59) | | `08-causal-statistical-inference` | 2 | 0.78 | `critic-info-architecture` (0.50) | | `09-algorithms-systems-for-ai` | 3 | 0.71 | `critic-info-architecture` (0.57) | | `10-complexity-cognition-natural-intelligence` | 1 | 0.77 | `critic-info-architecture` (0.50) | **Unresolved wikilinks (stub-seed candidates)** - `[[causal-representation-learning]]` × 5 refs (from 08-causal-statistical-inference/instrumental-variables, 08-causal-statistical-inference/mediation-analysis, 08-causal-statistical-inference/do-calculus) - `[[bayesian-neural-networks]]` × 3 refs (from 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference) - `[[expectation-maximization]]` × 3 refs (from 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference) - `[[policy-evaluation]]` × 3 refs (from 08-causal-statistical-inference/do-calculus, 08-causal-statistical-inference/do-calculus, 08-causal-statistical-inference/do-calculus) - `[[tensor-parallelism]]` × 3 refs (from 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/model-parallelism) - `[[model-based-reinforcement-learning]]` × 2 refs (from 06-reinforcement-learning/world-models, 06-reinforcement-learning/actor-critic) - `[[policy-gradients]]` × 2 refs (from 06-reinforcement-learning/ppo, 01-ai/rlhf) - `[[representation-learning]]` × 2 refs (from 10-complexity-cognition-natural-intelligence/compositionality, 01-ai/mechanistic-interpretability) - `[[quantization-aware-training]]` × 2 refs (from 04-neural-networks-deep-learning/scaling-laws, 09-algorithms-systems-for-ai/quantization) - `[[data-parallelism]]` × 2 refs (from 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/distributed-training) **Recurring critic issues (top 5)** - × 13 — critic-info-architecture: The page is missing a 'Where this concept appears' section, which is required fo - × 11 — critic-info-architecture: The 'Connected topics' section is missing entirely, failing the requirement for - × 8 — critic-info-architecture: The page is a core-concept page but lacks a 'Where this concept appears' section - × 7 — critic-info-architecture: The 'Connected topics' section is missing entirely, which is required for core-c - × 6 — critic-beginner-onramp: The prerequisites are listed in the frontmatter, but the page does not explicitlCycle — 2026-05-27 07:01 UTC — Retrospective¶
Runs analyzed: 30 · Approved: 25 · Errored: 4 · Avg conf: 0.76 · First-try: 73%
🟢 What went well¶
(no observations this cycle)
🔴 What went wrong¶
(none flagged)
🟡 What needs depth¶
(coverage feels adequate)
➕ What to add (auto-applies marked ✓, others queued for review)¶
(no additions proposed)
⚙️ Process improvements (human review)¶
(no process changes proposed)
Data appendix — Phase A signals
**Per-track health** | Track | Pages | Avg conf | Weakest critic | |---|---|---|---| | `01-ai` | 2 | 0.75 | `critic-beginner-onramp` (0.25) | | `02-generative-modeling` | 1 | 0.79 | `critic-info-architecture` (0.50) | | `03-representation-learning` | 4 | 0.72 | `critic-info-architecture` (0.38) | | `04-neural-networks-deep-learning` | 4 | 0.78 | `critic-info-architecture` (0.50) | | `05-statistical-probabilistic-ml` | 4 | 0.78 | `critic-info-architecture` (0.50) | | `06-reinforcement-learning` | 5 | 0.75 | `critic-info-architecture` (0.50) | | `07-attention-memory-reasoning-continual` | 4 | 0.81 | `critic-info-architecture` (0.59) | | `08-causal-statistical-inference` | 2 | 0.78 | `critic-info-architecture` (0.50) | | `09-algorithms-systems-for-ai` | 3 | 0.71 | `critic-info-architecture` (0.57) | | `10-complexity-cognition-natural-intelligence` | 1 | 0.77 | `critic-info-architecture` (0.50) | **Unresolved wikilinks (stub-seed candidates)** - `[[causal-representation-learning]]` × 5 refs (from 08-causal-statistical-inference/instrumental-variables, 08-causal-statistical-inference/mediation-analysis, 08-causal-statistical-inference/do-calculus) - `[[bayesian-neural-networks]]` × 3 refs (from 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference) - `[[expectation-maximization]]` × 3 refs (from 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference, 05-statistical-probabilistic-ml/variational-inference) - `[[policy-evaluation]]` × 3 refs (from 08-causal-statistical-inference/do-calculus, 08-causal-statistical-inference/do-calculus, 08-causal-statistical-inference/do-calculus) - `[[tensor-parallelism]]` × 3 refs (from 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/model-parallelism) - `[[model-based-reinforcement-learning]]` × 2 refs (from 06-reinforcement-learning/world-models, 06-reinforcement-learning/actor-critic) - `[[policy-gradients]]` × 2 refs (from 06-reinforcement-learning/ppo, 01-ai/rlhf) - `[[representation-learning]]` × 2 refs (from 10-complexity-cognition-natural-intelligence/compositionality, 01-ai/mechanistic-interpretability) - `[[quantization-aware-training]]` × 2 refs (from 04-neural-networks-deep-learning/scaling-laws, 09-algorithms-systems-for-ai/quantization) - `[[data-parallelism]]` × 2 refs (from 09-algorithms-systems-for-ai/distributed-training, 09-algorithms-systems-for-ai/distributed-training) **Recurring critic issues (top 5)** - × 13 — critic-info-architecture: The page is missing a 'Where this concept appears' section, which is required fo - × 11 — critic-info-architecture: The 'Connected topics' section is missing entirely, failing the requirement for - × 8 — critic-info-architecture: The page is a core-concept page but lacks a 'Where this concept appears' section - × 7 — critic-info-architecture: The 'Connected topics' section is missing entirely, which is required for core-c - × 6 — critic-beginner-onramp: The prerequisites are listed in the frontmatter, but the page does not explicitlCycle — 2026-05-27 07:00 UTC — Retrospective¶
Runs analyzed: 30 · Approved: 25 · Errored: 4 · Avg conf: 0.76 · First-try: 73%
🟢 What went well¶
(no observations this cycle)
🔴 What went wrong¶
(none flagged)
🟡 What needs depth¶
(coverage feels adequate)
➕ What to add (auto-applies marked ✓, others queued for review)¶
(no additions proposed)
⚙️ Process improvements (human review)¶
- (Phase B failed: KeyError('ANTHROPIC_API_KEY')) — check OPENAI_API_BASE + key