Author: Roger

I did:

Go time

We’re four weeks from an important deadline so everyone is flat out and we’re starting to figure out which work isn’t going live on time and what that means for our numbers. I love this kind of pressure. Did this stuff too.

• Planned onboarding for a new product manager joining us next week.
• Interviewed some very talented product managers.
• Talked about task completion as the unit of analysis for our north star metric.
• Chatted about playbooks, what that looks like with AI (writing evals and prompts rather than specific plays).
• Had some really good coaching sessions.
• Booked my ticket for Product for the People.
• Got cited in “Bridging theory and practice – implementation insights on artificial intelligence in health care”.

I read:

Experiment-Driven Product Development

Started reading Paul Rissen’s book about using an experimental approach to develop products. It sets out a framework for asking questions and getting answers in a structured way.

We took away psychological safety and then told everyone to be more productive

“What needs to change is the fundamental assumption that people are resources to be optimized rather than humans who require certain conditions to do their best work.”

Via Stéphanie Walters.

The Builder’s Job Is Not to Build: A Mindset for Better Outcomes

Interesting talk about being outcome-focused.

Via Debbie Blanchard.

How to deliver digital transformation in public services

Seven lessons:

• Anchor the programme in a clear, shared vision of the outcomes you want to achieve.
• Show leadership: take accountability and own risks and decisions.
• Cultivate the right mix of skills and collaborative ways of working.
• Build a picture of who your users are and what they need.
• Get your scoping right: work out where to start, what to prioritise and what to exclude.
• Prioritise the needs that are most critical to achieving your vision.
• Get to grips with the commercial environment and different delivery and funding models

Via Rob Cawston.

The strategic product designer

Nice collection of resources.

I thought:

Compounding improvements

Once we’ve finished a piece of work, the board we used to manage the work just gets abandoned or archived. We don’t analyse it and turn it into a template for future work. That seems like a lost opportunity for continuous, compounding improvement.

Hand-offs

We all know how bad hand-offs are, but maybe we don’t recognise just how bad. Knowledge loss is mostly invisible until something goes wrong because of it so it’s easy for no one to realise the scale at which it’s happening.

But practically speaking, it’s impossible to keep the same people working together on the same thing all the time, and documentation never captures the tacit knowledge that we create for ourselves.

Is knowledge loss just part of organisational life, part of the entropy of modern knowledge work?

I did:

Heatwave

The second order effects of things like heatwaves always fascinate me. In-person sessions cancelled, schools closed, more people on leave, people not feeling their best, more stress, maybe different decisions get made than would have in other circumstances. Anyway, this is some of the stuff I did during the heatwave:

• Did a training course in AI product strategy. We used AI as a tool to consider how changes in the AI market affects AI in our products.
• Set up a spreadsheet for doing Bayesian analysis on product outcomes. It needs more work but there’s definitely something useful in being able to express uncertain outcomes as probabilities.
• Chatted about Total Quality Management and where it could be useful for us.
• Created a little agent for answering questions about some work we’re doing.
• Me and three other product managers pitched our ideas to a group of stakeholders and got lots of good feedback.
• Presented my thinking on the future direction for one of our big products.

I read:

How LLMs affect business

Interesting post from the CEO of Buttondown about customers having used LLMs to research their product and what that does to support needs, lifetime value, etc. It’s an important consideration for every organisation. When customers come to you having already established an understanding about your business that you haven’t had much control over, it changes the nature of the relationship. This is AI as an intermediary.

The right it

Stumbled across Alberto Savoia whilst wandering around YouTube so bought his book. Despite calling Howard the Duck a failure, he has some good advice about collecting data to validate new ideas.

Bottleneck theatre

“Imagine the “bottleneck” really was engineering or coding. What does that imply about the competitive game you were playing? Are you saying the only thing holding you back was something relatively commoditized—something you could just hire more people to do? What does that say? It suggests you were competing in a world where speed of execution mattered more than insight, where everyone was building roughly the same thing, and whoever shipped faster won. But if that’s true, you better hope engineering wasn’t your bottleneck. Because if it was, and AI removes that constraint for everyone, your competitors will take you to the cleaners.”

I mean, no one ever really believed that organisations actually only have one bottleneck stopping them from suddenly being more successful, right? In many cases, the way the organisational structure is set up to operate is the actual bottleneck, and AI can’t fix that.

So a lot of this is just AI theatre. And when we talk about theatre we’re talking about the suspension of disbelief, which is to say, everyone knows it’s not real but everyone goes along with pretending it is. AI can’t fix that human trait either.

I thought:

Changing sociotechnical systems

There’s a pacing layers thing going on where technology can be changed quite quickly, changing tasks is slightly slower, structural changes happen more slowly still and people changes can be really slow. So there’s an uneven distribution of benefits of the change.

Spirals, not circles

So many diagrams explaining methods like Theory of Constraints, Agile, Scrum, etc., are circles. I get the simplicity but I think it’s too easy to interpret as repetitively going through the same process again and again but not really getting anywhere. I think spirals might explain the process better. The work flows through the same steps but each time it is more refined and closer to the target in the middle of the spiral.