#artificial-intelligence
Practical guides to Claude Skills and using AI to investigate production issues by connecting application code, monitoring data and query plans.
15 posts tagged with #artificial-intelligence
2026
- How to Build an MCP Server: Python, Remote and Ready for Production8 min read
- I Tried 28 Claude Code Skills. Here Are the 5 I Kept8 min read
- Claude MCP: What It Is and How to Add a Server7 min read
- Jev AI vs Logprobs vs Structured Output: We Tested TypeSafe's System One Model on Our Support Queue9 min read
- My Claude Code chief of staff: one VM, eight specialists and one Telegram chat8 min read
- Claude Code Review in Production: How Our Review Rules Evolved Over Five Months8 min read
- MCP vs API: When to Build an MCP Server, and When the API Is Enough14 min read
- If leaders want AI speed, they must share the production risk6 min read
- A 90% agent PR merge rate can still describe a weak engineering workflow6 min read
- AI in Software Testing: Why Generated Tests Miss Bugs5 min read
- Your customer support AI is probably going to fail in production!7 min read
- Loop Engineering in Practice: Six Feedback Loops for AI Coding Agents7 min read
- Using AI to Investigate a Slow Query: Why Django icontains Skipped Our pg_trgm Index6 min read