Comment by ummonk
What is the actual value of using agentic LLMs (rather than just LLM-powered autocomplete in your IDE) if it requires this much supervision and handholding? When is it actually faster / more effective?
What is the actual value of using agentic LLMs (rather than just LLM-powered autocomplete in your IDE) if it requires this much supervision and handholding? When is it actually faster / more effective?
The primary value is accrued by the AI labs. You pay hundreds or thousands of dollars a month to train their AI models. While you probably do increase your productivity saving time typing all the code, the feedback that you give the agent after it has produced mediocre or poor code is extremely valuable to the companies, because they train their reinforcement learning models with them. Now while you're happy you have such a great "assistant" that helps you type out code, you will at some point realize that your architectural/design skills really weren't all that special in the first place. All the models lacked to be good at that was sufficient data containing the correct rewards. Thankfully software engineers are some of the most naive people in the world, and they gave them that data by actually paying for it.
Why use a nailgun instead of a hammer, if the nailgun still requires supervision and handholding?
Example: Say I discover a problem in the SPA design that can be fixed by tuning some CSS.
Without LLM: Dig around the code until I find the right spot. If it's been some months since I was there this can easily cost five minutes.
With LLM: Explain what is wrong. Perhaps description is vague ("cancel button is too invisible, I need another solution") or specific ("1px more margin here please"). The LLM makes a best effort fix within 30 secs. The diff points to just the right location so you can fine tune it.