Insights
Practical perspectives on software, AI, and automation from the team at Automathing.
RAG isn't a universal solution, it's a precision tool. How to decide if your project needs it, how it actually works, and how to avoid the mistakes that break it.
An AI agent doesn't crash: it hallucinates, loops, picks the wrong tool, and still returns 200 OK. How we built observability for our agents' reasoning.
Full autonomy is a risk on critical actions. How to add human-in-the-loop checkpoints to your AI agent workflows, with a real example from TowerZ.
How we built a multi-agent architecture at Automathing: one orchestrator per project, specialized AI agents, and rules written from real errors.
A pragmatic guide to architectural decisions that let small teams move fast without building technical debt they'll regret.
