The feed of updates to Vaughn Tan
Meaningmaking is a simple concept but one that is counterintuitively powerful, concrete, and applicable to understanding how we think about work and technology in a world where AI exists. What is meaningmaking? the tl;dr is that meaningmaking is any decision we make about the subjective value of a thing . I’ve been working on meaningmaking for a while. It’s a natural extension of thinking about…
tl;dr: Now that AI tools can generate many outputs that look like they were made by humans, we begin to fear that there’s nothing exclusively human left for humans to do. This fear points in the wrong direction. Machines can match outputs but what stays human is the act underneath them: deciding what’s worth wanting and doing when there is no objective rule to settle the question. Philosophers…
tl;dr: Organisations say they want innovation but keep killing it. The problem is that the organisational decision-making machinery assumes you already know enough to justify a big bet, and genuinely new things never cross that bar. Big visible bets also trigger a predictable organisational immune response that neutralises, ejects, or quarantines anything new and unfamiliar. The way through is to…
tl;dr: AI has quietly changed the economics of software. Tools that once took months and tens of thousands of dollars to build can now be made in an afternoon. That makes a whole category of small software businesses viable — software companies serving freight forwarders, F&B operators, sub-contractors — a category venture capital dismisses as too small. Singapore’s economy comprises mostly…
tl;dr: Tangent is a new incubator in Singapore I’ve just started. It is deliberately not a venture capital incubator. Instead, Tangent looks for ideas that solve real problems in existing markets using technology that already works, that take the existence of AI into account, and that can become rapidly self-sustaining. Because Tangent isn’t chasing venture-scale outcomes, it can widen the funnel…
tl;dr: Most people use “ AI business” to mean one of two things — building the AI itself, or building products that call AI at runtime. There are actually four structurally distinct types. The other two — using AI to build products that then run without any AI , and building businesses that exist or matter primarily because AI proliferation has changed what markets are viable — are already…
tl;dr: Content and representation are different things, and re-presentation is different again: selecting from and translating a body of content to produce new artifacts for different audiences and purposes. LLMs make re-presentation cheap and fast. So document management should now mean caring for and feeding totipotent source documents — structured for completeness, not for any specific reader —…
tl;dr: The agentic AI field treats the agent as the unit you build and improve. This is the wrong abstraction. Agents should be composed of small, readable primitives — capabilities, success criteria, decision rules — that can be swapped, evaluated, and evolved independently. The idea comes from organisational theory: high-performing teams under uncertainty don’t treat people as monoliths either.…
tl;dr: When you’re matching capabilities to applications — AI tools to roles, research teams to industry sectors, platforms to use cases — the relationship has two properties: how tightly each capability connects to each application, and how many relevant connections exist. These two dimensions produce four quadrants, each requiring a qualitatively different strategy. The people involved (the…
tl;dr: Innovation requires uncomfortable unfamiliar work, but people instinctively resist discomfort. Incentives and motivation programmes don’t work for innovation either. Instead, successful organisations use productive desperation: deliberately committing to projects calibrated to be just beyond current capabilities, with real possibility of failure and no escape route. This forces learning,…
tl;dr: The most important knowledge in any organisation—what makes your work distinctively yours—can’t be written down or taught through training programmes. It’s tacit knowledge that must be learned through direct experience. Most organisations try to solve this by writing better documentation, which fails. Organisations that successfully teach tacit knowledge embed learning into everyday work…
tl;dr: Small-medium businesses are missing a huge opportunity because of three imagination failures: they believe digital transformation must be big and disruptive, they haven’t recalibrated software buying for the collapse in software development costs, and they don’t realise this economic shift requires a different consulting approach. These businesses need Boring Tiny Tools (very narrowly…
tl;dr: Critical thinking is foundational for making decisions that require subjective judgment. People learn how to do subjective decisionmaking through practice. Unfortunately, organisations increasingly reserve subjective decisionmaking for senior members, so junior members get neither practice nor support in learning how to do it; this also means that they don’t get practice in the kinds of…
I’m now incubating and funding AI-informed businesses at Tangent . If you want to start a company that makes Boring Tiny Tools, please take a look and get in touch . tl;dr : This essay is about Boring Tiny Tools —why they’re the way forward for digital transformation. Generative AI coding tools now enable high-utility, highly customised, but narrowly scoped software … but only with a fundamentally…
For 3 years during Covid, I lived in crumbling houses in depopulated hamlets on two different mountains in the Haute-Loire, one of the departements of France located on the volcanic plateau of the Auvergne. At dinner last week, someone asked me what one actually does when living alone in an otherwise uninhabited, rural, remote hamlet for an extended period. Boredom and distress seem to loom large…
