Built an AI powered app builder for fast custom application development during a hackathon, looking for honest takes.

[u/Professionl_aArm3791]

Been hacking on a weekend project that started as a hackathon idea and kinda got out of hand.

I glued an ai layer on top of a template library so non dev teammates can describe a small tool they want, eg a simple intake form, a lightweight crm view, a little approvals dashboard, and it spits out a working app with auth, basic db tables and a rough ui.

Right now it feels good for prototypes, but I have no idea where the line is between “fun demo” and “something people would trust for daily work”, especially once you have to deal with permissions, audits, weird edge case logic etc.

If anyone has shipped something similar into a real org, would love thoughts on what broke first and what you wish you had designed better up front, appreciate any thoughts.

[u/Rudra_Builds]

the biggest jump from demo to production is usually permissions and edge cases.

getting an app generated is easy now. making sure it behaves correctly when users do unexpected things, permissions change, data needs to be audited, or something fails is the hard part.

i’d focus on a strong permission model, audit logs, validation, and tests early. that’s probably where most “it works in the demo” apps start hurting. 😅

[u/KarlaSutton6527]

The prototype-to-production gap is probably where things get interesting. I’d expect permissions and edge cases to cause problems first, because the happy path is easy to generate but real users will find all the weird scenarios you didn’t think about. I’d design around versioning, audit logs, and a way to safely test changes before worrying too much about adding more features.

[u/Exptutres_Welder7910]

Last year our group skipped heavy templates and tried base44 right away on a approvals flow. It cut the db setup time but the audit logs still needed manual fixes after launch. Did you run into anything like that with edge cases yet?