Hello All, this is a mixture of two AI outputs based on my personal projects AI operational workflow. Sharing as food for thought and discussion. There a lot here to read here. Not sure how well the formatting will hold up. Any feedback welcome, lots more ideas to take this further in the works, but as of now its performing very well, even with lower models (in fact been testing it and improving it on using feedback from weak local models outputs to frontier models to adjust to save the same issues occurring again). ⭐PART 1 Operational The approach is to make agent work explicit, bounded, and evidence-driven. Agents are given: - A map. - A workflow. - A small reading list. - Known pitfalls. - Specialist help. - Verification gates. - Review expectations. - Examples of good output. Humans get: - More predictable agent behavior. - Cleaner handoffs. - Easier review. - Less repeated explanation. - A mechanism for turning mistakes into durable process improvements. The most important shift is cultural: stop treating AI assistance as a chat transcript and start treating it as an operational system. The files, prompts, rubrics, checklists, and gotchas are the system. The agent is just the worker moving through it. # Generic AI Agent Setup Overview This document describes a reusable, high-level approach for setting up a repository so AI agents can work inside it reliably. It intentionally avoids product-specific, stack-specific, and implementation-specific details. The focus is the operating model: how agents discover context, choose the right workflow, avoid repeated mistakes, produce evidence, and hand work back to humans in a reviewable state. The core idea is to treat AI agents like fast but context-limited contributors. They need a clear map of the repository, explicit rules for what they may and may not change, task-specific reading lists, examples of good finished work, and gates that force them to prove outcomes rather than merely assert confidence. ---

1. Watch the intro video and introduce yourself in the intro post here 2. Start with The Foundation (free course). Concepts, folder architecture, prompting framework. Everything else builds on this. 3. Check in at the bottom of each lesson. Polls, discussion posts, other members working through the same stuff. Use them. 4. When you're ready to build real things, move to Implementation Playbooks (Level 2). When you're ready to build your own tools, Building Your Stack (Level 3). 5. Post your work. Ask questions. Help others when you can. What are you here to build?