AI Integration and Vibe Coding Rescue
Production grade AI features, vector search, LLM cost control, and rescue work on AI generated codebases.
The Prompt as a Spec: How to Build Software With AI Tools Responsibly
Using a prompt as a spec means writing the context, constraints, and expected behavior into the prompt the same way you would write a technical specification. The model then generates code against a defined target rather than guessing intent from a few words. Teams that do this get reproducible, reviewable output. Teams that skip it get code that works once and breaks under any variation. The discipline is cheap. The alternative is not.
AI Integration and Vibe Coding RescueThe Founder Who Vibe Coded Their MVP: A Postmortem and Rescue Plan
Vibe coding (building software by prompting AI assistants without understanding the code they generate) has made it possible for non-engineers to ship working MVPs. It has also created a category of codebase that looks like it works and has serious structural problems invisible to the founder who built it. The rescue pattern is: audit the security and data model, stabilize what works, replace what is fragile, and implement the engineering process that was skipped in the original build.
AI Integration and Vibe Coding RescueWhen AI Code Generation Stops Saving You Time and Starts Costing You
AI code generation saves time on the parts of programming that are repetitive and clearly specified. It costs time on the parts that require judgment, context, and understanding of the system as a whole. The crossover point depends on the complexity of the codebase and the discipline of the engineer using the tool. I have watched both sides of this and the warning signs are consistent.
AI Integration and Vibe Coding RescueVibe Coding Rescue: How to Take Over a Codebase Written by ChatGPT
Vibe coding rescue is the process of taking over a codebase that a founder or junior engineer built primarily through AI code generation, then making it maintainable, testable, and safe to extend. The work is not glamorous. It involves reading confusing comments, untangling duplicated logic, and adding tests to code that was never designed to be tested. I do this kind of work regularly and the pattern is consistent enough to explain.
AI Integration and Vibe Coding RescueThe Last 20 Percent: Why Your AI Generated SaaS Fails at Stripe and Security
The last 20 percent of a SaaS build refers to the areas that AI code generation handles poorly: payment processing, authentication, authorization, and security. These areas require precise implementation of rules that have serious business and legal consequences when wrong, and AI generated code in these areas tends to produce plausible looking implementations that are subtly incorrect. The failures are not visible during development or basic testing; they surface when a real user hits a real edge case.