Have any of these no-bs articles described how they handle schema changes? Are they even using a “real” DB or is it all local, single user sqllite? Because I can see a disaster looming letting a vibe coder’s agent loose on a database.
And does it require auth? How is that spec’d out and validated? What about RBAC or anything? How would you even get the LLM to constantly follow rules for that?
Don’t get me wrong these tools are pretty cool but the old adage “if it sounds too good to be true, it probably is” always applies.
Senior engineers know process, including for what you described, and that maps to plan-driven AI engineering well:
1. Note the discussion of plan-driven development in the claude code sections (think: plan = granular task list, including goals & validation criteria, that the agent loops over and self-modifies). Plans are typically AI generated: I ask it to do initial steps of researching current patterns for x+y+z and include those in the steps and validations, and even have it re-audit a plan. Codex internally works the same, and multiple people are reporting it automates more of this plan flow.
2. Working with database for tasks like migrations is normal and even better. My two UIs are now the agent CLI (basically streaming AI chat for task list monitoring & editing) and GitHub PR viewer: if it wasn't smart enough to add and test migrations and you didn't put that into the plan, you see it in the PR review and tell it to fix that. Writing migrations is easy, but testing them is annoying, and I've found AI helping write mocks, integration tests, etc to be wonderful.
And does it require auth? How is that spec’d out and validated? What about RBAC or anything? How would you even get the LLM to constantly follow rules for that?
Don’t get me wrong these tools are pretty cool but the old adage “if it sounds too good to be true, it probably is” always applies.