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?

In my experience, letting LLMs work autonomously just produces code slop.

Also, I have no desire to micromanage a bunch of robots. I rather build things.

So does any template off GitHub?

When you run the Laravel Installer, you got pretty much all of these for free (sans LLM) And within a normal work week, you can have a valid prototype with an admin panel (Laravel Nova), and a lot of stuff that the laravel ecosystem provides. The issue is not coding those stuff (they've already been coded for you). The issue is to know what exactly do you want that is not part of some templates, the actual business value of the software.

> The cognitive load of this new state was immense. After about three hours of intense orchestration, I would feel completely burnt.

I definitely feel that. It's like the job becomes solely architecting the system (not terrible) but you still need to hold the entire program in your head (deeply taxing) while it is updated by a 1,000 tiny cuts which can dislodge your mental model... and then you are screwed. It is important center yourself from time to time and ensure you are on solid ground. The best way to do that is to give things a minute to sink in. Unless I am boilerplating everything, I don't WANT to go faster.

In general, I don't have a lot of desire to go down this orchestrator path. Maybe once tooling and things settle down a bit it can be helpful at times, but usually I get more value from letting things breathe, especially if there are structural changes or new ideas that bubble up and need to be considered.

Before LLMs, I would never re-architect on the fly, but I am more willing to make structural changes mid-flight now because it is so costless. Things I used to architect "good enough" (with a plan to revise in 12 months now) can be done precisely right the first time after going halfway down a path then noodling on it for an a day or so.

This is "Not the Way to Architect," but it sure is an effective way to go from idea -> complete.

one of the weirdest things about LLMs now being cheap and easily available is finding out how many people have no pride in their work, and will just "send a PR to the curl team without understanding it" or "publish some crap blog post, on their personal blog, and then push it to HN".

why?

it's great that you found a tool that can generate text for you to pass off as your own, but why did you then stop giving a fuck about what you're passing off as your own?

I’m not claiming vibe coded projects don’t have a place. I’m skeptical that using English prompts can build a maintainable code base as well as using a programming language.