Steldi Hurey

I have been using automated coding assistants for rapid prototyping over the past few weeks, and while it speeds up building initial ui screens tremendously, it also generates a lot of redundant utility classes and messy state logic.

every time i clean up the code manually, i wonder if there is a better prompt pattern or workflow to force cleaner output from the start.

for those building full products with ai tools, how do you prevent your repository from becoming an unmaintainable nightmare after a few weeks of fast iteration?

You call a company, explain your issue to the bot, get transferred, and explain it again. Then you message them on WhatsApp the next day and start from zero.

The fix isn't a smarter model. It's shared memory: past interactions, decisions and customer context stored in one place, available to every agent and every human with permission to see it. When a customer says "can we pick up where we left off?", the next conversation should already know where that was.

This turned out to be one of the hardest parts of our platform to get right, especially with permissions.

Have you seen a company do this well? Which product made you feel remembered?
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Our AI employees have names. Peter is an SDR, Kavya sells insurance, Arjun is a loan officer, Priya handles renewals.

We did it because customers found it easier to talk about "Peter's pipeline" than "the lead qualification workflow." Teams started treating the agents like colleagues with a job, which made it easier to define what each one owns.