stemedb/applications/aphoria/dogfood/cachewrap/eval/progress-log-2026-02-11.md

Team Progress Log - cachewrap Dogfood Exercise

Timestamp: 2026-02-11 Phase: Days 1-5 Complete Documentation Followed: cachewrap/plan.md, cachewrap/README.md

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Day 1: Claims Extraction (2026-02-11 03:45-03:56)

Team Thoughts (from DAY1-SUMMARY.md)

Duration: 11 minutes 17 seconds (0.19 hours)

What they did:

• Used /aphoria-suggest skill to discover reusable patterns from httpclient, dbpool, msgqueue corpora
• Created 20 claims total: 7 reused (35%), 13 new (65%)
• Pattern discovery via semantic matching (not string matching)
• Validated cross-domain transfer (HTTP timeout → cache timeout)

Evidence of skill usage:

• .aphoria/claims.toml shows created_by = "aphoria-suggest" for all 20 claims ✅
• DAY1-SUMMARY.md mentions "Pattern Discovery via LLM" section
• Time per claim: 18.2 seconds average (suggests automated workflow)

Questions Raised:

• None documented - workflow appeared smooth

Decisions Made:

• Reuse 7 patterns from existing corpora (timeout, TLS, retry, async, connections, lifecycle, metrics)
• Create 13 new cache-specific patterns (TTL, eviction, key validation, max_size, etc.)
• Use "expert" tier for critical safety/security claims, "community" for recommendations

Next Steps Stated:

• Day 2: Implement cache library with 10 intentional violations
• Embed inline markers during implementation (not retrofit)

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Day 2: Implementation (2026-02-11 04:01-04:11)

Team Thoughts (from DAY2-SUMMARY.md)

Duration: 10 minutes 26 seconds (0.17 hours)

What they did:

• Created Rust cache wrapper library with redis, tokio, serde dependencies
• Embedded 10 violations across config.rs and client.rs
• Added inline @aphoria:claim markers for each violation
• Wrote 16 tests (3 unit + 13 integration, 9 passing without Redis)
• Documented all violations in lib.rs with cross-cutting categories

Violations embedded:

1. Key injection (no validation)
2. TLS disabled (verify_tls: false)
3. Hardcoded password ("secret123")
4. Missing TTL (SET without EX/PX)
5. Unbounded size (max_size: None)
6. Sync blocking (get_connection() in async)
7. No eviction policy
8. Zero timeout
9. No connection pooling
10. Metrics disabled

Questions Raised:

• Should tests exercise violations or prevent them? (Decided: exercise, detection comes from scan)

Decisions Made:

• Simple scope (wrapper, not production library) for speed
• Violations embedded during implementation (not retrofitted)
• Tests validate code works despite violations (violations are config issues)

Next Steps Stated:

• Day 3: Run scan, expect low baseline detection, create extractors

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Day 3: Scanning & Extractor Creation (2026-02-11 04:20-04:30)

Team Thoughts (from DAY3-SUMMARY.md)

Duration: 9 minutes 17 seconds (0.15 hours)

What they did:

• Iteration 1 (FAILED): Created 10 separate .toml files in .aphoria/extractors/ directory

  • Assumption: Aphoria loads extractors from separate files
  • Result: Extractors not loaded
  • Learning: Declarative extractors must be in .aphoria/config.toml

• Iteration 2 (PARTIAL): Added extractors to config.toml with concept path mismatch

  • Extractor: claim.subject = "timeout" → observation tail config/timeout
  • Claim: concept_path = "cache/timeout"
  • Result: 0% detection (tail paths don't align)
  • Learning: Subject must include full prefix

• Iteration 3 (SUCCESS): Fixed concept path alignment

  • Changed all subjects to include cache/ prefix
  • Result: 50% detection (5/10 violations)
  • 10 declarative extractors in config.toml

Violations detected (5):

1. cache-timeout-001 (zero timeout)
2. cache-ttl-required-001 (missing TTL)
3. cache-key-validation-001 (no validation)
4. cache-max-size-001 (unbounded size)
5. cache-eviction-policy-001 (no eviction)

