AI Hero Studio - The Agent Factory

The Agent Factory: A Monorepo Built for AI Coding

We treat our development environment as a product for the coding agent: one monorepo, plus CLAUDE.md recipes disciplined enough that Claude Code can follow them. When that holds, features that would normally cross three teams collapse into single-session, single-commit changes. Here are three examples from one week of building AI Hero Studio.

Tags
AI AgentsClaude CodeMonorepoDeveloper Experience
Updated
July 13, 2026
Reading Time
15 min

The Problem

On December 28th, I typed "add a goal tracking agent" into Claude Code. Three hours later, a complete intentions agent (backend, frontend, voice integration, and website update) was in production. One commit, nearly 3,000 lines, twenty files.

Three days later, I shipped a feedback and memory system: users can thumbs-up agent responses, the system learns from patterns, and agents remember preferences across sessions. Six commits over three days, about 4,500 lines.

On January 1st, a complete daily summary email system. Celery task queue, distributed scheduling, timezone handling, Kubernetes manifests. One commit, in production by evening.

None of this is about typing faster. It's about treating the development environment as a product for the coding agent: one monorepo, plus written recipes disciplined enough that the agent can follow them. When that holds, a change that would normally cross three teams collapses into one session and one commit.

Traditional development is slow because coordination is slow. A new feature touches the backend, the frontend, maybe infrastructure. That's three teams, three repositories, three deployment pipelines. A backend engineer opens a PR and waits for review. The frontend engineer can't start until the API exists. DevOps sets up the infrastructure last. Calendar time stretches from days to weeks, and every handoff costs a mental model: the backend engineer moves on, frontend integration reveals a problem, and they have to reload context they've already dropped.

We call our setup an agent factory: a monorepo designed for AI-assisted development, optimized for how tools like Claude Code understand, navigate, and modify code. One distinction is worth making, because the term "software factory" has since become popular for something else: a software factory's product is software, with agents autonomously turning specs and signals into shipped code while humans direct, whereas our agent factory's product is agents, and the point is structuring the repo as a product for the coding agent, with the developer still in the session.

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Article by

Rahul Parundekar

Rahul Parundekar

San Francisco-based consultant specializing in cutting-edge Generative AI (GenAI). I partner with organizations to pinpoint high-impact opportunities, streamline AI operations, and accelerate the launch of innovative products—efficiently, cost-effectively, and with controlled risk. Founder of Elevate.do and A.I. Hero, Inc.