PRODUCTHEAD is a regular newsletter of product management goodness,
curated by Jock Busuttil.
how can you product sure? #
every PRODUCTHEAD edition is online for you to refer back to
tl;dr
AI is forcing us to adapt how we work in the face of greater information flow
However, this doesn’t mean we abandon the fundamental guiding principles of our discipline
hello
In a manner reminiscent of Martin Luther’s posting of his Ninety-five Theses on the door of the Schlosskirche in Wittenberg in 1517, a collective of prominent people from various tech disciplines have set out the 4 values and associated 16 principles they believe should guide the creation of meaningful products in this brave new world of AI. As was the intention for Luther and his followers, the Makers Manifesto1 is already provoking thoughtful debate. (Just hopefully not excommunication.)
Because you’re all erudite individuals, you’ll recognise the parallels between this new Makers Manifesto and the Agile Manifesto of 2001. Personally I’m still a bit miffed that ‘Agile’ has been abused as a concept so much that it’s practically become a byword for the very dysfunction it sought to combat. Only time will tell whether the intent of this new manifesto becomes (wilfully) misinterpreted to the same degree. I will offer the princely sum of £5 to anybody who spots an accusation of ‘makerwashing’ in the wild.
I hope that doesn’t come to pass. (Not least because I want to keep my £5.) AI offers the promise of doing more with less, of shipping product more frequently – just as people thought was the point of Agile – but this by itself doesn’t create value in any meaningful way. Churning out more soulless, ill thought-out slop2, more quickly than before, serves nobody’s true needs. But it does keep the type of people happy who value output instead of outcomes, and for whom tokenmaxxing is just another meaningless vanity metric to sit alongside ‘user stories per sprint’ and ‘lines of code’.
Jevons Paradox #
A lot of people have been citing the Jevons Paradox3 recently. Making something cheaper, easier and more efficient to achieve will mean more people make use of it, which in turn results in more usage overall, not less.
I encountered this first-hand at the Ministry of Justice. A senior civil servant was complaining that a service we’d recently redesigned and put online was being used by way more people than before (a good thing), and so had increased overall operating costs despite reducing the cost per transaction. He suggested we should hide it and make it harder to access in order to bring the costs back down. I suggested he should consider going camping on a tall cliff in high winds.
This highlights the same confusion of outputs and outcomes as before. The purpose of the service was to assist all people to achieve a particular goal. Only its obscure, cumbersome and confusing application process had been artificially constraining its usage (and cost). There was always the demand for what the service offered – it’s just that a significant proportion of that demand was discouraged by the earlier crap design. But to that senior civil servant, the earlier iteration was more ‘successful’ because it was cheaper to operate.
It’s therefore a misconception that AI is going to free us up to live the life of leisure. There is not a finite amount of work but an inexhaustible supply. Becoming more efficient at one set of work only clears space for another set to fill.
Delivering more value or more stuff? #
The next question the Jevons Paradox prompts is whether the activities that we can now do more of with less effort actually achieve valuable outcomes, or simply add to the noise.
At my parents’ house there was an aged gas oven. Over many years, the established way to light it had been to crank the gas on full and leave it for a minute or two before sparking the ignition. A muted ‘whuf’ would signal success. One day, the council upgraded the gas supply in the area to increase its flow. (Some of you are well ahead of me.) The next relighting of the oven was less a ‘whuf’ and more of an ‘WHOOOMPH’ (no injuries beyond singed eyebrows). The oven lighting procedure was duly amended.
There’s no doubt that AI has increased the flow of work and information. But our respective workplaces are systems, and removing one bottleneck tends to reveal the next one along. For many product people, our position at the nexus of the users, the business and technology means we’re more susceptible than most to a flow increase. We need to adapt our approach accordingly to avoid losing our eyebrows.
Adapting doesn’t mean abandoning our principles #
Despite us dealing with even more contextual information and change than before, coming at us more rapidly from more sources, we are nevertheless expected to raise our own productivity in response. We have to get even quicker and better at combining and sifting information to find the signal in the noise, and then acting on what that information tells us.
