Author: Roger

I did:

Conjecture

Three day week so very busy having lots of conversations about all the new work we’re doing. I love this phase of product work. It’s high energy, high ambiguity, and high fidelity guessing, which is why ‘conjecture’ is my word of the week. Also did this:

• Chatted to product managers about defining outcomes and scoping work to match. It’s been a opportunity for some good product thinking about how to set scope that is deliverable by the deadline but still achieves an outcome.
• Technical proof-of-concept for bringing user behaviour data from websites into our marketing automation platform.
• Thought about ways of building consensus and support for a new product and decided using an existing product to seed usage has a good chance of success.
• Talked about three ways to use data in product work: new opportunities for product development, operational reporting and evaluation, strategic performance analysis.

I read:

Platform Product Management

Nikhil Shrivastava says, “The modern platform PM is no longer responsible only for APIs, SDKs, documentation, and developer experience. Those still matter. But in many commercial platforms, the PM is also designing business systems, operational workflows, monetization architecture, ecosystem incentives, compliance boundaries, and multi-persona product journeys.” I completely agree. Platforms are becoming the cool products, and working on just the technical stuff isn’t enough for platform product managers any more.

Vibe coding is obsolete, product management isn’t

Jeff Gothelf talks about how what Andrej Karpathy, research scientist and founding member of OpenAI, said about agentic engineering is actually just product management. I suppose some of that is true, but only about product management as it is now, not as it will be in the future. It’s a little embarrassing that engineering is changing so quickly and us product people are still hanging on to a soon-to-be out of date idea about what we do.

Seven Myths about AI and Productivity

Fascinating article by Dritjon Gruda and Brad Aeon about the productivity and economic benefits of AI. The conclusion is that its different for different organisations in different situations.

I thought:

Started vs. Finished

What does the number of pieces of work started versus the number finished say about an organisation?

	High finish rate	Low finish rate
High start rate	+: Lots of work gets done. -: Lacks discernment, nothing gets stopped.	+: Good agile decision-making. -: Starting work that never gets finished is wasteful.
Low start rate	X	+: Maximum ROI, not much waste. -: Not getting enough done.

Organisational taxonomies

What organisations call things, what those things mean, who gets to define them, will be increasingly important as AI becomes part of organisational operating systems. AI will need those things clearly defined to treat them consistently.

Opportunity cost is a killer

I’m doing this but could I be doing that instead, or that other thing, or doing more analysis to find things I don’t even know that I could be doing yet.

Judgement is king

“Use AI at the speed of judgement” is the new “ship only as fast as you can learn”.

I did:

Move fast and brake things

This week was a lot about quickly figuring out what to stop. Or why that work started and whether it’s right to carry on. That involves lots of talking to people, getting different perspectives, looking at data, considering end-to-end, and making decisions about whether to speed up or slow down. Did this stuff too:

• Presented new opportunities to stakeholders, all of which they approved thanks to the solid thinking our product managers did.
• Talked about doing cohort-based reporting so we can see the difference between users who are successfully completing their enrolment and those that aren’t.
• Worked on a marginal gains strategy. There’s lots of thinking to do that will help us focus on the right things in the right way as returns diminish.
• Avoided a sabotage moment.
• Started planning the next six months of roll-out for one of our products.
• Used Microsoft Planner to organise some work. It’s changed a lot so I might have to update my guide.
• Did some interviews for a senior product manager role.

I read:

Rhizomes FTW

I love rhizomes. It’s my go-to mental model for organising without a centre, so it was great to read two things this week about rhizomes. Rachel Wood exploring rhizomatic service design, thinking about services as non-linear, interconnected, adaptive ecosystems that are constantly evolving. And Steve Messer shared some links to interesting thinking about rhizomes.

Continuous Discovery Habits That Actually Work

Listened to Melissa Perri’s round out of continuous discovery habits. Made me realise how much I miss the pace continuous-x work, but also how it’s only appropriate in certain circumstances.

Product strategy

Watched Ant Murphy’s talk about product strategy, which was cool and all, but like so many talks/posts/articles about product strategy, talk about what it is rather than how to do it. I don’t think I’ve ever seen anyone explain how they created a product strategy. It’s both strange and understandable at the same time. Strange because of how much a product manager’s job is about product strategy, and understandable because strategy is an ongoing emergent thing that is difficult to explain.

I thought:

Moving the goal posts

The problem with the metaphor is that in sports the goalposts don’t move, and so moving them is considered unfair. In business, the goalposts move all time and that’s a good thing.

