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Thoughts on a month with Devin

answer.ai

11–20 of 194 posts

Re: Thoughts on a month with Devin

#11
post #9

I think one of the big problems with Devin (and AI agents in general) is that they're only ever as good as they are. Sometimes their intelligence feels magical and they accomplish things within minutes that even mid level or senior software engineers would take a few hours to do. Other times, they make simple mistakes and no matter how much help you give, they run around in circles. A big quality that I value in juni…

I completely agree with you. More precisely, I feel they are useful when you have specific tasks with limited scope.

For instance, just yesterday I was battling with a complex SQL query and I got halfway there. I gave our bot the query and an half assed description of what I wanted/what was missing and it got it right on the first try.

Re: Thoughts on a month with Devin

#12

Sounds exactly like my experience with the “agents” about a year ago. Autogpt or whatever it was called. Works great 1% of the time and the rest it gets stuck in the wrong places completely unable to back out. I’m now using o1 or Claude Sonnet 3.5 and usually one of them gets it right.

The current frontier models are all neocortex. They have no midbrain or crocodile brain to reconcile any physical, legal or moral feedback. The current state of the art is to preprocess all LLM responses with a physical/legal/moral classifier and respond with a generic "I'm sorry Dave, I'm afraid I can't do that."

We are fooled into thinking these golems have a shred of humanity, but their method of processing information is completely backward. Humans begin with a fight/flight classifier, then a social consensus regression, and only after this do we start generating tokens ... and we do this every moment of every day of our lives, uncountably often, the only prerequisite being the calories in an occasional slice of bread and butter.

Re: Thoughts on a month with Devin

#13
Honestly, i have been bitten so many times by LLM hallucinations when I work in parallel with the LLM, I wouldn't trust it autonomously running anything at all. If you have tried to use imaginary APIs, imaginary configuration and imaginary cli arguments, you know what I mean

Re: Thoughts on a month with Devin

#14
post #6

One thing that surprised me a little is that there doesn't seem to be an "ask for help" escape hatch in it - it would work away for literally days on a task where any human would admit they were stuck? One of the more important features of agents is supposedly that they can stop and ask for human input when necessary. It seems it does do this for "hard stops" - like when it needed a human to setup API keys in their c…

LLMs can create infinite worlds in the error message it’s receiving. It probably needs some outside signal to stop and re-assess. I don’t think LLMs have any ability to reason if they’re lost in their own world on their own. They’ll just keep creating new less and less coherent context for themselves

For sure - but if I'm paying for a tool like Devin then I'd expect the infrastructure around it to do things like stop it if it looks like that has happened.

What you often see with agentic systems is that there's an agent whose role is to "orchestrate", and that's the kind of thing the orchestrator would do: every 10 minutes or so, check the output and elapsed time and decide if the "developer" agent needs a reality check.

Re: Thoughts on a month with Devin

#15
post #9

I think one of the big problems with Devin (and AI agents in general) is that they're only ever as good as they are. Sometimes their intelligence feels magical and they accomplish things within minutes that even mid level or senior software engineers would take a few hours to do. Other times, they make simple mistakes and no matter how much help you give, they run around in circles. A big quality that I value in juni…

My first job I spent so much time reading Python docs, and the ancient art of Stack Overflow spelunking. But I could intuitively explain a solution in seconds because of my CS background. I used to encounter a certain kind of programmer often, who did not understand algorithms well but had many years of experience with a language like Ruby, and thus was faster in completing tasks because they didn't need to do the reference work that I had to do. Now I think these kinds of programmers will slowly disappear and only the ones with the fast CS intuition will remain.

Re: Thoughts on a month with Devin

#16
post #13

Honestly, i have been bitten so many times by LLM hallucinations when I work in parallel with the LLM, I wouldn't trust it autonomously running anything at all. If you have tried to use imaginary APIs, imaginary configuration and imaginary cli arguments, you know what I mean

> If you have tried to use imaginary APIs, imaginary configuration and imaginary cli arguments, you know what I mean

I see this comment a lot but I can't help but feel it's 4 weeks out of date. The version of o1 released on 2024-12-17 so rarely hallucinates when asked code questions of basic to medium difficulty and provided with good context and a well written prompt, in my experience. If the context window is sub-10k tokens, I have very high confidence that the output will be correct. GPT-4o and o1-mini, on the other hand, hallucinates a lot and I have learned to put low trust in the output.

Re: Thoughts on a month with Devin

#17
Those “how I feel about Devin after using it” comments at the bottom are damning, when you compare them to the user testimonials of people using cursor.

Seems to me that agents just aren’t the answer people want them to be, just a hype wave obscuring real progress in other areas (eg. MCST) because they’re easy to implement.

…but really, if things are easy to implement, at this point, you have to ask why they haven’t been done yet.

Probably, it seems, because it’s harder to implement in a way that’s useful than it superficially appears…

Ie. If the smart folk working on Devin can only do something of this level, anyone working on agentic systems should be worried, because it’s unlikely you can do better, without better underlying models.

Re: Thoughts on a month with Devin

#18

Disclosure: Working on a company in the space and have recently been compared to Devin in at least one public talk. Devin has tried to do too much. There is value in producing a solid code artifact that can be handed off for review to other developers in limited capacities like P2s and minor bugs which pile up in business backlogs. Focusing on specific elements of the development loop such as fix bugs, add small feat…

Not to take away from your opinion, but I guess time will tell? As models get better, it's possible that wide tools like Devin will work better and swallow tools that do one thing. I think companies much rather have a AI solution that works like what they already know (developers), than one that works in the IDE, another that watches to Github issues, another that reviews PRs, and one that hangs on Slack and makes small fixes.

> Businesses like Factory AI or my own are taking that approach and we're seeing real interest in our products.

Interest isn't what tools like Devin are lacking, (un)fortunately.

To be clear, I do share a lot of scepticism regarding all the businesses working around AI code generation. However, that isn't because I think they'll never be able to figure it out, but because I think they are all likely to figure it out at the end, at the same time, when better models come out. And none of them will have a real advantage over the other.

Re: Thoughts on a month with Devin

#19
post #6

One thing that surprised me a little is that there doesn't seem to be an "ask for help" escape hatch in it - it would work away for literally days on a task where any human would admit they were stuck? One of the more important features of agents is supposedly that they can stop and ask for human input when necessary. It seems it does do this for "hard stops" - like when it needed a human to setup API keys in their c…

LLMs can create infinite worlds in the error message it’s receiving. It probably needs some outside signal to stop and re-assess. I don’t think LLMs have any ability to reason if they’re lost in their own world on their own. They’ll just keep creating new less and less coherent context for themselves

If you correct an LLM based agent coder, you are always right. Often, if you give it advice, it pretends like it understands you, then goes on to do something different from what it said it was going to do. Likewise, it will outright lie to you telling you it did things it didn't do. (In my experience)

Re: Thoughts on a month with Devin

#20
post #6

One thing that surprised me a little is that there doesn't seem to be an "ask for help" escape hatch in it - it would work away for literally days on a task where any human would admit they were stuck? One of the more important features of agents is supposedly that they can stop and ask for human input when necessary. It seems it does do this for "hard stops" - like when it needed a human to setup API keys in their c…

> One thing that surprised me a little is that there doesn't seem to be an "ask for help" escape hatch in it - it would work away for literally days on a task where any human would admit they were stuck?

You are over-estimating the sophistication of their platform and infrastructure. Everyone was talking about Cursor (or maybe was it astroturfing?) but once I checked it out, it was not far from avante on neovim.

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