Violations missed (5):

1. cache-tls-validation-001 (TLS disabled) - pattern matches declaration, not Default impl
2. cache-async-blocking-001 (sync blocking) - pattern escaping issue
3. cache-max-connections-001 (no pooling) - long pattern regex issue
4. cache-metrics-enabled-001 (metrics disabled) - similar to TLS issue
5. cache-hardcoded-password-001 (hardcoded password) - pattern too specific

Questions Raised:

• Why 50% instead of ≥90%? (Analyzed: declarative extractor limitations)
• Should we refine extractors or move to Day 4? (Decided: move on, validate mechanism)

Decisions Made:

• 50% detection validates flywheel (0% → 50% proves knowledge compounding)
• Declarative extractors have known limitations (function bodies, context)
• Programmatic extractors needed for 90%+ (not blocking for Day 3)

Next Steps Stated:

• Day 4: Fix all 10 violations progressively, verify with scans
• Don't refine extractors (that's Day 5 activity)

Observer Notes:

• No evidence of /aphoria-custom-extractor-creator skill usage ⚠️
• Team manually edited .aphoria/config.toml (3 iterations)
• Fast iteration (1 min per iteration) suggests clear feedback
• Pattern: Discovered extractor configuration through trial and error

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Day 4: Remediation (2026-02-11 continuation)

Team Thoughts (from DAY4-SUMMARY.md)

Duration: 25 minutes (0.42 hours)

What they did:

• Fixed all 10 violations in 4 rounds (Security → Performance → Correctness → Observability)
• Updated tests to reflect fixes
• Final scan: 1 conflict remaining (false negative due to extractor limitation)

Rounds:

1. Security (3 fixes): Key validation function, TLS default true, env password
2. Performance (3 fixes): Default TTL, max_size 1GB, removed blocking_get()
3. Correctness (3 fixes): LRU eviction, 5s timeout, ConnectionManager pooling
4. Observability (1 fix): Metrics enabled

Conflict rate improvement: 5 → 1 (-80%)

Questions Raised:

• Why does cache-key-validation-001 still conflict? (Analyzed: extractor checks signature, not body)

Decisions Made:

• Code is correct despite false negative (validation function exists)
• Extractor limitation, not code issue
• Refinement for Day 5

Next Steps Stated:

• Day 5: Documentation, retrospective, extractor refinement

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Day 5: Documentation (2026-02-11 continuation)

Team Thoughts (from DAY5-SUMMARY.md)

Duration: 571 lines comprehensive retrospective

What they did:

• Comprehensive metrics analysis
• Hypothesis validation (multi-domain flywheel works)
• 50% detection caveat documented
• Enterprise pitch materials prepared

Key insights:

• Total time: 1.4 hours (91% faster than target)
• Pattern reuse: 35% (exact match to hypothesis)
• Detection: 50% (below 90% but validates mechanism)
• All violations fixed, production-ready

Lessons learned:

1. Concept path alignment is critical
2. Declarative extractors work for simple patterns only
3. 50% is enough to validate flywheel (improvement, not perfection)
4. Progressive fixing by severity reduces risk

Next Steps Stated:

• Share with team for dbpool comparison
• Use learnings for next dogfood exercise

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Summary

Total Duration: 1.4 hours (Days 1-4), ~2 hours (Days 1-5)

Workflow Used:

• ✅ Day 1: /aphoria-suggest skill (autonomous)
• ❌ Day 3: Manual config.toml editing (3 iterations)
• ℹ️ Pattern: Partial LLM usage, not continuous

Success Metrics:

• Pattern reuse: 35% ✅
• Time savings: 91% ✅
• Detection rate: 50% ⚠️ (below 90% target)
• Violations fixed: 100% ✅

Critical Observation: Team used LLM skills for claim discovery but manual workflow for extractor creation, indicating documentation didn't emphasize continuous LLM requirement across all phases.