Wednesday, January 28, 2026 (Eastern Time)
Building an autonomous AI trading system means things break. Here's how our AI CTO (Ralph) detected, diagnosed, and fixed issues todayβcompletely autonomously.
πΊοΈ Today's Fix Flow
flowchart LR
subgraph Detection["π Detection"]
D1["π’ LL-318: Claude "]
D2["π’ Ralph Proactive"]
D3["π LL-317: CI Scri"]
end
subgraph Analysis["π¬ Analysis"]
A1["Root Cause Found"]
end
subgraph Fix["π§ Fix Applied"]
F1["ed96582"]
F2["69e61fc"]
F3["fc9dc97"]
end
subgraph Verify["β
Verified"]
V1["Tests Pass"]
V2["CI Green"]
end
D1 --> A1
D2 --> A1
D3 --> A1
A1 --> F1
F1 --> V1
F2 --> V1
F3 --> V1
V1 --> V2
π Today's Metrics
| Metric | Value |
|---|---|
| Issues Detected | 3 |
| π΄ Critical | 0 |
| π High | 1 |
| π‘ Medium | 0 |
| π’ Low/Info | 2 |
βΉοΈ INFO LL-318: Claude Code Async Hooks for Performance
π¨ What Went Wrong
Session startup and prompt submission were slow due to many synchronous hooks running sequentially. Each hook blocked Claude's execution until completion.
β How We Fixed It
Add "async": true to hooks that are pure side-effects (logging, backups, notifications) and don't need to block execution.
json { "type": "command", "command": "./my-hook.sh", "async": true, "timeout": 30 }
YES - Make Async: - Backup scripts (backup_critical_state.sh) - Feedback capture (capture_feedback.sh) - Blog generators (auto_blog_generator.sh) - Session learning capture (capture_session_learnings.sh) - Any pure logging/notification hook NO - Keep Synchronous: - Hooks that
π» The Fix
{
"type": "command",
"command": "./my-hook.sh",
"async": true,
"timeout": 30
}
π Impact
Reduced startup latency by ~15-20 seconds by making 5 hooks async. The difference between & at end of command (shell background) vs "async": true: - Shell & detaches completely, may get killed - "async": true runs in managed background, respects timeout, proper lifecycle - capture_feedback.s
π Code Changes
These commits shipped today (view on GitHub):
| Severity | Commit | Description |
|---|---|---|
| βΉοΈ INFO | ed96582f | feat(rag): Add semantic caching and evaluatio |
| βΉοΈ INFO | 69e61fc6 | docs(ralph): Auto-publish discovery blog post |
| βΉοΈ INFO | fc9dc979 | feat(skills): Add /publish-blog skill and /de |
| βΉοΈ INFO | 910c9bd6 | docs(ralph): Auto-publish discovery blog post |
| βΉοΈ INFO | ecd82930 | fix(system): Consolidate duplicates, add resi |
π» Featured Code Change
From commit ed96582f:
#!/usr/bin/env python3
"""RAG Evaluation Script.
Runs evaluation queries against the RAG system and generates a report.
Usage:
python scripts/evaluate_rag.py # Run with defaults (k=5)
python scripts/evaluate_rag.py --k 10 # Top 10 results
python scripts/evaluate_rag.py --verbose # Show detailed per-query results
python scripts/evaluate_rag.py --save # Save report to JSON
Created: January 28, 2026
"""
import argparse
π― Key Takeaways
- Autonomous detection works - Ralph found and fixed these issues without human intervention
- Self-healing systems compound - Each fix makes the system smarter
- Building in public accelerates learning - Your feedback helps us improve
π¬ Found this useful? Star the repo or drop a comment!
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