Something isn't clear about the size of your codebase here and the level of reliability your customers expect, as a reader of your comments. Clarity there will help.
My observation has been:
- Initial greenfield work by an LLM is fast and very effective with minimal or no human oversight.
- Subsequent work ends up being over engineered and very verbose. Assumptions are made that aren't suited to the problem at hand (for example I find Fable is extremely regex happy where structured data would work much better from a readability perspective.)
- Once code bloats beyond a certain point due to unguided LLM usage, complexity is high enough that only LLMs can operate on the codebase with any economical amount of time.
- Rinse repeat and your code ends up unclear about any state that's not explicitly being tested and verified in QA loops
For some of our products this has been fine, for others it's been problematic. An understanding of your size and reliability requirements will help make the conversation more productive.
> unguided LLM usage
Why aren't you guiding your LLM usage? Is that what I said - to spam it and not guide anything? Or to have a careful workflow where you agree on design and maximize your human judgement/leverage?
> any state that's not explicitly being tested and verified in QA loops
As opposed to before, when engineers perfectly reasoned about code behavior from first principals and QA was unnecessary?
> Why aren't you guiding your LLM usage? Is that what I said - to spam it and not guide anything? Or to have a careful workflow where you agree on design and maximize your human judgement/leverage?
You didn't say anything positively or negatively regarding this so I made an assumption that you were using the LLM relatively unguided (e.g. a bit of oversight, not the kind of thing that heavy code reviews used to involve pre-agents.) Feel free to add clarity on your actual usage loop.
> As opposed to before, when engineers perfectly reasoned about code behavior from first principals and QA was unnecessary?
In my experience, most engineers are quite good at reasoning about code behavior for non-QAed code paths. Obviously things fall through the cracks. But I've been in the ground floor of plenty of Big Techs in their early stages before agents and, yes, a lot of initial development had spotty test coverage and yet most of the engineers had good mental models of what was happening. It used to be a very valuable skill to wrap your head around a torrid piece of code with few or no tests but was nonetheless a core piece of your application. Conversely, agentic development can bring cognitive debt [1].
===
This isn't a fight. We aren't sparring over what's right and wrong. I'm just curious how other people use agents in their work as someone who is also now in a startup that uses LLM agents heavily and has no limitations on spend.
[1]: https://martinfowler.com/fragments/2026-02-09.html
> You didn't say anything positively or negatively regarding this so I made an assumption that you were using the LLM relatively unguided
I feel like this statement betrays your lack of advanced experience coding with LLMs.
OP's elaboration of the steps they are going through (planning, agreeing on plan, getting one LLM to draft execution plan, approving it, then executing with a separate LLM, then reviewing/testing) made it super obvious to me that they are guiding their LLMs quite considerably as part of their work.
Anyone making blanket statements about LLMs producing garbage is just telling on themselves about not having proper SDLC practices in place.
Planning, agreeing on a plan, separating planning and implementation LLM, using separate review LLMs, these are all table stakes. This isn't "guidance" if you're getting paid to write software. If you think "unguided" means "I typed a prompt into claude code and waited yolo" I don't know what to say but, you have a very different idea of what professionals do than I do.
I find for my own work that I need to read the diff the LLM produces then offer feedback on the diff in its own loop before I am satisfied, and this is after all the unattended QA steps through Codex Computer or Claude MCPs happen. Then auto reviewers come in and then reviewers come in. Of course, at our stage, we rarely have this luxury and it's only reserved for the very core of our codebase.
This is still much less guidance than we used to do for code before agents became popular. Even at Series A companies, before agents, we used to socialize tech specs, get buy-in from multiple engineers, create test plans, etc etc.
> Anyone making blanket statements about LLMs producing garbage is just telling on themselves about not having proper SDLC practices in place.
> I feel like this statement betrays your lack of advanced experience coding with LLMs.
Are we in school debate club? I don't know what's going on lol, I'm just curious how people are using LLMs! Is it just that irresistable to take a cheap shot at each other?
> Are we in school debate club?
Not that I know of but that's the conclusion I drew from your statement.
It's not a cheap shot unless you took it personally?
I suppose I could have said "the fact that OP's explanation of how they work did not lead you to conclude they were in fact guiding their LLM usage quite a bit tells me that perhaps you have not been working with LLMs in any advanced capacity".
For the SDLC comment I admit it was a broader statement (based on observing people generalizing that "LLMs produce bad outputs") and not specifically aimed at you, and I didn't make that clear, so my bad.
> "unguided" means "I typed a prompt into claude code and waited yolo"
Yes, this is literally what that means.
> If you think "unguided" means "I typed a prompt into claude code and waited yolo" I don't know what to say but, you have a very different idea of what professionals do than I do.
What exactly does "unguided" mean to you, then?
Not having human input in the loop, i.e. allowing agents to act without guidance. I understand the idea of having agents guide agents, but really how much do we gain when Sol scolds Fable?
AI is an accelerate tool for any organizations, management thinks it'll solve their organization issue because it accelerates it. Most often, it accelerates toward a wall.
Design is too expensive, we do agile. QA too expensive, we fire all of them, and claim devops is the now, which allows us to fire the Ops team too, 100% ownership from deisng to ops on devs.
One person with an agent can replace all these teams. Yeah mo profits.