Following the recent release of Claude’s latest model Scott White, Anthropic’s Head of Product for Enterprise, said that he thought we were moving into an era of ‘vibe working’. If vibe-coding was about describing the thing you’d like to build and letting AI write the code, vibe-working is the idea that humans can define outcomes and let the AI do the work of achieving it.
A theme of my recent writing has been how we can establish systems that embed critical thinking into the application AI to ensure that we avoid the atrophy of good judgement and learned experience, and that we don’t just blindly follow where the technology leads us (a huge risk for any business right now). So I wanted to also write something in defence of craft, and our continuing need for the kind of mastery that can only come from years of hands-on experience in any field. My central question is this: When AI is not just telling us how to do the work but increasingly doing the work itself, how can we protect craft?
Craft is not solely about learning technique. It is epistemological. By which I mean it is central to how humans know what they know. Michael Polanyi’s concept of ‘tacit knowledge’ which describes the implicit, embodied understanding that can’t be fully codified is really about how human understanding goes way beyond the knowledge that we can articulate. When we deploy AI agents that can autonomously define how best to achieve outcomes and then execute that process, we risk losing the tacit human knowledge embedded in the process itself. A frictionless process may be more efficient, but over time we may find that we’re eroding the judgement and the epistemological value that can only come from doing the work yourself.
In this sense craft isn’t separate from the knowing, it is the knowing. In the same way that an experienced woodworker knows how a piece of wood will respond under stress, an experienced strategist can intuitively spot opportunity from a wealth of research material and assimilate a way forwards. An experienced salesperson can rely on years of reading people and situations to frame a pitch in a way that resonates with a client. An experienced trainer can read a room, know how something is landing, and flex in ways that can help a room full of delegates go on their own journey to achieve a new level of understanding.
You can’t possibly codify all of that tacit understanding. In late 2024 Ben Affleck described AI as being like craft because it replicates what already exists. But AI will never create art, he said, because it lacks the taste to ‘know when to stop’. It’s a well articulated (and very quote-worthy) point, but I think it under-plays the value of human craft. The renowned Dreyfus Skill model shows a progression of skills acquisition from novice, to advanced beginner, to competence, proficiency, expertise and ultimately to mastery. Expertise and particularly mastery is the domain of craft. Experts can seamlessly integrate perception and action and intuitively adjust techniques based on context, but masters ‘seek to expand and refine their repertoire of intuitive perspectives. In doing so, they sometimes create new possibilities of performing and transform the style of their domain’. The expert and the master bring themselves into the task in a way that changes the process itself. A simple example – Stephen Curry changed the game of basketball forever by making the 3-point shot central to the game. An apprentice may learn the fundamentals of a craft from an experienced teacher but it is only when they have spent years developing their own approaches that they gain true mastery.
Richard Sennett has written compellingly about craftsmanship and he describes how thinking happens through making, and how the hand engaged in craft work develops its own intelligence (he calls this the ‘intelligent hand’). So the accomplished cellist’s fingers find their positions without conscious guidance, the potter can feel when the thin clay is about to collapse, and the chef knows the exact moment to take the pan away from the heat. He talks about how the craftsperson learns by reasoning backwards from effects to causes, and through the resistance the material offers (wood splitting, clay collapsing, metal bending).
Developing craft is about the intuition that emerges through years wrestling with challenging problems or situations. It is about the ‘feel’ that you get for situations that operates outside of conscious thought. It is about knowing what to leave out or when to stop or change. AI, by reducing friction, may inadvertently eliminate the very resistance that develops mastery.
In 1974, Harry Braverman’s book Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century argued that industrial era automation had acted to ‘deskill’ workers and erode craftsmanship. More than a decade later, Shoshana Zuboff wrote (in her book In the Age of the Smart Machine: The Future of Work and Power) about how information technology could either ‘informate’ (increase worker knowledge) or ‘automate’ (reduce worker agency). We’re facing a similar inflection point now with AI.
The idea of ‘vibe-working’ risks becoming thought without embodied engagement. To avoid this organisations need to move from implicit assumptions about judgement and craft being maintained to explicit systems that protect the conditions under which judgement and craft can develop. This doesn’t mean pulling back from applying AI but it does mean taking a more deliberate approach to building non-AI domain-specific skills and time to practice them (particularly for more junior staff), including craft skills in performance review, skills mentoring, periodically returning to craft-intensive foundational work, assessing judgement not just throughput, creating rituals where staff explain how they arrived at their conclusions (not just what they concluded), and protecting the value of uniquely human and judgement-driven areas of work.
Craft isn’t just about output quality. It’s not about achieving outcomes as efficiently as possible. Nor is it about replicating the same process seamlessly. It’s about the cognitive development that happens through the struggle. It’s about learning from friction. About responding to subtle changes. Recognising when something is ‘off’. Developing intuitive judgement derived of thousands of hours of practice. It’s about wisdom.
We’re at a moment where we face a stark choice. Should AI become something that amplifies human craft or something that atrophies it? At its simplest level, this is a choice between superagency and growing dependency.
A version of this post appeared on my weekly Substack of AI and digital trends, and transformation insights. To join our community of over thirteen thousand subscribers you can sign up to that here.
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