Build It Faster

Mike and Joe discuss using Claude with GitHub Issues, PRs, repo instructions, local dev, and Google Meet add-on work while refining their lean coffee tool’s UI and workflow.

- 00:00 Mike tries the new AI-assisted workflow

- 01:13 Old Git tooling mistakes and a cleaner process

- 03:47 PRs, deploys, and local development

- 06:07 Claude Code limits and session timing

- 07:18 GitHub Issues as agent memory

- 10:58 Infrastructure, deploy labels, and environments

- 14:09 Wrap-up and adversarial check skills

- 17:27 Planning sessions, Slack context, and model choice

- 20:29 Memory files versus repo instructions

- 23:27 Issue granularity and agent-ready work

- 27:04 What changed in the product this week

- 28:41 UI cleanup, menus, confirmations, and controls

- 36:28 Simplifying the start timer behavior

- 39:49 Why standalone browser mode still matters

- 45:01 Seeing the Google Meet add-on working

- 49:40 The pivot, the beachhead, and what comes next

- 52:36 Small UI bugs and mobile-width polish

- 55:08 What is still blocking public release

Tags: claude code, github issues, ai coding agents, software development workflow, pull requests, google meet add-on, lean coffee, product development, build it faster, agent memory, developer workflow, ai assisted coding

Mike and Joe turn a sprawling lean coffee/video side project into a focused Google Meet add-on plan: remove built-in video, target book club first, use ephemeral peer-to-peer boards with export, and create issues from the discussion.

00:00 Setting up a side project session

01:51 Level setting: Instant Coffee and book club

04:25 Asking for a real plan

07:08 Why built-in video is the wrong problem

10:30 Formally cutting video from the app

12:19 Google Meet add-on as the new target

13:35 Free, freemium, and keeping costs low

15:45 Ephemeral boards, exports, and imports

17:35 Premium feature ideas

20:27 First version: peer-to-peer board with export

22:03 Shipping now, premium later

23:34 Do we need a standalone app?

27:53 Going all in on the beachhead

29:33 Lean coffee only, Google add-on only

31:34 Naming and searchability

34:33 Auto-facilitation and future features

36:19 Next step: build the Meet add-on

38:19 Working together through issues

40:08 Cleaning the backlog

41:58 Deployment path and handoff

43:57 The relief of cutting scope

Josh came in with one goal: resist showing us the 3D demo he spent two weeks building. He succeeded. Barely.

Instead we talked about the actual interesting stuff — why he's building systems for AI agents instead of humans, how a mech arena became his favorite benchmarking tool, and what happens when you let Claude playtest your game engine for you.

Also: two Blackwell GPUs, a Glicko rating system, and the most cursed MMORPG premise we've ever heard.

• 00:00 Intro — Mike's late, just Joe and Josh
• 01:04 Six weeks later: redefining success
• 02:34 Enter Matt, the PM partner
• 04:35 Federated agents and the mech arena
• 07:44 BattleBots but autonomous
• 09:20 Why he killed the 3D demo
• 17:32 Mike finally shows up
• 20:58 How the arena actually works
• 24:55 Josh's model stack and hardware ceiling
• 35:48 Monday idea, Friday artifact
• 38:23 BYO LLM: prompt it, throw it in, watch it lose
• 43:15 Tournaments, ratings, Steam for agents
• 51:28 Token fight economics
• 54:16 Three-day POC rule and wrapping up

Mike shares his recent deep dive into AI tools like Claude, exploring how he's integrating them into work processes, building AI-driven workflows, and lessons learned along the way. The conversation covers practical strategies for leveraging LLMs, managing code projects, and enhancing communication and project management with AI.

• 00:00 Introduction and Personal Updates
• 03:17 The Impact of AI on Work Habits
• 06:11 Learning and Teaching AI Tools
• 09:21 Building an AI Guild at Work
• 12:10 Problem Solving with AI
• 18:17 Creating a Google Form with AI
• 24:08 Iterating and Improving Processes with AI
• 28:20 Planning and Context Management in AI Usage
• 30:45 Navigating AI Tools for Project Management
• 32:00 Creating Effective Project Roadmaps
• 34:53 Leveraging AI for Code Analysis
• 38:43 Integrating AI with Data Sources
• 41:43 Focusing AI's Attention on Relevant Information
• 44:46 Optimizing AI for GitHub and Snowflake Access
• 48:57 The Role of AI in PR Management
• 53:39 Trusting AI: The Need for Human Oversight

Mike recently got access to Claude Code at work — and as a non-engineer, he's been using it in ways nobody expected. In this episode, Mike and Joe break down what happens when a PM starts interrogating the codebase, from learning how systems actually work to catching years of organizational mythology that turned out to be wrong. They explore practical use cases for non-technical folks — market research, data access, UI mockups — and get into the weeds on Mermaid diagrams, hallucination strategies, and sub-agents. They also both happen to be starting AI Guilds at their respective companies, and have a lot to say about why bottom-up beats top-down when it comes to AI adoption.

00:00 Intro & The Flowchart Problem01:29 Mike Gets Claude Code Access06:45 Use Cases for Non-Engineers09:30 Market Research & Data Science with AI Agents11:25 Read-Only Database Access: What's Safe?13:00 Two Challenges: Threading & Hallucination15:25 How to Pressure-Test AI Answers17:45 Mermaid Diagrams Explained21:44 Mermaid in Notion23:49 Building an AI Guild at Work28:46 Sub-Agents & Avoiding Hallucination30:23 Wrap Up & What's Next

When AI can build anything, how do you decide what's worth building?