Brute-forcing the problem (working longer and harder) simply won’t compete with the AI torrent. But try to put aside any fears of being left behind. The tooling we need to keep up will catch up. It’s happened many times before4. For next week’s PRODUCTHEAD, I’m planning to share a selection of the emerging approaches.
Although we do need to change the way we work, we don’t need to abandon our guiding principles. We continue to operate in service of our users primarily, then of our business. Our users have neither infinite attention nor time. It doesn’t serve their needs if (for example) we smother them with product iterations simply because we can now ship at greater frequency.
Much of the Makers Manifesto is devoted to spelling this out. There’s no harm in a considered reminder of what we were meant to be doing all along.
Speak to you soon,
Jock
what to think about this week
Makers Manifesto
Our purpose is to see more people making great products — ones that create genuine value for the people they serve and the organisations that make them.
Every organisation is adopting AI technologies. Few are clear on what needs to change, and what remains true. Just because you can, doesn’t mean you should.
We offer these principles not as a fixed doctrine but as a working position — one we hope will drive better decision making and optimisation at every level: organisation, team and individual, for both humans and agents.
We also acknowledge that this document captures a moment in time. The rate of change in this environment means these principles may need revisiting. We offer them in that spirit.
Service Standard
Although it has been revised a few times over its introduction in 2012/13 (depending on whether you count the pilot), the intent of the UK government’s Service Standard remains the same: to build services of value primarily to the people using them, iteratively and with evidence from real user research. All of which was completely antithetical to the approach in government at the time. And boy, was there push back.
That it has survived broadly intact for this long is a good sign. However, the UK’s Civil Service seems to mark time in epochs, and the whole digital movement is still considered by some in government to be a minor, short-lived annoyance. See also the related Design Principles.
How government is expected to create and run public services
[GOV.UK Service Manual]
Why your values are useless
How many of you have something like “Build a delightful user experience” as a value? Maybe you call it a team value, a product principle, or design value? Most of us do. Because it’s an admirable goal. Of course we want to build amazing delightful user experiences. And our industry is rife with similar values, as you can see in the image above, based on research from my friends at Xing.
But do any of these fluffy values really help you make decisions? Have you ever gone in to a meeting super excited to present your latest and greatest plan for a shitty user experience, only to be reminded that that probably doesn’t fit your values? Of course not.
Principles help you make better decisions, faster
[Martin Eriksson / The Decision Stack]
recent posts
Startup to Scale-up Club Q&A – 14th April 2026
For Startup to Scale-Up Club‘s April Q&A session, we covered topics including:
Structuring analytics for user engagement
Defining an MVP in the AI era
When to use genAI and when to use machine learning (ML)
Product differentiation in a crowded market
Implementing reusable components and designs
Free advice for startup and scale-up founders
[I Manage Products]
We’re all addicted to AI, but it’s going to be okay
We seem to stuck in a contradiction in which we worry about AI’s effect on our critical thinking, while finding it equally hard to resist using. Why is that?
[I Manage Products]
Canary in the mine: AAA game developers are unionising
Product management has had its own fair share of problems over the last few years. Nevertheless, there are early warning signs from AAA game studios that there may be another storm brewing in tech for us to weather.
Union-busting just isn’t a good look
[I Manage Products]
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PRODUCTHEAD is a newsletter for product people of all varieties, and is lovingly crafted from a new cohort of coaching clients.
Notes #
- The missing possessive apostrophe will forever irk me. ↩
- Brad Colbow, a graphic artist and reviewer of drawing tech, came up with a great definition of ‘slop’: slop isn’t specifically content that’s generated by AI, it’s any content created solely for the sake of content, for the sake of monetization, for feeding the algorithm, or for engagement at all costs. ↩
- See 1. ↩
- Social media, big data, more detailed usage analytics, to name a few, have each represented step changes in the amount of information we can draw on, and in each case better tooling has emerged to cope with the onslaught. ↩