The lines between technology and culture are blurring. And so, it’s no longer enough to build great tech.

Whether in expressed via product design, brand, or user experience, taste now defines how a product is perceived and felt as well as how it is adopted, i.e. distributed — whether it’s software or hardware or both. Technology has become deeply intertwined with culture.3 People now engage with technology as part of their lives, no matter their location, career, or status.

founders are realizing they have to do more than code, than be technical. Utility is always key, but founders also need to calibrate design, brand, experience, storytelling, community — and cultural relevance. The likes of Steve Jobs and Elon Musk are admired not just for their technical innovations but for the way they turned their products, and themselves, into cultural icons.

The elevation of taste invites a melting pot of experiences and perspectives into the arena — challenging “legacy” Silicon Valley from inside and outside.

B2C sectors that once prioritized functionality and even B2B software now feel the pull of user experience, design, aesthetics, and storytelling.

Arc is taking on legacy web browsers with design and brand as core selling points. Tools like Linear, a project management tool for software teams, are just as known for their principled approach to company building and their heavily-copied landing page design as they are known for their product’s functionality.4 Companies like Arc and Linear build an entire aesthetic ecosystem that invites users and advocates to be part of their version of the world, and to generate massive digital and literal word-of-mouth. (Their stories are still unfinished but they stand out among this sector in Silicon Valley.)

Any attempt to give examples of taste will inevitably be controversial, since taste is hard to define and ever elusive. These examples are pointing at narratives around taste within a community.

So how do they compete? On how they look, feel, and how they make users feel.6 The subtleties of interaction (how intuitive, friendly, or seamless the interface feels) and the brand aesthetic (from playful websites to marketing messages) are now differentiators, where users favor tools aligned with their personal values. All of this should be intertwined in a product, yet it’s still a noteworthy distinction.

Investors can no longer just fund the best engineering teams and wait either. They’re looking for teams that can capture cultural relevance and reflect the values, aesthetics, and tastes of their increasingly diverse markets.

How do investors position themselves in this new landscape? They bet on taste-driven founders who can capture the cultural zeitgeist. They build their own personal and firm brands too. They redesign their websites, write manifestos, launch podcasts, and join forces with cultural juggernauts.

Code is cheap. Money now chases utility wrapped in taste, function sculpted with beautiful form, and technology framed in artistry.

The dictionary says it’s the ability to discern what is of good quality or of a high aesthetic standard. Taste bridges personal choice (identity), societal standards (culture), and the pursuit of validation (attention). But who sets that standard? Taste is subjective at an individual level — everyone has their own personal interpretation of taste — but it is calibrated from within a given culture and community.

Taste manifests as a combination of history, design, user experience, and embedded values that creates emotional resonance — that defines how a product connects with people as individuals and aligns with their identity. None of the tactical things alone are taste; they’re mere artifacts or effects of expressing one’s taste. At a minimum, taste isn’t bland — it’s opinionated.

The most compelling startups will be those that marry great tech with great taste. Even the pursuit of unlocking technological breakthroughs must be done with taste and cultural resonance in mind, not just for the sake of the technology itself. Taste alone won’t win, but you won’t win without taste playing a major role.

Founders must now master cultural resonance alongside technical innovation.

In some sectors—like frontier AI, deep tech, cybersecurity, industrial automation—taste is still less relevant, and technical innovation remains the main focus. But the footprint of sectors where taste doesn’t play a big role is shrinking. The most successful companies now blend both. Even companies aiming to be mainstream monopolies need to start with a novel opinionated approach.

I think we should leave it at “taste” which captures the artistic and cultural expressions that traditional business language can’t fully convey, reflecting the deep-rooted and intuitive aspects essential for product dev

LLMs will represent a step change in tool support for end-user programming: the ability of normal people to fully harness the general power of computers without resorting to the complexity of normal programming. Until now, that vision has been bottlenecked on turning fuzzy informal intent into formal, executable code; now that bottleneck is rapidly opening up thanks to LLMs.

