Weeknotes 387

This week I did:

Riskiest assumption testing

I spent some time defining an MVP to help us validate our two riskiest assumptions; can we get the right audience to the product (acquisition), and can we get people to the outcome they are looking for (result, the other ‘R’ I added to the pirate metrics). The first is fairly easy to validate for one of our two potential audiences, so that’s something I’ll work on next week.

100 days of task tracking

Analysed and wrote up what I’ve learned from tracking my tasks for 100 days. I think the most useful things I learned was how ineffective goal-setting is, how the time available affects achieving goals, and that having the data about what I actually did is better than not having it.


I started writing about some of the things I’ve learned this year but realised that it might be taken the wrong way if someone didn’t have an open working, reflective approach. So, instead I think I’ll look back over my weeknotes and summarise some of the things I did, read and thought about.

I read/watched/listened to:

System dynamics

This lecture by Donella Meadows, the godmother of systems thinking, is amazing.

The year of AI

Apart from the other seventy six years of work that went into the field of artificial intelligence, 2023 was the year that one, very narrow, type of AI that got a lot of attention.

The essence of product management

Probably the best product management podcast of the year, this episode of Lenny’s podcast with Christian Idiodi gives a really clear explanation of what product management is and how product managers figure out how to validate solutions.


This list of canvases is great. It makes me think of a product to help people pick the right visual working tool depending on what they are trying to achieve.


Still reading Better Value Sooner Safer Happier. I’ve moved from reading slowly and thinking about it to reading quickly and skipping over parts. It is quite possibly the worst written book with the most impactful ideas.

I thought about:

Product management maturity models

None of the product management maturity models seem to be based on research and, given the websites they are on, are just lead gen content, which is a shame. So, if “all maps are wrong but some are useful”, then “all maturity models are wrong and most are misleading”. The question then is, could a maturity model for product management be useful? I tend to think not, that an improvement kata approach that allows course correction depending on the context would be better, but I’m interested to see if I can prove myself wrong.


I’ve done better this week at using my daynotes to record what I’m thinking about. Mostly it’s been about how to explain the effects of high levels of work in progress.