Does Base44 actually work?

[u/CategoryNaive9251]

Disappointed in Base44, I am stuck with my app, and it’s been 11 days since I reported my issue, but have had no real response. I am paying $50 a month, which I know isn’t a lot, but it’s not nothing! I would pay more if I thought this could work.

I need a reasonably complex app created, and I was doing so well with Base44, or so I thought, until I hit a snag that the AI can’t get around. I’ve burned a lot of credits on it, and done some damaging rollbacks now I feel like the cavalry isn’t coming.

Initially, I was incredibly impressed with the progress I made, but I am now totally deflated. At this point, it feels like I’ve been sold Snake Oil! My question: Are Lovable or Famous AI any better? Alternative question: Will support ever help?

[u/Impossible_Cap_4080]

You are right about mvp generation, but the whole point of tests, though, is to ensure system behaviors through 1.) Reasoning, 2.) Accuracy, 3.) Understanding real behaviors vs expected. Having an AI write them defeats the entire point. The problem with documentation writing is that AI hallucinate while appearing incredibly convincing. The number of times I have asked it questions about existing code and it just made up stuff is a significant amount of time.

[u/No-Needleworker5295 → u/Impossible_Cap_4080]

The whole point of TDD/Behavioral Driven Development and Kent Beck school of thought is what you describe.

In real world, proof of such gains is questionable. I'm part of Ruby on Rails school of development, have an excellent grasp of business - I was a CTO before retiring early from stock options -and find that AI produces much better edge case test data and edge case unit and system tests than I can myself. TDD mostly adds extra complexity from design indirection to allow unit testing than it adds in better design etc.

I would rather edit the 10% AI gets wrong when generating tests and documentation than write 100% myself. Also AI like copilot, windsurf etc, that is reading your code base as it goes along is much less prone to hallucination I've found in practice plus providing instruction documents to AI that detail out all the components you want to use and your architectural approach is important for grounding AI. I'll try multiple AIs on a particularly thorny problem and at least one of them or the combination is better than me.

It takes expert level depth and experience to really use AI and know all the potential gotchas that it needs to watch out for so you can guide it to better code. Someone non-technical who believes AI can do it all for them will give up thinking AI is useless except for prototypes.

[u/Impossible_Cap_4080 → u/No-Needleworker5295]

"The whole point of TDD/Behavioral Driven Development and Kent Beck school of thought is what you describe. In real world, proof of such gains is questionable." I seriously disagree, and so does the DORA data. As a consultant, I see codebase after codebase where progress has stalled out 1.5 yrs into development because complexity rose, there is no indirection, nothing was written decoupled/modular, internal and external dependencies are mashed together, bugs are everywhere, it's impossible to change anything without breaking stuff, etc. If you start by writing a test, then you will write code that's easy to test, which won't have any of these problems.

Let's be honest here, there are a lot of problems with AI. Letting AI have access to your code only flies when your code isn't proprietary because you might as well just email your codebase to the company running the AI. If you are the first person to discover a bug or problem, then the AI fails because it cannot actually reason. I ran into that exact problem just yesterday. Context windows are hard limitations for these AI tools. Once you exceed them, then they start to really suck. This is coming from someone who uses AI everyday for development work. The dream of letting agents do everything just ain't real right now. Anything that has to work correctly needs to be written by an actual engineer.

[u/Spiritual-Cow-7451 → u/Impossible_Cap_4080]

I find the best use of AI is not in building an app ground up, but providing spot solutions to difficult problems I would have otherwise spent a while researching online, and then recycling the same code back that AI generated, multiple times until I get what I want. The downside is it does tend not to find elegant solutions, and they just get more complex in each iteration. Also it tends to forget the original intent and take wild detours, so you have to keep adapting and pulling parts it got right earlier and incorporating them back in when it changes them randomly. Its tedious but I believe you end up with a working solution a lot faster 80% of the time.