If this hypothesis indeed comes true, we might start to see some surprising changes in the way people use software: One-off scripts: Normal computer users have their AI create and execute scripts dozens of times a day, to perform tasks like data analysis, video editing, or automating tedious tasks. One-off GUIs: People use AI to create entire GUI applications just for performing a single specific task—containing just the features they need, no bloat. Build don’t buy: Businesses develop more software in-house that meets their custom needs, rather than buying SaaS off the shelf, since it’s now cheaper to get software tailored to the use case. Modding/extensions: Consumers and businesses demand the ability to extend and mod their existing software, since it’s now easier to specify a new feature or a tweak to match a user’s workflow. Recombination: Take the best parts of the different applications you like best, and create a new hybrid that composes them together.

Chat will never feel like driving a car, no matter how good the bot is. In their 1986 book Understanding Computers and Cognition, Terry Winograd and Fernando Flores elaborate on this point: In driving a car, the control interaction is normally transparent. You do not think “How far should I turn the steering wheel to go around that curve?” In fact, you are not even aware (unless something intrudes) of using a steering wheel…The long evolution of the design of automobiles has led to this readiness-to-hand. It is not achieved by having a car communicate like a person, but by providing the right coupling between the driver and action in the relevant domain (motion down the road).

Think about how a spreadsheet works. If you have a financial model in a spreadsheet, you can try changing a number in a cell to assess a scenario—this is the inner loop of direct manipulation at work. But, you can also edit the formulas! A spreadsheet isn’t just an “app” focused on a specific task; it’s closer to a general computational medium which lets you flexibly express many kinds of tasks. The “platform developers"—the creators of the spreadsheet—have given you a set of general primitives that can be used to make many tools. We might draw the double loop of the spreadsheet interaction like this. You can edit numbers in the spreadsheet, but you can also edit formulas, which edits the tool

what if you had an LLM play the role of the local developer? That is, the user mainly drives the creation of the spreadsheet, but asks for technical help with some of the formulas when needed? The LLM wouldn’t just create an entire solution, it would also teach the user how to create the solution themselves next time.

This picture shows a world that I find pretty compelling. There’s an inner interaction loop that takes advantage of the full power of direct manipulation. There’s an outer loop where the user can also more deeply edit their tools within an open-ended medium. They can get AI support for making tool edits, and grow their own capacity to work in the medium. Over time, they can learn things like the basics of formulas, or how a VLOOKUP works. This structural knowledge helps the user think of possible use cases for the tool, and also helps them audit the output from the LLMs. In a ChatGPT world, the user is left entirely dependent on the AI, without any understanding of its inner mechanism. In a computational medium with AI as assistant, the user’s reliance on the AI gently decreases over time as they become more comfortable in the medium.

With the comprehensive application of Artificial Intelligence into the creation and post production of images, it seems questionable if the resulting visualisations can still be considered ‘photographs’ in a classical sense – drawing with light. Automation has been part of the popular strain of photography since its inception, but even the amateurs with only basic knowledge of the craft could understand themselves as author of their images. We state a legitimation crisis for the current usage of the term. This paper is an invitation to consider Synthography as a term for a new genre for image production based on AI, observing the current occurrence and implementation in consumer cameras and post-production.

For the layman to build their own Folk Interfaces, jigs to wield the media they care about, we must offer simple primitives. A designer in Blender thinks in terms of lighting, camera movements, and materials. An editor in Premiere, in sequences, transitions, titles, and colors. Critically, this is different from automating existing patterns, e.g. making it easy to create a website, simulate the visuals of film photography, or 3D-scan one's room. Instead, it's about building a playground in which those novel computational artifacts can be tinkered with and composed, via a grammar native to their own domain, to produce the fruits of the users' own vision. The goal of the computational tool-maker then is not to teach the layman about recursion, abstraction, or composition, but to provide meaningful primitives (i.e. a system) with which the user can do real work. End-user programming is a red herring: We need to focus on materiality, what some disparage as mere "side effects." The goal is to enable others to feel the agency and power that comes when the world ceases to be immutable.

I hope this mode can paint the picture of software, not as a teleological instrument careening towards automation and ease, but as a medium for intimacy with the matter of our time (images, audio, video), yielding a sense of agency with what, to most, feels like an indelible substrate.