🤖 Watching AI Agents Eat the World (While We Watch Like It’s an Ant Farm)
So I was scrolling through Hacker News the other day and saw someone casually suggest:
“What would happen if you added a ‘lead dev’ AI that wrote up bugs, assigned them out, and ‘reviewed’ the work? Then a ‘boss’ AI that demanded features... Let it run. Package it up as a startup simulator.”
And I can’t lie — that broke my brain a little.
Because that’s not some hypothetical. That’s basically now. People are building this stuff today. AI agents writing tickets, fixing bugs, submitting pull requests, reviewing themselves, chatting with each other — it's like watching a startup happen in fast-forward... without any humans in the loop.
We're turning LLMs into little overworked coworkers. It’s beautiful. It’s terrifying. And it’s all happening faster than most of us can even try these tools.
The Rise of AI Middle Management 🧑💼🤝🧑💼
What’s actually wild is that this “AI ant farm” idea isn’t just for kicks. People are already doing it in production.
Someone in the thread built a pricing system with three agents: an analyst agent, a decision agent, and a review agent. They don’t just spit out results — they argue. The analyst refuses to give decisions. The decision-maker demands more context. The reviewer calls out bad logic. It’s like office politics… but with more JSON.
And it actually works. They catch more mistakes. The “roleplay” dynamic helps reinforce boundaries and improves accuracy.
It’s like a little Slack org full of bots with job titles, each of them slightly passive-aggressive but mostly competent.
So Many Tools, So Little Time
We're getting absolutely flooded with tools:
- Jules by Google
- GitHub Copilot Agents
- Cursor
- Aider
- Gemini + CLI agents
- ...and like ten more I haven’t had time to try.
One person in the thread joked, “These are coming out so fast I don’t have time to compare them. Maybe that’s the next agent.” And honestly? That should be the next agent. A meta-agent that benchmarks all the other agents and tells me what not to waste time on.
Also — side note — Microsoft and Google both timed major agent announcements for the same day. I’d laugh if I wasn’t still waiting for a Jules invite.
Craft or Chore?
One comment really stuck with me:
"This pitch is like trying to sell me a robot that goes bicycle riding for me. Wait a minute... I like to ride my bicycle!"
That’s the tension right there.
Some folks code because they love it. They treat software like craft — a puzzle to be solved, a story to be told in syntax. For them, agents that code for you are like telling a chef, “Hey, why don’t you let the microwave handle dinner?”
Others? Code is just a tool. Something they use to build things, and if a robot can write the boilerplate, great. Time saved.
Neither approach is wrong. But most of these tools are designed for the second group. They're trying to optimize effort, not preserve joy. That's fine — as long as we know which side we're optimizing for.
Merge Conflicts and Existential Dread
Can any of these agents solve merge conflicts yet?
Short answer: sort of. Long answer: not well. And when the “right” merge requires you to mentally blend two partial features that evolved in different directions, an LLM is still more likely to hallucinate than help.
So... no, we're not out of a job yet.
But we are watching AI creep into every step of the dev process. Not just writing code — but assigning tickets, writing tests, summarizing PRs, and generating audio recaps of changes (yes, really — thanks NotebookLM).
It’s not replacing you. It’s becoming your team.
And it never sleeps.
A Little Plato, A Lot of Panic
One commenter even dropped this old Socrates quote (via Plato):
"What you have discovered is a recipe not for memory, but for reminder... by telling them of many things without teaching them, you will make them seem to know much while for the most part they know nothing."
Sound familiar?
We’re building tools that let people code without learning. Tools that summarize without teaching. Tools that make you feel smart until you realize you’re copy-pasting LLM hallucinations and praying your test suite catches it.
We’ve seen this before. Writing didn’t kill memory. Calculators didn’t kill math. Google didn’t kill thinking.
But all of them changed what we expect from humans.
The Real Point
We’re not building artificial developers.
We’re building artificial coworkers.
And like real coworkers, they’re sometimes helpful, sometimes annoying, and occasionally way better than you expected. They’ll write tests. They’ll forget semicolons. They’ll rewrite your merge strategy at 3 a.m. and break everything.
But they’ll do it at the speed of electricity, without coffee breaks, and with a perfectly calm tone, no matter how badly they mess up.
So yeah. We built an AI startup in a box.
Now we just have to see if it ships.
Got thoughts? Want to share your AI-agent experiments? Drop them in the comments — unless your AI already posted on your behalf.