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Thinking on AI engineering, architecture, and what it takes to deliver at the frontier.
What AI-Augmented Development Demands from Your Organisation
The cost of producing working code has been falling for years, and AI coding tools have accelerated that trend dramatically. We do not yet know where the floor is. A single developer, assisted by AI agent(s), can now produce in hours what once took a team days. Multiple agents working in parallel can generate volumes of code that would have been unthinkable just two years ago. And yet, producing more code faster has not automatically translated into delivering better software or business value. What we are seeing instead is that organisations with existing structural weaknesses keep wondering why they cannot harvest those productivity gains. That tells us something important about what AI actually improves, and what it does not.
Helping Build Healthy Software Organizations: Flow, Metrics, and Developer Experience at Datawise.ai
Over the past decade, the software industry has learned a hard truth: you can have excellent engineers, modern cloud infrastructure, and the latest frameworks, and still struggle to deliver meaningful change quickly. What separates consistently high‑performing organizations from the rest is not a specific technology choice, but how teams, architecture, and workflows are designed to support a consistent and predictable rate of change.
The Elite Software Engineer: Lessons in Managing Complexity
The journey to becoming a great software developer has never been easy, not even in the age of AI assistance. While large language models can autocomplete code or summarize documentation, they can’t eliminate the real challenge: learning how to manage complexity.
(BU) intelligence before AI
From BI and UI all the way to AI. A roadmap for building an AI-first company. How to build solid foundations without blowing up the costs and making the best use of your engineering resources.