Articles
Practical breakdowns of engineering systems: autonomous AI teams, QA workflows, releases, infrastructure, and the constraints without which automation quickly turns into a convincing illusion.
Agentic SDD: Forcing AI Agents to Write Code by Strict Contract
In Findrates.ai, Agentic SDD (autonomous spec-driven development) runs every day: we have closed over 240 plans through this pipeline. Our actual process differs significantly from conference slides where classical SDD is presented as an effortless silver bullet.
The Limits of Vibecoding
With the rise of LLMs, developers initially relied on “vibecoding”—prompting a chatbot to “build feature X.” For quick scripts and prototypes, this was enough. On an existing codebase, however, vibecoding quickly caused loss of context: models forgot constraints between sessions, broke neighboring modules, and generated unmanaged technical debt.
Read →18 Days Without a Single Task From Me
An owner’s report after 18 days: how an autonomous employee runs on schedule, closes its own hypotheses, catches its own mistakes, and stops where the decision belongs to a human.
Read →How I Built a Concierge for Claude Code and Codex
A practical breakdown of a personal AI concierge for Claude Code and Codex: how it understands incoming requests, resumes the right sessions, tracks assignments, and returns results.
Read →How I Built an Autonomous Digital Employee
A practical breakdown of an autonomous digital employee: schedule, authority, memory, engineering intuition, a research pipeline, and risk boundaries.
Read →How I Built a Workflow for Autonomous AI Engineering Teams
A practical breakdown of a system of autonomous AI engineering teams: roles, task queue, QA, audit, retrospectives, and the release loop.
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