The Serverless Edge @ServerlessEdge

Wardley Mapping is powerful — but introducing it badly can kill the idea before it starts. 🗺️ Start with the conversation, not the canvas. Map collaboratively. Focus on user needs. Keep maps visible and evolving. More: linkedin.com/pulse/bringing… #WardleyMapping #TechStrategy

Before you build it: could it become your cloud provider’s next standard feature? Wardley Maps help you spot that shift. Five examples covering AI, serverless and AWS CDK: linkedin.com/pulse/can-ward…

What if your biggest strategic advantage is knowing what not to do? 🗺️ Wardley Mapping helps teams focus on customer value, spot market shifts and cut distractions. A Cloud Guru is a great example of clarity creating scale. Read more 👇 linkedin.com/pulse/unlockin… #WardleyMapping #TechStrategy

The Value Flywheel Effect isn’t about moving faster. It’s about creating momentum in the right direction. ⚡ Explore the 12 tenets that connect purpose, engineering, architecture and long-term value — and help teams turn effort into sustainable progress. 👇 linkedin.com/pulse/12-tenet… #ValueFlywheel #TechStrategy #EngineeringLeadership #SoftwareArchitecture

Wardley Mapping isn’t about creating the perfect map. 🗺️ It’s about finding the one or two things that actually matter. At Map Camp, David Anderson shared how mapping helped connect business and technology strategy, shape a serverless-first approach, and influence the thinking behind The Value Flywheel Effect. The real value? Not the map itself. The conversations, decisions and action it creates. Read more: linkedin.com/pulse/map-camp… #WardleyMapping #TechStrategy #Serverless #ValueFlywheel

Your first Wardley Map will probably be wrong. That’s not a reason to avoid mapping. It’s part of learning how to map. When we first discovered Wardley Mapping, it felt like common sense. Actually creating useful maps was much harder. We over-mapped. We missed users. We worried whether things were in the “right” place. And for a while, we could understand other people’s maps better than we could create our own. The breakthrough came through practice — especially mapping with other people. Because the real value isn’t producing a perfect diagram. It’s the conversation the map creates. In our latest newsletter, we look back at our journey with Wardley Mapping and share what helped us move from confusion to using it as a practical tool for strategy, including: 🗺️ Starting with customer needs 🗺️ Understanding evolution 🗺️ Moving from individual to group mapping 🗺️ Knowing when to simplify 🗺️ Turning maps into decisions and action Wardley Mapping is a key part of The Value Flywheel Effect, but you don’t need to understand everything before you begin. Start small. Map something. Discuss it. Change it. linkedin.com/pulse/began-fo… What was the hardest part of Wardley Mapping for you when you first started? #WardleyMapping #TechStrategy #SoftwareArchitecture #EngineeringLeadership #ValueFlywheel

The best engineering teams aren’t the ones with the most heroes. They’re the ones that don’t need heroes in the first place. We’ve spent years celebrating the engineer who stays up all night fixing the production incident. But real engineering excellence looks very different. It’s about building systems and practices that prevent the incident from happening: → Reliable software → Fast feedback loops → Strong testing and automation → Well-architected systems → Meaningful DORA metrics → Less technical debt → Continuous improvement “Slow is smooth, and smooth is fast.” Investing in quality can feel slower in the short term. But constantly firefighting, fixing preventable problems and accumulating technical debt is far slower. Engineering excellence isn’t about writing more code or shipping more features. It’s about creating an engineering system that can deliver business value reliably, repeatedly and sustainably. We explore what engineering excellence really means — and how organisations can build a problem prevention culture rather than a superhero culture. 🔗 Read the full article: linkedin.com/pulse/engineer… What does engineering excellence look like in your organisation — and how are you measuring it? #EngineeringExcellence #SoftwareEngineering #EngineeringLeadership #DevOps #DORA #SoftwareArchitecture

