thanks for the share!
The pipe dream of agents handling Github Issue -> PullRequest -> Resolve Issue becomes a nightmare of fixing downstream regressions or other chaos unleashed by agents given too much privilege. I think people optimistic on agents are either naive or hype merchants grifting/shilling.
I can understand the grinning panic of the hype merchants because we've collectively shovelled so much capital into AI with very little to show for it so far. Not to say that AI is useless, far from it, but there's far more over-optimism than realistic assessment of the actual accuracy and capabilities.
1. I create multiple git workspaces 2. I connect Antigravity in multi mode, - one to each 3. I have prompts that I craft on a per workspace node 4. I ask questions and give it bit sized tasks.
Now to be clear, I'm not seeing the wheel reinvented. But the tedious work I'm now churning out at scale, so that I can focus on the heart of the problem. Frankly, I think this speaks to how much boilerplate is frequently required.
[1]: https://kerrick.blog/articles/2025/use-ai-to-stand-in-for-a-...
But scrap that, it's better just thinking about agent patterns from scratch. It's a green field and, unless you consider yourself profoundly uncreative, the process of thinking through agent coordination is going to yield much greater benefit than eating ideas about patterns through a tube.
0: https://arxiv.org/search/?query=agent+architecture&searchtyp...
Like if I'm not ready to jump on some AI-spiced up special IDE, am I then going to just be left banging rocks together? It feels like some of these AI agent companies just decided "Ok we can't adopt this into the old IDE's so we'll build a new special IDE"?_Or did I just use the wrong tools (I use Rider and VS, and I have only tried Copilot so far, but feel the "agent mode" of Copilot in those IDE's is basically useless).
It is like learning to code itself. You need flight hours.
What exactly do you mean with "integrating agents" and what did you try?
The simplest (and what I do) is not "integrating them" anywhere, but just replace the "copy-paste code + write prompt + copy output to code" with "write prompt > agent reads code > agent changes code > I review and accept/reject". Not really "integration" as much as just a workflow change.
There's obviously a whole heap of hype to cut through here, but there is real value to be had.
For example yesterday I had a bug where my embedded device was hard crashing when I called reset. We narrowed it down to the tool we used to flash the code.
I downloaded the repository, jumped into codex, explained the symptoms and it found and fixed the bug in less than ten minutes.
There is absolutely no way I'd of been able to achieve that speed of resolution myself.
Already a "no", the bottleneck is "drowning under your own slop". Ever noticed how fast agents seems to be able to do their work in the beginning of the project, but the larger it grows, it seems to get slower at doing good changes that doesn't break other things?
This is because you're missing the "engineering" part of software engineering, where someone has to think about the domain, design, tradeoffs and how something will be used, which requires good judgement and good wisdom regarding what is a suitable and good design considering what you want to do.
Lately (last year or so), more client jobs of mine have basically been "Hey, so we have this project that someone made with LLMs, they basically don't know how it works, but now we have a ton of users, could you redo it properly?", and in all cases, the applications have been built with zero engineering and with zero (human) regards to design and architecture.
I have no yet have any clients come to me and say "Hey, our current vibe-coders are all busy and don't have time, help us with X", it's always "We've built hairball X, rescue us please?", and that to me makes it pretty obvious what the biggest bottleneck with this sort of coding is.
Moving slower is usually faster long-term granted you think about the design, but obviously slower short-term, which makes it kind of counter-intuitive.
So with the top performers I think what's most effective is just stating clearly what the end result you want to be (with maybe some hints for verification of results which is just clarifying the intent more)
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