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In this episode of Serverless Craic, Dave Anderson, Mark McCann, and Michael O’Reilly explore Chapter 15 of The Value Flywheel Effect — Map Your Solution. They discuss how Wardley Mapping and tech stack mapping create situational awareness, reduce friction between teams, and guide better architectural decisions.

If you’re a software engineer, architect, or tech leader aiming to evolve your systems with serverless and cloud-native thinking, this conversation shows practical techniques to uncover bottlenecks, reduce technical debt, and align teams on strategic improvements.

⏱️ Chapters

00:00 – Intro: jumping from summer to winter
01:00 – Mapping your solution: why it matters
02:20 – Tech stack mapping in practice
03:50 – Situational awareness and collaboration
05:50 – Funding priorities and bottlenecks
07:20 – Cloud services, serverless options, and evolution paths
09:30 – Custom build vs buy vs adopt cloud-native
11:00 – Organisational insights from mapping
12:00 – Duplication and domain-driven design issues
13:00 – Team Topologies and independent service heuristic
14:20 – Total cost of ownership and well-architected lens
15:50 – Target architecture and business impact
16:50 – Using mapping for strategy and incentives
17:40 – Context switching and leadership effectiveness
18:10 – Takeaways: evolutionary architecture

🔗 Resources

📖 The Value Flywheel Effect Book – https://thevalueflywheeleffect.com

🎥 Wardley Mapping 101 – https://www.youtube.com/watch?v=uP9Rl26Xeag

🎧 Podcast: Wardley Mapping is a Game-Changer – https://open.spotify.com/episode/5cUQgQFBeIkOBWUe35rDRU

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In this episode, Dave Anderson, Mark McCann, and Michael O’Reilly dive deep into The Value Flywheel Effect (Chapter 14) — discussing frictionless developer experience, sense checking, feedback culture, AI in software engineering, DevOps, platform engineering, and marginal gain.

We explore how AI and LLMs are shaping engineering practices, the importance of psychological safety, continuous improvement, and why code is always a liability. If you’re interested in serverless, DevOps, or building resilient modern software teams, this conversation is packed with insights.

Chapters
00:00 – Introduction & Belfast heatwave 🌞
00:18 – Revisiting *The Value Flywheel Effect* (Chapter 14)
01:11 – Sense checking & psychological safety in teams
02:37 – Leadership, listening, and feedback loops
04:12 – RFCs, well-architected reviews & threat modelling
05:14 – Trusting AI feedback vs human feedback
07:59 – Documenting engineering standards for AI
09:33 – Human in the loop & cadence of reviews
11:42 – Traceability, accountability & marginal gains
13:56 – Scaling teams & expanding the “full stack”
14:29 – Infrastructure as code, DevOps origins & AI parallels
17:13 – Deployment pipelines & frictionless production
18:01 – Platform engineering & hardened building blocks
19:40 – Code as liability & avoiding bloat
20:20 – Well-architected standards & AI context
21:32 – Shifting security left & automated governance
22:33 – Isolation, zero trust & resilience
23:18 – Platforms as standards & consolidation
25:23 – Less code, better docs, and evolving patterns
27:06 – Avoiding command & control in engineering culture
28:22 – Empowerment, enabling environments & AI’s role
28:50 – Developer experience & future of AI in software

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In this episode Dave Anderson, Mark McCann, and Michael O’Reilly continue their deep dive tackling Chapter 14: The Frictionless Developer Experience.

The crew explore whether the principles of engineering excellence, developer enablement, and team topologies still stand strong in a world increasingly powered by AI and agentic systems. From **managing cognitive load** to **code as a liability**, they unpack how AI changes (and doesn’t change) the fundamentals of building high-quality software.

📌 Topics include:

Does AI really make development frictionless?
Maintaining engineering excellence in an AI-driven world
Enabling constraints and team autonomy
Revisiting the four team types in *Team Topologies*
The enduring importance of DORA metrics and stability
Why code is a liability—and how AI impacts this
The rise of specifications, contracts, and stronger test practices

⏱ Chapters
00:00 – Intro & recent travels
01:20 – Go To Service Bangalore & serverless momentum
02:40 – Frictionless developer experience in an AI world
04:50 – Cognitive load & enabling constraints
06:20 – Engineering excellence: still relevant?
08:10 – Three characteristics of great software creation
10:25 – Principles, context, and best practices in the AI era
12:40 – Goal-driven frameworks & outcome-based leadership
14:00 – Challenging teams with the right questions
15:35 – AI as an enabler for strong engineers
17:20 – Democratising knowledge & rapid learning
18:40 – Team Topologies in the AI landscape
20:45 – Socio-technical changes & enabling teams
22:15 – Will teams be smaller or just better?
23:30 – Autonomy, mastery, and purpose
25:05 – Engineers’ mastery in the age of AI
26:00 – DORA metrics: throughput & stability
28:00 – Code as a liability & maintainability concerns
29:20 – Specifications, contracts, and test-driven approaches
31:00 – Shared outcomes & embracing AI in delivery

🔗 Resources & Links

📚 Team Topologies: https://teamtopologies.com by Matthew Skelton & Manuel Pais
📖 Accelerate by Nicole Forsgren, Jez Humble & Gene Kim
🌐 The Serverless Edge https://theserverlessedge.com)– Blog & resources

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Serverless myths debunked for modern cloud teams: In this episode, we dive into the second part of Chapter 13 The Serverless First Edge from The Value Flywheel Effect book. We explore common serverless myths, how relevant they still are in 2025, and what’s changed since the early days of serverless adoption.

