- ↗Knowing when not to answer
Most leaders default to jumping in. Here's a three-question framework for deciding whether you should
- ↗FontCrafter: Create Your Handwriting Font for Free
- ↗Why some people ask 'why not both?' while others ask 'what matters most? Nothing but Noise
- Seven Steps to Solving the Right Problem
Seven steps to solving the right problem. The framework by Charles Conn and Robert McLean.
- From Doing to Building
The higher you get, the more your value shifts from ticking off tasks to building systems.
- ↗5 Ways I’m Using AI As An Engineering Manager
- Agile vs. Waterfall
Clients don't care about methodology. They care about results.
- Write It Down
If it isn't written down, it didn't happen.
- ↗Maximizers vs. Focusers
The most productive tension in product teams is not between engineering and design. It’s between maximizers and focusers.
Maximizers lean toward speed, optionality, parallel bets. Focusers toward depth, coherence, doing less for more.
Neither is right. Both create value and risk.
This explains why some conflicts feel unresolvable. A maximizer sees a focuser killing momentum. A focuser sees a maximizer burning trust for short-term gain. Different languages for what “good” means.
I am a maximizer. My instinct is “why not both?” Parallel bets surface opportunities you miss with pure focus. But maximising without constraint creates shallow progress everywhere and deep progress nowhere. The art is in knowing when to switch.
- ↗Why initiative matters more than intelligence Maximizers vs. Focusers
- ↗High Agency Matters
The smartest person in the room is not always the most valuable. The person who actually does something is.
High agency is the belief that you can act, combined with the will to follow through. Seeing a problem and deciding: I’ll solve this. Without waiting for instructions, without asking permission for every detail.
Intelligence without action is potential energy that never converts to movement. You can be brilliant and achieve nothing. You can be averagely intelligent and get an enormous amount done.
Why is agency so rare? We have spent decades optimising for compliance. Schools reward correct answers to set questions, not the asking of interesting questions. Companies bought obedience by the kilo. Follow the process, do what you’re told, don’t deviate.
That trained agency out.
The people who get ahead are the ones who train it back in. Who choose bias toward action over analysis. Who ship and then improve instead of planning endlessly.
- ↗Simon Willison on the professional practice of AI-assisted software engineering High Agency Matters
- MoSCoW: Prioritisation That Works
Not everything can be urgent. Four categories force honest conversations about what matters.
- ↗Vibe engineering
There is a difference between prompting until something works and engineering with AI assistance.
The first is hacking. You try things until they work, copy code you don’t understand, and hope it keeps working. That’s fine for experiments and prototypes. It’s not how you build production software.
The second is what Willison calls “vibe engineering.” You use AI as a tool, but the engineering fundamentals remain. Writing tests. Reviewing code. Understanding what you ship. Taking responsibility for the result.
The irony: AI tools make engineering fundamentals more important, not less. If you can generate code faster, the bottleneck becomes validating that code. And validating requires understanding.
Engineers who know their craft get leverage from AI. They can do more, faster. Engineers who rely only on AI without the fundamentals build houses of cards.
- ↗A personal perspective on what talent really means in organisations Vibe engineering
- ↗Why treating AI as a code generator misses the point Talent is Alignment
- ↗The AI Coding Trap
AI coding tools promise 10x speed. What they often deliver is 10x more code to understand and maintain.
The trap is not in the AI. It’s in how we use it. If you treat AI as a code generator that produces output, you get exactly that: more output. More files, more functions, more lines. But more code is not the same as better software.
The problem shifts. Instead of writing code, you are now reviewing code. Code you didn’t write yourself, following patterns you didn’t choose, making assumptions you didn’t validate.
The paradox: the faster you generate code, the more time you spend understanding what was generated.
What works is using AI as a thinking partner, not a typist. Let it reason about architecture, edge cases, alternative approaches. The value is in the dialogue, not the output.
- ↗Simon Sinek on the difference between managers and leaders The AI Coding Trap
- ↗5 Things Managers Do That Leaders Never Would
The difference between managing and leading shows up under pressure.
Managers retreat into control mode. More rules, more checkpoints, more reporting. It feels productive but signals distrust.
Leaders step into trust mode. They explain the situation, ask for input, and give people room to act. It feels vulnerable but builds ownership.
The sharpest contrast: information. Managers treat details as a tool for power. The less others know, the more dependent they are. Leaders do the opposite. They share everything relevant and trust people to handle it well.
What it really comes down to is discomfort. Difficult conversations, bad news, conflicts. Managers avoid them or wrap them in processes. Leaders lean into them, directly but with care. “This is hard, but I care about you, so let’s talk.”
The bottom line: don’t avoid the hard things.