Agile Is Not Dead. The Agile Industry Might Be.
I keep hearing it lately: “Agile is dead because of AI.” At conferences, in customer meetings, on LinkedIn. The reasoning is usually the same: If an AI agent builds in two hours what a team used to build in two weeks, why do we still need sprints, standups, and retrospectives?
Why Vaadin Browserless Testing Is a Game Changer for AI Generated Web Applications
AI coding agents write code fast. The bottleneck is no longer typing, it is verification. How fast can the agent find out that the code it just wrote is correct? This is where testing speed and testing architecture suddenly matter more than ever.
The Three Levels of Spec-Driven Development, and Where the AI Unified Process Sits
Spec-driven development is a popular term at the moment. Everybody uses it, and everybody means something slightly different. Birgitta Böckeler from Thoughtworks wrote a helpful article on martinfowler.com where she looked at tools that call themselves spec-driven. Her main finding: spec-driven development is not one thing. There are three levels.
Code Is No Longer the Bottleneck. Requirements Are.
On August 21, 2026, Anthropic published The AI-Native SDLC Playbook. It is worth reading. It describes how the software development lifecycle changes when agents write most of the code. The core message: code is no longer the bottleneck. The bottlenecks now sit to the left and right of the build, in planning, review, testing, and deployment. [...]
A Paper from 1995 Describes How You Should Work with AI Agents
The paper is older than Java. And it answers a question everyone is asking in 2026: Who guards the architecture when AI agents write the code?
From Plan-Build-Run to Specify-Generate-Verify-Operate
For about twenty years, most IT organisations were built around three words: Plan, Build, Run. It was a good model. It gave everyone a place. Plan owned the budget and the roadmap. Build owned the code. Run owned the servers and the pager. With AI agents and spec-driven development, that model no longer fits. What [...]
I hear the same sentence in almost every project I join. “We have a frontend team and a backend team.” Nobody questions it. It is just how software is built today. But this split was never a technical decision. It was a hiring decision. And with AI agents in the loop, the reason behind it [...]
The MCP Server That Leaked a Connection Every Four Minutes
How one underrated Actuator metric explained a recurring OutOfMemoryError in a Spring AI MCP server — and why the default keep-alive setting is the wrong default.
Modernizing Legacy Systems with the AI Unified Process
Most software modernization projects do not fail because of technology. They fail because nobody knows anymore what the old system actually does. The code is there. It runs. It carries the business every day. But the people who wrote it are gone, the documentation is outdated, and the requirements only exist implicitly in the code. [...]
Waterfall Was Never the Problem
Every time I talk about Spec-Driven Development, someone says the same thing. “That is just waterfall.” They mean it as a gotcha. It is not. Two things are going on here. First, most people have never read what Royce actually wrote. Second, even the real waterfall is good in the right place. Let me take [...]
Use-Case 3.0: The Refreshed Guide to Driving Development with Use Cases
Use cases have been around since 1987. In May 2024, Ivar Jacobson, Ian Spence, and Keith de Mendonca published a refreshed guide called Use-Case 3.0. If you read my earlier post on Use-Case 2.0, this is the natural next step. Use-Case 3.0 keeps the same core ideas and adds structure so that use cases fit any [...]
AI Writes the Code. This Book Still Teaches the Use Cases.
In the AI Unified Process (AIUP), the spec sits at the center. The use case is the unit of work. You write a system use case, AI generates the code, and tests confirm the behavior. The use case is the source of truth. The code is a derived artifact. That puts a lot of weight [...]