From cold starts and testing challenges to cloud lock-in and the rise of AI, we reflect on the evolution of the landscape — and the mindset shifts still needed across engineering and leadership teams.

💥 Packed with practical insights and real-world experiences, this is a must-watch for anyone navigating modern cloud architecture, serverless patterns, or leading engineering teams in the age of AI.

⏱ Chapters:

00:00 - Intro & weather chat
00:34 - Chapter 13 overview: "The Serverless First Age"
01:17 - Cold start problems: Still a myth?
05:11 - Serverless is hard to test? Solved with cloud-native testing
09:34 - Observability: You can't see what's happening?
12:48 - Serverless isn’t the next big thing? The AI distraction
16:23 - Vendor lock-in fears & multi-cloud myths
20:00 - “We’re different” & custom standards fallacy
23:02 - Serverless is more expensive?
25:26 - Engineers won’t do what I tell them
26:23 - Engineers are disconnected from the business
27:24 - “This worked last time, let’s use it again”
28:02 - “We only work on the cool stuff”
28:27 - Organisational myths: “We’re under capacity”
29:54 - Security is blocking serverless?
30:41 - Finance myths: OPEX model resistance
30:54 - Sunk cost fallacy in cloud transformation
31:37 - Outsourcing strategy to consultancies
32:47 - Wrap-up & what’s still relevant

🔗 Links & Mentions:
The Value Flywheel Effect book
ServerlessDays Belfast
Talks by Jeremy Daly, Yan Cui , Adrian Cockcroft
BizTech Evolution by Ivan Krnić

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Serverless First: Focus, Not Functionality

In this episode, Dave Anderson, Mark McCann and Michael O’Reilly dive into Chapter 13 of the Value Flywheel Effect—focusing on the concept of “Serverless First” and what it really means for engineering teams and product leaders today.

🔍 Topics include:
Why code is a liability and how to identify what to build—and more importantly, what not to.
Embracing a frictionless developer experience to enable speed and innovation.
The shift from legacy cloud to modern cloud and the pitfalls of lift-and-shift thinking.
Understanding core vs. supporting domains through DDD and how that informs what to offload.
The enduring value of good architecture*and how modern cloud constraints can be enabling.
A powerful reminder that the point of serverless isn’t tech—it’s focus.

🚀 Whether you're navigating cloud migration, modernising your stack, or wondering how to leverage AI without drowning in infrastructure, this conversation will help you elevate your thinking.

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🎙️ Serverless Craic: Chapter 12 – The Workgrid Case Study

In this episode, Dave Anderson, Mark McCann, and Michael O’Reilly dive deep into Chapter 12 of The Value Flywheel Effect — the Workgrid case study.

This episode explores the early days of Workgrid, a startup founded in 2017 with Gillian McCann. As one of the first companies to adopt a “serverless-first” philosophy, Workgrid’s journey offers valuable lessons in building modern digital employee experiences under real-world startup constraints.

💡 Topics Covered:
The importance of a pragmatic, serverless-first architecture
Managed services vs. infrastructure-heavy approaches
Startup pressures: speed, cost, and time to market
Creating an “environment for success” in engineering teams
Real-world examples of modular design, cost awareness, and evolving architectures
Building secure, compliant, multi-tenant SaaS on serverless
The value of partnering with cloud providers like AWS
Lessons in team growth, hiring for mindset over tech stack

🔥 Quote of the episode:
"I never said serverless was easier. I said it was better." – Gillian McCann

Whether you’re in a startup or enterprise, this episode will inspire you to rethink your architectural strategy and team dynamics for building scalable, cost-effective cloud-native systems.

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Mapping Your Org Capability | Chapter 11 Breakdown of The Value Flywheel Effect

In this episode, Dave Anderson, Mark McCann, and Michael O’Reilly dive into Chapter 11 of The Value Flywheel Effect — "Map Your Organisational Capability".

We unpack how to use mapping techniques, such as Wardley Mapping, to assess and visualise your organisation’s capabilities across areas like security, cloud-native development, and emerging tech like GenAI. The discussion covers:

🔹 Why individual expertise ≠ organisational capability
🔹 Mapping techniques using industry standards and evolutionary stages
🔹 How to use mapping for strategic clarity and identifying capability gaps
🔹 Lessons from applying security and cloud-native capability maps in real organisations
🔹 Using mapping as a lightweight but powerful tool for technology leadership and investment planning

This episode is full of practical insights for tech leaders seeking clarity, situational awareness, and better strategic decisions.

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🎙️ Serverless Craic: Exploring Socio-Technical Systems for Change

Welcome back to Serverless Craic! In this episode, the team dives into Chapter 10: Challenge – A Socio-Technical System for Change from the book, The Value Flywheel Effect. This thought-provoking conversation unpacks how organisations can effectively bridge the gap between people and technology to foster meaningful, sustainable change.

🔍 Topics Covered:

What makes socio-technical change so difficult
The importance of flow, team design, and time to value
Lessons from Team Topologies and Drive by Daniel Pink
Frameworks like Cynefin and Wardley Mapping
Democratising AI and enabling change through feedback loops
Why architecture alone won't save you

🤔 Whether you're a tech leader, architect, or engineer, this episode offers valuable insights on how to navigate complexity, decentralise expertise, and embed purpose and autonomy at every level of your organisation.

📚 Referenced:

Team Topologies
Drive by Daniel Pink:
Cynefin Framework (Dave Snowden)
Wardley Mapping
Fred Emery’s Design Principles

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