The code passes every test. The spec is satisfied. And the software still shouldn’t exist. That’s the ceiling of spec-driven development. Specs give AI coding agents guardrails. But guardrails aren’t judgement. They don’t capture the conversations, assumptions, ownership, architectural context or changing evidence behind a decision. As AI makes implementation cheaper, the real risk isn’t bad code. It’s building the wrong thing faster. In our latest article, we explore what needs to sit above the specification — and why trust infrastructure may be the missing layer. 👉 Read: Spec-Driven Development Has Hit Its Ceiling: theserverlessedge.com/spec-driven-de… Can your team still explain why a decision was made six months later? #SoftwareEngineering #AI #SpecDrivenDevelopment #SoftwareArchitecture #EngineeringLeadership

“Code is a liability. The system is the asset.” Long-term value is not created by using AI to ship quickly today and firefighting tomorrow. It comes from building resilient systems, reducing technical debt and embedding engineering excellence from the start. The goal is simple: create more space for innovation — and less need to fix the same problems again. 🔗 Read the latest newsletter: linkedin.com/pulse/long-ter… #ValueFlywheel #EngineeringExcellence #TechnicalDebt #SoftwareArchitecture #TechLeadership

Our podcast has over 5,000 downloads! buzzsprout.com/1908105/achiev…

“What’s the first small step you can take today to add business value?” That’s the heart of Next Best Action, Phase 3 of the Value Flywheel. Don’t wait for the perfect plan. Take action. Get feedback. Adjust. Keep moving. Because strategy only creates value when it becomes action. 🔗 Read the latest newsletter: linkedin.com/pulse/next-bes… #ValueFlywheel #BusinessValue #TechStrategy #Leadership #SoftwareEngineering

“Show me the person who knows it all, and I’ll show you the fool.” That line from a computer science teacher has stayed with us. In technology, nobody has the full picture. Leaders may understand the strategic direction. Architects may see the wider system. But engineers working closest to the technology understand its hidden constraints, dependencies and failure points. That is why Challenge is the second phase of the Value Flywheel. Not challenge for the sake of winning an argument. Not engineers being asked to critique a strategy that has already been decided. And certainly not challenge being used as a weapon. Healthy challenge means creating a safe environment where people can question assumptions, test ideas and improve the direction together. Techniques such as Wardley Mapping, Event Storming and Threat Modelling help because the team challenges the map, model or system — not the individual. When leaders silence challenge, talented engineers disengage. When leaders actively invite it, teams surface risks earlier, make better decisions and create stronger feedback loops. You hired intelligent people. Give them clarity of purpose, put the right guardrails in place — and let them challenge the plan. Read more about Challenge, Phase Two of the Value Flywheel:linkedin.com/pulse/meeting-… How easy is it for engineers to challenge strategy in your organisation? #ValueFlywheel #TechStrategy #EngineeringLeadership

Your purpose is not to write code. Code is the mechanism. Value is the mission. In The Value Flywheel Effect, we explore how organisations can join business and technology strategy through four phases: Clarity of Purpose Challenge Next Best Action Long-Term Value Keep turning the flywheel. Build momentum. Deliver value. linkedin.com/pulse/introduc… #ValueFlywheelEffect #Serverless #EngineeringLeadership #CloudStrategy

Most teams don't have a delivery problem. They have a purpose problem. They're shipping features. Closing tickets. Completing sprints. Hitting deadlines. But ask a simple question: "Why are we building this?" And the room goes quiet. Too many organisations have become experts at building things quickly, without ever stopping to ask whether they're building the right thing. As Melissa Perri calls it, we've fallen into the Build Trap. ⚠️ Build the thing right. ⚠️ Build it quickly. ❌ Forget to build the right thing. That's where cost, complexity and wasted effort multiply. The highest-performing teams we've worked with all share one characteristic: 👉 They have absolute clarity of purpose. They know: ✅ Who their users are ✅ What problem they're solving ✅ What success looks like ✅ Which metrics actually matter When teams understand their North Star, decision-making becomes easier, prioritisation becomes clearer, and experimentation becomes safer. Because you know the game you're playing. As AI accelerates delivery, clarity of purpose becomes even more important. The bottleneck is no longer writing code. The bottleneck is knowing what's worth building in the first place. linkedin.com/pulse/clarity-…

