Blog Archive

Most builders assume end-of-turn detection is a silence threshold. That model breaks in production. The fix is architectural: four probabilistic events, speculative reasoning, and everything downstream cancellable.

An 8th specialist that touches the browser — navigating, clicking, and typing to find bugs that scripted journeys miss. How exploratory testing with Playwright catches what verification alone cannot.

Seven specialists, each with their own checklist — QA, UX, UI, Security, Performance, Data Leakage, Language. How splitting evaluation into focused agents catches more.

The leap from AI-assisted coding to autonomous batch processing. Fresh context per task, filesystem locks, model routing, and orchestration that runs while you sleep.

Exponential backoff, dual timeouts, SSE heartbeats, idempotency caches — the unglamorous patterns that keep LLM-powered systems running at 3am.

Real browser, predefined journeys, specialist agents checking every step. How QA findings feed back into the issue tracker to close the development loop.

The AI picks up a planned issue, implements it, tests it, commits, and marks it done. How headless batch mode lets me plan in the afternoon and wake up with code in the morning.

Users ask similar questions in different words. Semantic caching with pgvector turns repeated intent into instant answers — no LLM call, no embedding, no retrieval pipeline.