Send us a text

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

Serverless Craic from The Serverless Edge
Check out our book The Value Flywheel Effect
Follow us on X @ServerlessEdge
Follow us on LinkedIn
Subscribe on YouTube

Send us a text

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

Serverless Craic from The Serverless Edge
Check out our book The Value Flywheel Effect
Follow us on X @ServerlessEdge
Follow us on LinkedIn
Subscribe on YouTube

Send us a text

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

Serverless Craic from The Serverless Edge
Check out our book The Value Flywheel Effect
Follow us on X @ServerlessEdge
Follow us on LinkedIn
Subscribe on YouTube