tl;dr : Online workshops rarely work well, and we keep on doing them because they would be too expensive/infeasible to do in-person. This is the wrong framing. The right framing is to ask how to redesign online workshops from the ground up to be effective not in spite of but because they’re online. Virtual spaces destroy our spatial navigation abilities and make reading participants nearly…
tl;dr: Why borrowing private sector strategic thinking and values undermines public strategy — and a practical tool for using tradeoffs to develop robust public strategy that serves diverse stakeholders over long time horizons. I spoke today at the Institute of Public Administration’s Governance Forum , to a few hundred attendees from across the public and non-profit sectors. The core problem I…
tl;dr: Every important decision requires subjective reasoning about objective facts—deciding what matters and why. Yet we have almost no explicit frameworks for this work, which is a source of civilisational fragility in an age of AI and accelerating political and social fragmentation. Reasoning scaffolds fill this gap: they’re an explicit structure to make subjective reasoning visible and…
tl;dr: I’ve been prototyping an AI tool that uses Socratic mirroring to build a reasoning scaffold that helps users develop stronger arguments . Testing a fully functioning prototype across universities, corporations, startups, and government shows that the method generalises: Users doing real work with real stakes find it useful enough to want their institutions to provide it. Theoretical…
tl;dr: Students now have access to LLMs that can write essays, but seem to be losing the capacity to think critically. I solve this problem by reconsidering the interaction logic between human users and the AI tools they use. I’ve developed an AI tool that inverts the usual logic of the empty, unconstrained chat box — the goal is to help users learn to think critically and do meaningmaking work…
tl;dr: After over a decade teaching strategy in private and public sector settings, I’ve developed a new public sector strategy course that flips the conventional wisdom. Instead of borrowing failing private sector concepts, my approach recognises that public sector organisations — with their complex stakeholder environments, wicked problems, and indefinite time horizons — require fundamentally…
What if you could experience what it’s like to make decisions when the actions and outcomes available to you are truly uncertain? That’s what FOUNDATION , a new prototype interactive exhibit at MOD . , invites you to explore. FOUNDATION is a multi-player construction game where participants work together to make the best foundation for future players to build the tallest structures possible. But:…
Current AI interfaces lull us into thinking we’re talking to something that can make meaningful judgments about what’s valuable. We’re not — we’re using tools that are tremendously powerful but nonetheless can’t do “ meaningmaking” work (the work of deciding what matters, what’s worth pursuing). I developed and tested with first-year undergraduates a pen-and-paper prototype designed to isolate the…
In June, I ran a workshop with 15 researchers from diverse fields to develop practical, implementable mechanisms for experiencing different types of not-knowing firsthand. While we identified some new categories of not-knowing beyond those in my original framework, the real breakthrough was creating concrete prototype ideas — like “ the camera of not-knowing” that forces you to take action without…
tl;dr: Categories aren’t academic conceits—they’re tools that enable more effective practical action. If you care about making AI work in real-world settings, or navigating business uncertainty, or more reliably drinking wine that you enjoy, then learning to think more rigorously about what types of things you’re dealing with can be a competitive advantage. This post shows how categories clarify…
tl;dr: Hidden behind an unmarked doorway in Barcelona, two coffee businesses share the same small space — one roasting and selling, the other teaching and tasting — but not at the same time. This smart setup, which I called a stacked space , cuts costs, spreads downside-exposure, and promotes urban experimentation and innovation. It’s an emerging pattern you can now spot in Singapore, Tokyo,…
This is an overview essay for a series about not-knowing . The first essay in the series is True uncertainty ≠ formal risk . TL;DR: Most organisations treat not-knowing as a single thing requiring a single response. It is not. Four structurally distinct types exist — about what actions are possible, what outcomes are imaginable, how actions cause outcomes, and what outcomes are actually worth —…
tl;dr: I’m looking for — or would like to build — games that operationalise true uncertainty, not just simple risk, to help players become better at making decisions when facing different types of not-knowing. Games are safe spaces to learn how to deal with the unknown. By design, they can be insulated from real-world consequences, giving us room to experiment, fail, and try again. They help us…
tl;dr: Current LLMs can’t truly or create new knowledge on their own; but they can help humans do that innovation work more quickly. LLMs work best as eager research assistants: good at mapping known landscapes, bad at deciding what matters. So, paradoxically, they’re most useful to people with enough domain expertise to ask good questions and spot flaws — but they leave novices vulnerable to…
tl;dr: A futurist friend recently made an expensive, early exit from the Middle East during a flare-up in the Israel-Iran conflict … then felt embarrassed when the situation de-escalated theatrically. That embarrassment stems from misframing the decision as an optimisation problem — which assumes that precise estimation of risks, probabilities, and timings is possible. It wasn’t. The situation…
tl;dr: Anthropic’s experiment with using Claude as an autonomous shopkeeper (“Claudius”) failed — not just because the AI was gullible, but because running even a simple business involves inherently human, meaning-making decisions. Doing business isn’t just executing tasks like pricing or inventory. It’s deciding what matters, what to trade off, and what success looks like. These are subjective…