The Ultimate Guide to Making Your Entire Development Cycle AI Native
Most engineering orgs adopting AI coding assistants are getting slower, not faster. A randomized study found developers finish tasks 19% slower with AI while being convinced they were 20% faster. The problem isn't the model - the problem is they don't have a system and team standard. This is the full two-hour workshop where I take a real brownfield codebase that has nothing (no rules, no skills, no connections) and make its entire SDLC AI native, live! A PRD in Confluence all the way to a pull request an agent has already reviewed in CI, covering the PM, the developer and QA. It's model and tool agnostic, so it works whether your org runs Claude Code, Codex, Copilot, Cursor, Pi, or any other coding agent. The entire system is built right within source control, so every engineer who uses that repo inherits the same rules and workflows with zero setup. The starter pack I use throughout is free and public! ~~~~~~~~~~~~~~~~~~~~~~~~~~ Check out Bluehost, one of the best platforms for hosting your apps and agents: https://www.bluehost.com/ ~~~~~~~~~~~~~~~~~~~~~~~~~~ - Apply for a private team workshop: https://dynamous.ai/ai-native-engineering-org-apply - Join the Dynamous community for the full Agentic Coding Course: https://dynamous.ai - The AI Layer Starter Pack: https://github.com/coleam00/ai-native-starter-pack ~~~~~~~~~~~~~~~~~~~~~~~~~~ 0:00 Intro 1:45 The Shift to Agentic Engineering 5:45 A Template, Not a Framework 9:33 Sponsor: Bluehost 10:43 The Productivity Mirage 12:33 How Most Teams Use AI Today 15:22 The Brownfield Codebase 18:21 Vibe Coding: What Not to Do 22:00 The AI Native SDLC Blueprint 25:51 Q&A: Tooling, CI, and Copilot 30:37 The AI Layer Starter Pack 33:33 Global Rules and the Skills Library 37:04 Running /create-rules 39:44 The Six Parts of the AI Layer 41:32 Keeping CLAUDE.md Lean 44:52 The AI Layer Belongs in Source Control 49:01 PM Workflow: PRD to Jira Tickets 53:49 Connecting Your Agent with MCP 57:01 The Five Levels of AI Coding 59:59 Q&A: Jira vs GitHub Issues 1:03:07 Reviewing the Generated Tickets 1:05:04 The Developer's Turn: Priming a Ticket 1:09:14 The R-PIV Loop Explained 1:11:36 Interviewing the Agent 1:16:52 Creating the Structured Plan 1:23:49 Execution in a Fresh Session 1:28:11 Q&A: /init, Central Repos, Staying Sharp 1:36:21 What Archon Adds 1:41:43 Automated PR Reviews in CI 1:46:00 System Evolution 1:47:52 Recap: The Full AI Native SDLC 1:48:58 Private Team Workshops 1:51:51 Q&A: Architecture Changes Mid-Loop 1:54:18 Q&A: Evals for Your AI System ~~~~~~~~~~~~~~~~~~~~~~~~~~ Join me as I push the limits of what is possible with AI. I'll be uploading videos weekly - at least every Wednesday at 7:00 PM CDT!
