AI coding tools have gotten very good at one thing: generating code fast. What they haven't gotten good at is discipline.
They don't know your architecture. They don't remember that you rejected a pattern last sprint. They don't know which parts of your context window are signal and which are noise. And they have no concept of a development workflow — no phases, no review gates, no verification steps. You describe what you want, they generate, and you hope the output fits.
For small tasks this works fine. For anything that touches your real codebase at scale — refactors, new features with cross-cutting concerns, compliance-sensitive changes — the lack of workflow structure creates subtle, expensive problems that compound over time.
We've been building
We're looking for 5 engineering teams to run Ortho on a real internal repo for 30 days and give honest feedback. If you're shipping AI-generated code and hitting architecture or workflow problems, I'd love to hear about it. Email: [email protected]
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