Thinking on agent orchestration — harnesses, review gates, evals, and what it takes to ship serious software with AI agents.
Your coding-agent pilot stalled — impressive branches, a broken main. The agents were fine. Here is where AI agents fail, and the engineering that was missing.
The four vibe coding problems that stall every AI-built codebase — untestable code, no type safety, hidden coupling, zero documentation — and the engineering playbook that fixes each one without starting over.
What an agent orchestration engagement actually looks like, phase by phase: the audit, the harness build, the first gated merges — and the hours it costs your team.
What AI agent orchestration actually is: the specs, harnesses, review gates, CI, and evals that turn coding agents into a reliable software delivery system — plus the benefits, the caveats, and when you don't need it.
Agent orchestration systems like Paperclip and Claude Code are astonishing in the first hours — then real work hits the reliability wall. Here's the engineering that turns agent magic into a machine that ships, and what your job looks like once it exists.
One AI-native engineer vs three full-time hires: the real math on a composite seed-stage engagement — what it cost, what shipped in 9 weeks, what almost broke, and when you should hire three people instead.
How to interview an AI engineer: a 90-minute structure — postmortem interrogation, a rigged AI-written code review, and one constraint question — that separates senior AI-native engineers from vibe-coders.
A design engineer is the person who turns design into working, production-grade product — not a prettier Figma file. Here's why the role exists, why the Figma-as-source-of-truth handoff is now the bottleneck, and why early-stage founders should care.
Two years into the AI-native engineering shift, the question isn't how many engineers you need — it's when they formed their intuition about what production software actually requires. A founder's perspective on the distinction that matters.
A 4-layer code review stack — automated gates, AI review, CI guardrails, and focused human review — that lets 2-person engineering teams ship clean code without slowing down or hiring a staff engineer.
A week-by-week playbook for shipping a real, production-ready MVP in six weeks with two AI-native senior engineers — what gets built, what gets cut, and where the leverage actually comes from.
Spec-Driven Development is having a moment, but the discipline isn't new — BDD asked for the same rigor fifteen years ago. What changed is the economics. Here's what that means for the engineers you hire.
The conventional math says AI means smaller teams and lower burn. Here's why that logic fails — and what the right model actually looks like for early-stage startups.
There's a fear circulating in founder circles right now. You've heard about vibe-coding. Here's what actually separates an AI-native engineer from a vibe-coder — and why the distinction matters.