I built a production app in a week by managing a swarm of 20 AI agents
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Re: I built a production app in a week by managing a swarm of 20 AI agents
#2Hey HN, author here.
I spent last week in a deep-dive experiment to see how far I could push modern agentic workflows on a greenfield project. I wanted to move past simple code generation and see if I could build a system where I was orchestrating a team of agents to build a full application.
The results were pretty wild (~800 commits, 100+ PRs, and a functioning app we use internally at my company), but the most interesting part was the playbook of rules I had to develop to make it work. The post covers the 8 rules I learned, from managing the AI's context window with sub-agents and manual checkpoints, to creating autonomous test loops, to why I had to become ruthless about restarting failed runs.
A few quick notes to preempt questions:
Tech Stack: The core of this was Claude Code, a custom parallelization script, and open-source MCPs like Serena.
Cost: The token cost was significant (~$6k). This was an experiment to push the limits, not to optimize for cost efficiency... yet.
Effort: This was not a standard 40-hour week. It was an intense, "in the hole" sprint with a very high cognitive load.
I’m convinced the role of an engineer is shifting from a hands-on coder to an architect of these intelligent systems. I’m curious to hear how others are approaching this. What workflows or tools for managing agents have you found to be effective?
Re: I built a production app in a week by managing a swarm of 20 AI agents
#3Hey HN, author here. I spent last week in a deep-dive experiment to see how far I could push modern agentic workflows on a greenfield project. I wanted to move past simple code generation and see if I could build a system where I was orchestrating a team of agents to build a full application. The results were pretty wild (~800 commits, 100+ PRs, and a functioning app we use internally at my company), but the most int…
Ask yourself what happens when Claude releases Claude Code 2.0, which just uses AI to self-manage the swarms from a simpler prompt.
Re: I built a production app in a week by managing a swarm of 20 AI agents
#4What did you use to write the blog post?
Re: I built a production app in a week by managing a swarm of 20 AI agents
#5Editing notes on the content - the content of this blog post is clearly AI-enhanced (emdash) which is ok but the tone is not. It's super flowery and oversold - example "It was a shift from a single laser to a powerful floodlight."
Re: I built a production app in a week by managing a swarm of 20 AI agents
#6Hey HN, author here. I spent last week in a deep-dive experiment to see how far I could push modern agentic workflows on a greenfield project. I wanted to move past simple code generation and see if I could build a system where I was orchestrating a team of agents to build a full application. The results were pretty wild (~800 commits, 100+ PRs, and a functioning app we use internally at my company), but the most int…
> I’m convinced the role of an engineer is shifting from a hands-on coder to an architect of these intelligent systems.
I think this is what a lot of people do and don't understand. The AI is only as good as your ability to architect the software. I think I'd be okay if someone wrote AI generated code if they hand wrote all unit testing to ensure that the AI isn't producing garbage, I think this is a reasonable trade.
Re: I built a production app in a week by managing a swarm of 20 AI agents
#7Hey HN, author here. I spent last week in a deep-dive experiment to see how far I could push modern agentic workflows on a greenfield project. I wanted to move past simple code generation and see if I could build a system where I was orchestrating a team of agents to build a full application. The results were pretty wild (~800 commits, 100+ PRs, and a functioning app we use internally at my company), but the most int…
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Re: I built a production app in a week by managing a swarm of 20 AI agents
#8It would be a more interesting blog post if you showed that the app they built is actually production ready.
In my experience, letting LLMs work autonomously just produces code slop.
Re: I built a production app in a week by managing a swarm of 20 AI agents
#9Hey HN, author here. I spent last week in a deep-dive experiment to see how far I could push modern agentic workflows on a greenfield project. I wanted to move past simple code generation and see if I could build a system where I was orchestrating a team of agents to build a full application. The results were pretty wild (~800 commits, 100+ PRs, and a functioning app we use internally at my company), but the most int…
So where is the app?
Re: I built a production app in a week by managing a swarm of 20 AI agents
#10Hey HN, author here. I spent last week in a deep-dive experiment to see how far I could push modern agentic workflows on a greenfield project. I wanted to move past simple code generation and see if I could build a system where I was orchestrating a team of agents to build a full application. The results were pretty wild (~800 commits, 100+ PRs, and a functioning app we use internally at my company), but the most int…
> The results were pretty wild (~800 commits, 100+ PRs, and a functioning app we use internally at my company)
I'd be very interested to hear less about the process, and more about the app itself.
If a week "in the hole" resulted in a Slackbot that greets people when they enter a Slack channel, I'd be significantly less impressed than if you'd built, say, a CI pipeline, or something that automatically creates Jira tickets based on outages, or automatically handles subscription renewals or something.
Plus, the number of commits & PRs is absolutely not a useful metric. How well is the app running? How many bugs are you finding day to day? How much functionality is missing, how easy is it to add new functionality based on user feedback, etc? Monitoring?