Claude and Codex workflows depend on more than the model: context, permissions, quotas, and the harness shape the result.

Mike, Joe, and Josh talk through a practical AI coding agent discussion: testing a new AI coding tool on Windows, deciding how much access to give an agent, how Claude and Codex handle projects differently, and why moving work between harnesses is not always seamless.

Topics include:

- AI coding agents on Windows

- Claude, Codex, and different agent harnesses

- Giving agents repo access without handing over private data

- Owning your context instead of fighting tool-specific project state

- Claude subscription limits, third-party usage, and token burn

- Why learning the harness matters before expecting the workflow to transfer

Chapters:

- 00:00 Opening

- 00:23 Combining the episode and testing an AI tool on Windows

- 11:04 The first magic and reliability gap

- 20:59 Enterprise concerns and agent permissions

- 22:25 Letting Codex work on trusted repos

- 27:33 Context windows and agent harnesses

- 34:23 Claude, subscriptions, and third-party harnesses

- 39:13 Extra usage, token burn, and safety questions

- 43:09 Owning your context

- 44:19 Moving context between different harnesses

- 50:04 Learning how each harness works

More Build It Faster: https://fasterpod.com

Mike and Joe celebrate launching their Google Meet lean coffee app, work through branding and early feedback, reduce friction in the Meet experience, assess mobile usability, and reflect on AI-assisted development patterns they want to reuse.

- 0:00 Celebrating Rapid Development

- 2:47 Exploring Branding and Domain Names

- 5:34 Feedback and User Experience

- 8:37 Mobile Experience and Usability

- 11:49 Lessons Learned from Development

- 17:38 Applying Knowledge to Future Projects

Joe preps for the AI Engineer World’s Fair, Mike and Joe review Google Marketplace rejection fixes, then Mike shares how he used Claude for a first production PR and automated his photography paperwork workflow.

- 0:00 Anticipation for the AI Engineer World's Fair Conference

- 2:53 Goals and Expectations for the Conference

- 6:06 Networking and Knowledge Acquisition Strategies

- 9:04 Exploring AI in Literature and Media

- 12:08 Preparing for Effective Networking

- 14:57 Transitioning to New Topics and Future Discussions

- 16:05 Navigating Rejection: Lessons from Google Marketplace

- 21:00 Personal Growth: Achievements in Project Management

- 33:34 Streamlining Photography: Automating the Creative Process