Hacker News Reader

Comment by layer8 | Hacker News Reader

This is the same fallacy as low-code/no-code. If you have to check a precise algorithm, you’re effectively coding, and you need a language with the same precision as a programming language.

View on HN

Only if you want a production-ready output. To get execs able to self-feed enough, this works fine. Look, you don’t see value until it’s perfect. Good, other people do. I see your fallacy and raise you a false dichotomy.

The problem I see is how do you verify that the result of your text-to-sql is really what you were asking for, without understanding the SQL (or “the algorithm”)? It boils down to that you have to know what you are doing, and with the present state of art of AI we can’t have confidence in that.

I’m assuming exploratory work from the exec, not something they make decisions with or put into production. If you need something you can trust, you typically need a lot of checks, including multiple humans.

I play a weird part at work near AI. I use it all the time but I’m the first person to warn everyone that it’s absolutely not trustworthy. No matter your prompt, the data, the guidelines built into it, the output is fundamentally flaky. But I use it while knowing that and working around it. Making the process reliable is a big part of my focus, and usually that means minimising the part the LLM plays. Checks and balances live where things are predictable.

Reply on news.ycombinator.com