Deep dives into agent-first engineering, patterns, and production lessons.
How replacing ad-hoc prompts with structured specs transforms agent reliability from 40% to 95% task completion. A deep dive into the architecture of intent.
Practical patterns for agents that detect, classify, and recover from failures without human intervention.
AI DX is not about better autocomplete. It is about restructuring the entire development loop around agent capabilities.
How we let an agent refactor 140 files across 3 services with zero regressions. The architecture, the guardrails, and the surprises.
Why existing orchestration frameworks fell short and what we built instead. A minimal runtime for maximum control.
A real incident where an agent generated and executed a destructive migration. What went wrong, what we learned.
The paradox of agent management: more configuration options lead to less predictable outcomes. How to design for constraint.
A step-by-step guide to writing agent specs that are precise, testable, and composable.
