How do you actually work with AI coding tools in production? From breaking down features into AI-friendly tasks? How to choose between agents vs. manual prompting? How to writing code that LLMs understand better?  Where do spec-driven workflows fit in?


0:00 - Introduction
1:09 - What's the WORST thing you can do when adopting AI?
4:44 - Experimentation vs. Following Old Mental Models
7:06 - Working at Feature Level: Breaking Down AI Tasks
10:10 - Cheesy's Workflow: Brainstorming, Stride, and Task Management
13:45 - Phil's Approach: Staying in Flow State vs. Using Agents
16:01 - The Death of Prompts: Plugins and Tools Take Over
18:11 - Context Engineering vs. Prompt Engineering
21:00 - Context Window Size: Bigger Isn't Always Better
23:48 - Spec-Driven Development → Task Management Tools
25:22 - Model Wars: Anthropic vs. Open Source (Qwen, DeepSeek)
30:00 - Should You Short Anthropic Stock? (Philosophical Discussion)
33:00 - Why Claude Code Still Leads Despite Model Convergence
35:01 - Hardware Costs and the Future of AI Accessibility
38:11 - Does Boilerplate Death Change Architecture?
42:00 - When Should You Care About Code Organization with AI?
45:26 - Writing Code FOR LLMs: Semantic JavaScript and Context
47:49 - Wrap Up: Future Topics on LLM-Friendly Code

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The team debates AI development workflows, introduces Stride (a multi-agent requirements system), and discusses whether programming languages and software engineering principles still matter when AI writes most of your code. They explore how product management is transforming as iteration costs plummet and MVPs now take hours instead of weeks.

• Ancillary AI Development Tools - Tools built on AI models like OpenSpec, SpecKit, and Kiro.dev that help with planning and design before coding
• Planning vs. Direct Implementation - Debate on whether extensive planning (BDD/Given-When-Then) is needed or if iterative development with AI works better
• Stride Requirements System - Cheesy's Kanban-based tool that manages multi-agent workflows, prevents merge conflicts, and matches tasks to agent capabilities
• Does Programming Language Matter? - Whether language choice still matters when AI generates code, and if developers will let AI select languages based on accuracy
• Product Management Transformation - How PM roles are shifting from managing backlogs to rapid prototyping with drastically reduced iteration costs
• Code Review and AI Trust - Evolution from reviewing every AI-generated line to relying on automated checks as confidence increases
• Software Engineering Principles - Whether core principles (DRY, SOLID, clean code) remain important - consensus is yes, they help AI work more effectively

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What does the future of software development look like when AI is writing most of the code? We dive deep into how AI is fundamentally changing team dynamics, agile methodologies, and the roles we've held sacred in software engineering. We break down why humans are now the real bottleneck, how to build trust with AI-generated code, and what your development workflow should actually look like right now.

Sections & Timestamps

00:00 - Intro

0:06 - The Two Pizza Team: Still Relevant?

1:36 - Where Agile Breaks Down with AI

3:18 - Rethinking Team Structure in an AI-First World

5:06 - Can We Keep the Roles? Should We?

6:50 - From Developers to Agents: The Shift in Thinking

8:00 - Code Review is Your New Bottleneck

10:15 - The Beads Project: Never Looking at Your Own Code

12:14 - Why Companies Keep Forcing AI Into Old Processes

14:00 - Humans Are the Bottleneck Now (the Big Insight)

16:00 - How to Convince Skeptical Engineers to Trust AI Code

18:30 - Start Small, Build Confidence Over Time

21:50 - Why Brownfield Projects Are Actually AI's Sweet Spot

25:30 - Managing Context Windows and Problem Decomposition

28:00 - The Hard Problem: Testing Non-Deterministic Agents

31:50 - What We're Actually Using Right Now (Tool Rundown)

32:20 - The Rise of AI UX and Task Formatting

34:00 - Tidewave, Claude Code, and Cloud Skills

36:00 - Closing Thoughts & See You Next Time

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Is the Agile Manifesto obsolete in the age of AI? Is a complete rethinking of software development required? From agile overhead  to evolving roles and responsibilities of development teams, we'll unpack it all. 

0:00 - Introduction 
1:30 - Agile Methodologies and AI 
6:00 - Overhead and Productivity
10:30 - Agile Manifesto
15:00 - Testing and Documentation 
18:00 - Team Structures and Collaboration 
22:00 - Product Management and Customer Interaction 
30:00 - Impediments to Adoption 
37:00 - Insights and Takeaways 
42:00 - Conclusion and Decision

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NEW POD! Zarar and Csaba discuss examine the findings of the 2024 DevOps Research and Assessment Report (DORA) and the impact of AI on continuous delivery 

00:00 - Intro

02:15 - The Big Question: Does AI Speed Up Production Deployments?