Josh comes back on the show and throws a question at Mike and Joe that every solo dev and indie hacker is quietly wrestling with: is shipping still the goal?

We dig into what "value" actually means when code is free, why building for yourself beats building for the market, and how the shovel factory metaphor exposes the trap most AI-era developers fall into without realizing it. Mike breaks down how real product managers filter signal from noise and pick what to build next. Joe makes the case that what's timeless matters more than what's novel. And Josh gets honest about pausing a product he's been heads-down on — and what that decision actually cost him.

If you've ever vibe-coded three apps in a weekend and felt empty at the end of it, this one's for you.

Topics covered:

• Signal vs noise in product prioritization
• Why passion-first building outperforms market-first building
• The "shovel factory" trap and how to escape it
• What PMs actually do when they score backlog items
• When consulting beats shipping a product
• How to know if your beachhead is real

00:00 Reconnecting After a Break

00:37 Navigating Project Management Challenges

03:05 Defining Value in Product Development

08:23 Signals vs. Noise in Decision Making

18:22 Finding the Right Focus in Fast-Paced Environments

26:12 Building for Passion vs. Others

27:01 Finding Excitement in Projects

28:19 Navigating the Saturated App Market

30:02 The Shovel Factory Metaphor

30:55 The Value of Timeless Solutions

32:19 Identifying Real-World Outcomes

35:23 Consulting as a Viable Path

38:58 The Importance of Use Cases

43:48 Teaching and Sharing Knowledge

In this episode of Build It Faster, hosts Mike and Joe discuss their vision for creating a cohesive body of work from their podcast episodes. They explore the idea of synthesizing content into articles and books, the importance of indexing their discussions, and the potential for monetization through membership and workshops. The conversation emphasizes the need for organization and accessibility of their content, aiming to create a valuable resource for listeners.

00:00 Introduction and Goals

04:58 Exploring the Body of Work

11:22 Synthesis and Content Creation

16:37 Indexing and Organizing Content

33:25 Proof of Concept and Future Directions

Join us as Josh shares his innovative journey in automating development workflows using AI, self-improving systems, and signal processing. Discover how these advancements are transforming project management, code review, and system resilience.00:00 Welcome and Introductions02:51 Josh's Return and Project Updates05:41 Adjusting to AI-Powered Workflows08:25 Self-Improving Systems and Automation11:18 Launching Multiple Products14:10 Defining 'Done' and Community Contributions17:14 Understanding Signals in Development25:50 System Resilience and Recovery27:53 Integrating Voice Control Features29:24 Contextual Understanding in AI31:44 Managing System Capacity and Bandwidth36:30 Testing and Validation of Features40:37 Leveraging External Signals for Improvement44:37 The Future of Agile Development with AI47:15 Collaboration and Team Dynamics in AI Projects

Mike and Joe hosts discuss the rapid evolution of a development project with Josh, who shares insights on emergent behaviors, organizational structures, and the importance of delegation in AI systems. They explore the concept of the Autonomous Virtual Agency (AVA), trust metrics, and the significance of feedback loops in self-improving systems. The conversation also delves into managing prioritization and backlogs, autonomous trace analysis, and the insights gained from using cloud code. Finally, they touch on the challenges faced by mid-level SaaS companies in the current landscape and the excitement of leveraging AI for development.

00:00 Welcome Back: The Excitement of Rapid Development

01:46 Emergent Behavior in Development: Observations and Insights

05:33 Organizational Dynamics: Balancing Development and Operations

11:49 The Role of Delegation in AI Systems

17:18 Signal Processing: Understanding Inputs in Development

22:01 Defining Signals: The Importance of Context in Development

26:40 Tackling Low Hanging Fruit

28:29 Inputs and Outputs: The Core of Life

29:52 Prioritization in Project Management

32:17 Observing and Improving Workflows

34:25 Utilizing Hooks for System Safeguards

37:03 The Importance of Code Quality

37:39 Real-Time System Monitoring

39:34 The Role of the Lead Engineer

43:22 The Squeeze: Navigating Industry Changes

46:43 Exploring Cloud Code Insights

Joe Still and Mike reconnect with Josh Mabry to discuss the evolution of AI and its impact on development practices. They reflect on the journey since their last conversation, exploring the current landscape of technology, the acceleration of AI development, and the importance of building agentic systems. The discussion delves into the economics of AI, the role of consulting, and how empowering teams with knowledge of AI tools can lead to significant productivity gains. The episode concludes with thoughts on the future of work and the collaboration between humans and AI.

00:00 Reconnecting and Reflecting on the Journey

02:54 The Current Landscape of Technology

05:49 The Acceleration of AI Development

09:00 Navigating the Hype and Reality of AI

12:08 Building Agentic Systems and Automation

14:44 The Evolution of Development Practices

17:59 Creating a Self-Improving System

20:52 Integrating Agile Practices with AI

23:44 The Economics of AI and Development

26:29 Consulting and ROI in AI Projects

29:46 Empowering Teams with Agentic Tools

32:39 Future Directions and Closing Thoughts