The difference between wrong and getting righter

Ignore the grammar, it was never my strong suit, but I was thinking quite a bit this week about the difference between unitarist, binary, right/wrong thinking and the idea there is an end state to be reached; and pluralistic, more or less right thinking that recognises constant change as the norm. These co-exist but they feel mutually exclusive. You can’t have both and not have them conflict each other because they see the world in completely different ways. And there doesn’t seem to be any way to reconcile that conflict without changing people’s entire paradigm. It’s an interesting meta-problem.

MOPEDD teams 🛵

We’re experimenting with hexagonal teams (which is obviously twice as good as a trio). These teams that have six roles; marketing, ops, product, engineering, design and delivery. Putting people together is easy. Helping them reach a shared understanding is going to be the hard bit, so I’ve been pondering the different concepts and perspectives each role brings and how they might fit together. Maybe marketers think about audiences and campaigns, whereas maybe designers think about users and journeys. Where is the overlap in these concepts that helps create common ground and shared understanding?

I did:

HSLD

Universities have an annual cycle of students enrolling, starting studying, completing their first assignment, etc. It’s a cadence that drives everything else that happens. It gives us product people focus but means if we don’t ship in time, our work isn’t going to have impact for a whole other year. This week has mostly been about:

• Discussed service-level KPI’s, including switching our thinking from funnels to cohorts. I’d like to mock-up a dashboard to help me get my head around it but I doubt I’ll get time. Luckily, we’ve got fantastic data analysts who do a much better job than I would.
• Reviewed a whole bunch of new features as part of a fixed scope piece of work. Sometimes I think we’ve been convinced that agile is the only way to do things right, but it’s just not true. Right tool for the job.
• Pushed a couple of ideas forward through technical feasibility analysis that have been suffering from a flow efficiency problem (small pieces of work with lots of time in between them).
• Kicked off some new work with a new way of working for product managers. It’s going to be a challenge to do quickly but it’s an interesting part of repositioning product managers as responsible for outcomes (changing user behaviours in ways that get business results).
• Enjoyed a coaching session talking about outcomes.

I read:

Webinars

Watched Jeff and Josh’s webinar on prompting AI for outcomes using their ‘who does what by how much’ template to generate ideas for achieving that outcome. And I watched four four’s webinar on using AI to organise and analyse customer feedback.

You can’t fake belonging

“The best organizations don’t just give you a paycheck. They give you a shared language, a sense of purpose, a reason to show up that transcends the specific task in front of you. That is not a recruitment tagline. That is, increasingly, a documented competitive advantage, and it is built, or destroyed, one interaction at a time.” Interesting points about the effect a sense of belonging has personal and organisational performance.

Shipped Isn’t Solved

“…speed is an amplifier, not a strategy. It amplifies whatever you point it at. If you point it at a deeply understood customer problem with thoughtful design, you get to a better product faster. If you point it at a half-understood problem with no design thinking, you get to the wrong answer faster.” Arguing that adoption is the biggest constraint, which I agree with, and that’s why product managers care about time-to-value, not time-to-delivery.

No rules rules

Trying to get back into using my Kindle for reading so I bought Reed Hastings and Erin Meyer‘s No Rules Rules. It’s about how “Hastings rejected the conventional wisdom under which other companies operate and defied tradition to instead build a culture focused on freedom and responsibility, one that has allowed Netflix to adapt and innovate as the needs of its members and the world have simultaneously transformed.” The implication is that organisational culture positively correlates with business success, which is impossibly hard to prove.

I thought:

Shots on goal

One of the problems with product managers working on the same product for a long time is that it often means they don’t get to build up the experience of dealing with different problems. I think, the more shots you take, the more you goals you hit, and the better judgment you develop from the experience of winning and losing. Maybe the measure of product managers is how many how shots on goal they have.

Decisions in the garbage can

It’s an unfortunate metaphor because it suggests everything in it is rubbish and that’s just not the case, but the garbage can model is a really useful for thinking about how decision-making works in organisations like universities.

In the garbage can, decisions take a long time to be made, involve lots of people with lots of different perspectives, they change as they are being made, and they don’t always stay made.

At first glance, that seems like an ineffective way to make decisions, and the obvious way to improve it seems like it would be to add structure, process, documentation. But garbage cans resist that. The only way to make decision-making work in the garbage can is through relationships, discussion, influence, negotiation.

Jonah Berger, in his book Contagious, says ideas move through people and culture in predictable patterns. They spread like social viruses through networks, relying on human psychology, social dynamics, and the environment. Decisions are the same. Decision-making in the garbage can relies on having a mental model for how things work in the garbage can that closely matches reality.

What if bottlenecks are release valves?

Not quite sure what I mean but I was wondering what would happen to a system of work that had no bottlenecks, one where everything flowed at maximum capacity all the time. Sounds to me like it might have some knock-on effects, so maybe the bottlenecks serve a purpose.