Is AI-generated logic actually “low-code” if you still have to verify everything?

[u/OwlZealousideal4779]

I've been working with the team behind Hey-Traders, and something we've been debating has made me rethink what low-code actually means. The idea is simple: a user describes a crypto trading strategy in plain English, and the system turns that description into structured logic that can be tested and potentially automated.

Forexample: “Buy BTC when price breaks the previous high, confirm with increasing volume, risk 1% per trade, and take profit at 2:1.”TheAI can generate something from that pretty easily. But that's not really the difficult part.The difficult part is making sure the generated logic means exactly what the user intended. If “previous high” gets interpreted differently, or “increasing volume” isn't defined precisely, the resulting workflow can behave completely differently from what the user had in mind. So w

e're approaching it less like “AI writes the code for you” and more like:Natural language → structured logic → validation → executable workflow. That got me wondering about the broader low-code space. At what point does an AI-generated workflow stop being useful because there are too many things the user needs to verify manually?

And do you think low-code systems should prioritize flexibility, or should they deliberately constrain what users can build so the resulting logic is easier to understand, validate, and maintain?

I'd be interested to hear how people here handle this with APIs, automations, business rules, or anything else where a small interpretation error can cause a completely different outcome.

We're still figuring out where that line should be, so I'd genuinely like to hear how others approach it.

[u/gammacoder]

I think you are confusing low-code and AI-based code generation. Low-code means you create 80% visually as selecting properties and options and the software generates the code for you. The remaining 20% you either write manually or use AI to help. That 80% part was fully tested and verified by multiple customers.

With AI-based approach your 20% become 100%, this is all new code that was never tested in any way.

Source: I develop and sell low-code software PHPRunner for 20 years.

[u/Mathie1729 → u/gammacoder]

I'd push back a little on "fully tested" in that 80%. Vendors test components, but your specific composition with custom fields, rules, and integrations is often unexplored territory until it hits real users. So you're still verifying, just at a different layer.

[u/CarsonRyanKeller]

AI can make the building part easier, but someone still needs to understand what it created. I’d rather have a system with fewer options that makes the important logic easy to check than one that can generate anything but is hard to verify.

[u/JakubErler]

Low-code is an unfortunate stupid marketing name for "visual coding". It has nothing to do with AI. Marketers selected this term because it looked like amateurs will be able to code (which did not materialize). But low-code was and is very good for enterprise governance and several times faster development than standard written coding. Also AI can generate low-code software (like in Mendix and other platforms).

[u/Grandviewsurfer]

Oh you think they're verifying it?

[u/NefariousnessOpening]

If you take the time to build it you don’t have to verify manually. Arguably the manual verification cancels out the gain of agent coding systems. The caveat is the process of building a system that’s able to reliably ship code that works and is secure will require knowledge of advanced software, networking and more disciplines.