04:30 - The DORA Report Shocker: AI's Surprising Impact

07:45 - Where AI Actually Shines: Documentation Over Deployment

11:20 - The Dangerous Trap of AI-Generated Tests

15:10 - Smart AI Usage: Boilerplate vs. Business Logic

18:00 - Junior Developers in Crisis: The Experience Gap Widens

22:30 - The Abstraction Debate: Are We Losing Essential Skills?

26:45 - The Death of Refactoring Tools

29:15 - Product Performance Paradox: More Tools, Same Results

32:00 - The Hockey Stick Prediction: DORA's Optimistic Future

34:30 - The Big Question: AI Addiction and Pricing Reality

36:45 - The Open Source Response: Will History Repeat?

39:20 - Local AI Revolution: Running ChatGPT on Your Laptop

42:10 - The Toilsome Work Mystery: Why AI Isn't Solving Burnout

https://www.youtube.com/watch?v=jZZtG6LLhq4

#continuousdeliverypodcast #agile #dorametrics #dora

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Kanban guru, Fernando Cuenca joins the podcast alongside Jeff "Cheezy" Morgan and Csaba Bereczki to discuss Kanban. Hosted by Zarar Siddiqi.

00:00 🚦 Introducing Kanban: Why Your Scrum Teams Are Stuck

Learn why traditional sprint methodologies might be holding your team back and how Kanban can unlock better workflow

04:32 🔍 The Kanban Lens: Understanding Your Current Process

Discover how Kanban isn't about switching processes, but about gaining insights into your existing workflow and identifying improvement opportunities

11:45 🤝 Tackling Organizational Dependencies Like a Pro

Master strategies for managing complex dependencies in large organizations and keep your team's productivity flowing

18:20 💡 Work Item Types: Not All Tasks Are Created Equal

Unlock the secret to creating more meaningful work categories that actually make sense to your customers

24:15 📋 Crafting Powerful Team Policies for Maximum Autonomy

Learn how clearly defined policies can surprisingly give your team MORE freedom, not less

30:40 🧩 WIP Limits: The Game-Changing Productivity Hack

Understand how work-in-progress limits can transform your team's efficiency and speed of delivery

36:50 🚀 From Scrum to Continuous Flow: The Kanban Evolution

Explore how high-performing teams are moving beyond rigid sprint boundaries to a more flexible, value-driven approach

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Brad Smith, author of "DevOps for the Desperate" and Sr. Director of Engineering at Varo Bank, formerly a Sr. Engineering Manager at Amazon, joins the podcast to discuss:

00:00 Intro
00:30 Minimizing productivity dips when onboarding
11:45 Simplification through reduction in cognitive load
14:15 Lightweight Architectural Decision Records
18:45 Need for SRE? How we got from DevOps to SRE
27:10 Scaling startup infrastructure efficiently
41:30 Zarar’s crazy story about his old boss 
42:53 Viability of one-stack frameworks like Elixir LiveView and OneStack
49:50 Where does AI fit in current and future development workflows? 

Book link: https://www.amazon.ca/DevOps-Desperate-Hands-Survival-Guide/dp/1718502486/

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Digital accessibility leader, Patrick Dunphy, joins Zarar Siddiqi and Csaba Bereczski on the podcast to discuss:

- How to Shift Left on Accessibility
- Why accessibility is a mark of a quality product
- What developers need to known about accessibility
- How does shift left work with accessibility
- Models to structure teams so that they produce accessible products
- Are Ontario accessibility guidelines too onerous?
- Big Tech / operating systems handing accessibilities, which companies are getting it right
- Much more...

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John Ousterhout, author of the influential book A Philosophy of Software Design, joins the podcast. The book is:

https://www.goodreads.com/book/show/39996759-a-philosophy-of-software-design

Topics include:

- What does software complexity look like?
- How do we identify complexity before it develops?
- The importance of continuous refactoring
- What the education system gets wrong about teaching software complexity
- How John teaches Computer Science at Stanford
- What John thinks of agile
- Balancing tactical and strategic programming, what TDD gets wrong

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Topics include:

- What does software complexity look like?
- How do we identify complexity before it develops?
- The importance of continuous refactoring
- What the education system gets wrong about teaching software complexity
- How John teaches Computer Science at Stanford
- What John thinks of agile
- Balancing tactical and strategic programming, what TDD gets wrong

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Apple Podcasts: https://apple.co/4bNrAJK
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Tom Howlett, Head of Product Management at Sonar is our guest today. Sonar is the leader in helping engineers write clean code through continuous feedback during the development process, and is trusted by millions of developers worldwide.

We talk about:

- The idea of "Start Left" and how it ties into "Shift Left"
- Gen AI in developer workflows and how it promotes TDD
- How does Sonar empower development teams? What's the role of the PM?
- What constitutes a bad test?
- Will static code analysis ever eliminate the need for pen testing?
- How can static code analysis catch bugs across integration boundaries?
- What does a team at Sonar look like?
- Is there a QA or BA role at Sonar?
- What makes Sonar a great place to work

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