Joe Prisk
Engineer who specialises in building thoughtful, scalable digital products that turn complex problems into simple, human-centred solutions.
Specialties
- Front-end Engineering,
- Design Systems
article
Build vs buy: AI code review for teams that have opinions
There’s a good chance that somewhere in your org, someone is trialling an AI code review tool right now, and at the same time someone else is pasting agent output into PRs under their own name.
·6 min readarticle
What engineering teams owe for the AI speed boost
AI-assisted development genuinely accelerated engineering teams, but many organisations stopped at the velocity gains and ignored the accumulating debt. The costs: code nobody fully understands, weakened code review culture, bloated dependency trees, and architectural decisions made without real judgement about tradeoffs...
·4 min readarticle
Why your design system is the most important input to Claude Code
Design systems are critical inputs for AI-assisted development tools like Claude Code because they constrain the AI’s micro-decisions around colours, spacing, and components – preventing "drift at speed" and ensuring generated UI remains consistent with your product’s visual language.
·5 min read
More posts from other Thinkmill voices
What AI use looks like in five enterprise design teams
Listening to design teams at Stripe, Shopify, Ramp, Atlassian, and Intercom, three ingredients become clear: a place to prototype, good context, and someone helping people put both to use.
·9 min readFrom Vibes to Durable Context
AI can speed up implementation, but it does not remove the need for good engineering. This article looks at how planning, human judgment, useful documentation, and a well-structured codebase can help coding agents make better decisions with less guesswork.
·4 min readIs Your Design System Ready for AI?
AI can generate convincing interfaces, but it struggles when a design system’s decisions live in team knowledge rather than its components, documentation and defaults. Preparing a design system for AI means making those decisions discoverable, explicit and verifiable.
·6 min read
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