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The complete operating model I'd bring to a product and engineering organisation: squad structure, every role defined, sprint and release process, DevOps principles, product tiers, AI use cases, and how the whole thing flexes down for smaller headcounts. Twelve documents, written to be used rather than admired.
Stop using AI as autocomplete. Start using it to build systems. Here's the practical, no-shortcuts approach.
The cost of baking observability in from day one is close to zero. The cost of not having it can be measured in missed deadlines, lost revenue, and sleepless nights.
A peer-reviewed study puts numbers to the AI coding debate. The results might surprise the sceptics.
Cutting through the noise on AI-assisted development, for people who need to make decisions about it.
Aviation has spent a century formalising how to handle human error. It is time software engineering caught up.
Moving fast doesn't mean breaking things. It means building the ability to turn them off in seconds.
When production fails, the pressure to find a 'why' often gets in the way of finding a 'how'. Here is how to manage the chaos.
Why your engineering team isn't just 'typing' and why a single misplaced space can bring a platform to its knees.
When building gets cheaper, the finances change completely
AI handles the typing. The hard part was never the typing.
The risks are real. They're also familiar, and manageable.
Your developers are probably already using these tools. The question is whether they're doing it intentionally.
Your developers are probably already using these tools. The question is whether they're doing it intentionally.