THE ZAGVO BLOG
Practical notes on planning, building, debugging and shipping software with AI tools. No AI hype. No prompt lists copied from Twitter. Just useful context for getting your product built.
Most builders think their AI tool is failing them. Usually the tool is fine. The prompt is fine. What's missing is the next correct move. Here's how to think about sequencing work when an AI builder is doing the typing.
The gap between an idea and a first working screen is where most projects die. A practical framework for turning a vague idea into a single first build task an AI tool can actually complete.
Your Lovable prototype looks like a product. That's the dangerous part. Here's what to inspect, test and harden before you assume you have something real, and how to decide the next slice of work.
When an AI tool patches the same bug three times in a row, the problem isn't the model. It's context loss and symptom fixing. Here's how to interrupt the loop and give the tool something it can actually resolve.
The fastest way to slow down an AI build is to ask for six things at once. A tighter scope isn't a compromise. It's what makes the first version shippable and the second version possible.
Your app looks finished. The buttons work. The dashboard loads. That does not mean it's ready for real users. A practical readiness check across core flow, auth, data, mobile, failure states and payments.
Every week someone asks which AI builder is best. It's the wrong question. What matters is the match between the tool, the stage of your build and how comfortable you are inspecting what the tool produces.
After running hundreds of hackathons and innovation programs, one pattern kept repeating. Builders don't get stuck on hard problems. They get stuck on the wrong next problem. Notes on why that happens and what to do instead.