Most engineers think becoming a Cloud Engineer starts with learning AWS, Azure, Google Cloud and AI. They're wrong. The best Cloud Engineers we've worked with could answer one simple question: 👉 "What business outcome are you trying to achieve?" Not: ❌ What service are you deploying? ❌ What framework are you using? ❌ Which certification are you studying for? But: ✅ What KPI are you moving? ✅ How does this create value? ✅ Why does this work matter? Technology changes. Business outcomes don't. That's why the highest-performing cloud teams: • Chase business outcomes, not technical outputs • Build security in from day one • Optimise for flow and throughput • Design systems that fit in their heads • Reduce code where possible • Focus relentlessly on value Cloud engineering isn't about the cloud. It's about solving business problems with technology. That's a very different mindset. What's the most underrated skill for a modern Cloud Engineer in 2026? linkedin.com/pulse/how-beco…

"AI is going to replace software engineers." "AI is just another tool." "AI changes everything." We've heard all three. The truth? Most organisations are still trying to figure out which one is right. Over the last few months, we've explored some of the biggest questions facing technology leaders, architects, engineers, and CTOs: 👉 Will AI eliminate software engineering roles?
👉 Is AI a genuine competitive advantage or rapidly becoming a commodity?
👉 How do you maintain engineering excellence when AI can generate code?
👉 What happens to platform engineering, cloud strategy, and developer experience in an AI-first world?
👉 Which skills become more valuable as AI becomes more capable? No hype. No fear-mongering. Just practical conversations from people building, leading, and modernising software systems every day. We've brought all of our recent AI content together into a single playlist: 🎥 AI, Software Engineering & The Future of Technology Whether you're writing code, designing architectures, leading teams, or setting technology strategy, there's something here for you. 📺 Watch the playlist:
youtube.com/playlist?list=… One question: What is the biggest AI challenge your engineering team is facing right now?

“AI is making specifications a first-class engineering artefact again.” For years, we treated specs as paperwork. Now they're becoming one of the most valuable assets in software engineering. Because AI can generate the code. But it still needs: ✅ clear intent ✅ clear context ✅ clear requirements The teams that win with AI won't be the ones writing the most code. They'll be the ones writing the best specifications. New Serverless CrAIc episode 👇 theserverlessedge.com/spec-driven-de… #AI #SoftwareEngineering #SpecDrivenDevelopment #AIEngineering

“You can’t outsource your critical thinking.” AI accelerates delivery. But judgement, architecture and organisational clarity still matter more than ever. youtube.com/watch?v=dWIng6… #AI #EngineeringLeadership

“If code generation throughput goes up, then all the other stuff becomes even more important.” AI can accelerate software delivery. But it also increases: -cognitive load -coordination challenges -governance pressure -architectural complexity That’s why Team Topologies and socio-technical thinking matter more than ever. New article 👇 theserverlessedge.com/ai-engineering… #AI #PlatformEngineering #SoftwareEngineering #DevOps

AI isn’t just changing software delivery. It’s changing the shape of engineering teams. “The bottleneck is no longer code creation.” Now it’s: -cognitive load -decision making -collaboration -organisational design And that’s why concepts like Team Topologies matter more than ever. Because AI agents don’t remove complexity. They amplify it. The teams that succeed won’t just adopt AI faster. They’ll design better socio-technical systems around it. New Serverless CrAIc episode 👇 youtube.com/watch?v=kquxaS… #AI #TeamTopologies #SoftwareEngineering #EngineeringLeadership #PlatformEngineering