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Author	SHA1	Message	Date
nyash-codex	d7805e5974	feat(joinir): Phase 213-2 Step 2-2 & 2-3 Data structure extensions Extended PatternPipelineContext and CarrierUpdateInfo for Pattern 3 AST-based generalization. Changes: 1. PatternPipelineContext: - Added loop_condition: Option<ASTNode> - Added loop_body: Option<Vec<ASTNode>> - Added loop_update_summary: Option<LoopUpdateSummary> - Updated build_pattern_context() for Pattern 3 2. CarrierUpdateInfo: - Added then_expr: Option<ASTNode> - Added else_expr: Option<ASTNode> - Updated analyze_loop_updates() with None defaults Status: Phase 213-2 Steps 2-2 & 2-3 complete Next: Create Pattern3IfAnalyzer to extract if statement and populate update summary	2025-12-10 00:01:53 +09:00
nyash-codex	77d4fd72b3	phase: 20.49 COMPLETE; 20.50 Flow+String minimal reps; 20.51 selfhost v0/v1 minimal (Option A/B); hv1-inline binop/unop/copy; docs + run_all + CURRENT_TASK -> 21.0	2025-11-06 15:41:52 +09:00
Selfhosting Dev	63c8fda808	🔍 Research: GPT-5-Codex capabilities and GitHub PR integration ## Summary Investigated OpenAI's new GPT-5-Codex model and Codex GitHub PR review integration capabilities. ## GPT-5-Codex Analysis ### Benchmark Performance (Good) - SWE-bench Verified: 74.5% (vs GPT-5's 72.8%) - Refactoring tasks: 51.3% (vs GPT-5's 33.9%) - Code review: Higher developer ratings ### Real-World Issues (Concerning) - Users report degraded coding performance - Scripts that previously worked now fail - Less consistent than GPT-4.5 - Longer response times (minutes vs instant) - "Creatively and emotionally flat" - Basic errors (e.g., counting letters incorrectly) ### Key Finding Classic case of "optimizing for benchmarks vs real usability" - scores well on tests but performs poorly in practice. ## Codex GitHub PR Integration ### Setup Process 1. Enable MFA and connect GitHub account 2. Authorize Codex GitHub app for repos 3. Enable "Code review" in repository settings ### Usage Methods - Manual: Comment '@codex review' in PR - Automatic: Triggers when PR moves from draft to ready ### Current Limitations - One-way communication (doesn't respond to review comments) - Prefers creating new PRs over updating existing ones - Better for single-pass reviews than iterative feedback ## 'codex resume' Feature New session management capability: - Resume previous codex exec sessions - Useful for continuing long tasks across days - Maintains context from interrupted work 🐱 The investigation reveals that while GPT-5-Codex shows benchmark improvements, practical developer experience has declined - a reminder that metrics don't always reflect real-world utility\!	2025-09-16 16:28:25 +09:00

Author

SHA1

Message

Date

nyash-codex

d7805e5974

feat(joinir): Phase 213-2 Step 2-2 & 2-3 Data structure extensions

Extended PatternPipelineContext and CarrierUpdateInfo for Pattern 3 AST-based generalization.

Changes:
1. PatternPipelineContext:
   - Added loop_condition: Option<ASTNode>
   - Added loop_body: Option<Vec<ASTNode>>
   - Added loop_update_summary: Option<LoopUpdateSummary>
   - Updated build_pattern_context() for Pattern 3

2. CarrierUpdateInfo:
   - Added then_expr: Option<ASTNode>
   - Added else_expr: Option<ASTNode>
   - Updated analyze_loop_updates() with None defaults

Status: Phase 213-2 Steps 2-2 & 2-3 complete
Next: Create Pattern3IfAnalyzer to extract if statement and populate update summary

2025-12-10 00:01:53 +09:00

nyash-codex

77d4fd72b3

phase: 20.49 COMPLETE; 20.50 Flow+String minimal reps; 20.51 selfhost v0/v1 minimal (Option A/B); hv1-inline binop/unop/copy; docs + run_all + CURRENT_TASK -> 21.0

2025-11-06 15:41:52 +09:00

Selfhosting Dev

63c8fda808

🔍 Research: GPT-5-Codex capabilities and GitHub PR integration

## Summary
Investigated OpenAI's new GPT-5-Codex model and Codex GitHub PR review integration capabilities.

## GPT-5-Codex Analysis

### Benchmark Performance (Good)
- SWE-bench Verified: 74.5% (vs GPT-5's 72.8%)
- Refactoring tasks: 51.3% (vs GPT-5's 33.9%)
- Code review: Higher developer ratings

### Real-World Issues (Concerning)
- Users report degraded coding performance
- Scripts that previously worked now fail
- Less consistent than GPT-4.5
- Longer response times (minutes vs instant)
- "Creatively and emotionally flat"
- Basic errors (e.g., counting letters incorrectly)

### Key Finding
Classic case of "optimizing for benchmarks vs real usability" - scores well on tests but performs poorly in practice.

## Codex GitHub PR Integration

### Setup Process
1. Enable MFA and connect GitHub account
2. Authorize Codex GitHub app for repos
3. Enable "Code review" in repository settings

### Usage Methods
- **Manual**: Comment '@codex review' in PR
- **Automatic**: Triggers when PR moves from draft to ready

### Current Limitations
- One-way communication (doesn't respond to review comments)
- Prefers creating new PRs over updating existing ones
- Better for single-pass reviews than iterative feedback

## 'codex resume' Feature
New session management capability:
- Resume previous codex exec sessions
- Useful for continuing long tasks across days
- Maintains context from interrupted work

🐱 The investigation reveals that while GPT-5-Codex shows benchmark improvements, practical developer experience has declined - a reminder that metrics don't always reflect real-world utility\!

2025-09-16 16:28:25 +09:00

3 Commits