How teams use agents to iterate, review, and ship PRs with proof.
Showing 12 of 122 posts
Why coding benchmarks miss the failure modes that matter in agentic systems, and how to build orchestration evals that measure task handoffs, feedback loops, and recovery behavior.
Why feedback loops, not model selection, determine success in agentic coding systems - and how the close-the-loop principle transforms AI-assisted development.
Why averaging UX for different user types fails, and how shipping two experiences with a shared core serves both vibe coders and tinkerers effectively.
Learn why AI coding assistants default to popular frameworks and how providing concrete code examples in your context window steers output toward your actual stack.
Vibe coding delivers speed but creates blind spots around security. Learn why new builders accidentally expose API keys and how guardrails can catch mistakes before they become incidents.
Discover why XML tag-based tool definitions may outperform native function calling for AI agents, with practical guidance on when to swap formats for better reliability.
AI memory features create hidden switching costs that undermine multi-model strategies. Learn how to evaluate memory as infrastructure and why portable memory matters for engineering teams.
How OpenRouter's team audited error shapes, message IDs, and tokenization patterns to ship an unreleased OpenAI model without fingerprinting the provider.
Rate limit errors on experimental AI models like Gemini 2.5 Pro aren't billing issues - they're supply problems. Learn why adding credits won't help and how to build fallback routing strategies.
The model exists but the endpoint doesn't. Learn why announced context windows don't match API reality and how cluster economics block long-context inference.
Learn why local AI models excel at scoped code edits but fail at greenfield generation, and how to build a hybrid workflow that balances privacy requirements with agentic coding capability.
Stale code comments confuse AI coding agents by providing contradictory context. Learn how to audit comment freshness and practice context hygiene for better agent output.
Cloud Agents review code, catch issues, and suggest fixes before you open the diff. You review the results, not the process.
