AI-assisted engineering practice
AI coding tools can help teams ship faster. But when engineering workflows do not keep up, they can also create instant legacy code: systems that work, but no one fully understands. Handcode helps teams build the practices, workflows and tooling they need to use AI at speed without losing control of the codebase.
The problem
Many teams are discovering that the hard part is no longer producing code. Features are still shipping. But reviews are getting slower, tests are less trusted, and fewer people can explain why the system is shaped the way it is.
Consultancy
Handcode provides focused, founder-led engagements for teams using AI to move faster than their current engineering workflow can safely support. The work starts with the code you already have, but looks at the whole system around it: planning, context, generation, review, testing, refactoring, and decision-making.
A focused review of one team, codebase, or product area. Handcode examines both the software and the AI-assisted workflow behind it: where AI is helping, where it is creating risk, and how the team can move faster while keeping ownership, understanding, and review quality.
Designed as a short, focused engagement rather than an open-ended consultancy project.
A deeper technical assessment of architecture, tests, duplication, coupling, and maintainability risks. Useful when a repo, service, or subsystem needs closer analysis after the initial engineering review.
A focused intervention for a feature area, service, or prototype that grew too quickly. The sprint targets clearer boundaries, missing tests, and a refactoring path your team can continue.
For teams with a vibe-coded MVP that now needs to become maintainable, operable, and ready for long-term development, without rewriting everything at once.
The usual starting point is an AI Engineering Review: a short founder-led engagement for one repo, service, or product area.
Ask about a reviewProduct
Handcode’s consulting work is also shaping an IDE-integrated agent harness for deliberate software change. The harness is in development and is driven by the same requirements: understanding before editing, explicit plans, traceable steps, refactoring support, rollback, and decision records.
Handcode is not trying to replace developers. It is trying to preserve the practices that make software development work: understanding, design, review, refactoring, testing, and shared ownership.
About
Handcode is founded by Tom Payne, a senior Java engineer and technical leader with two decades of experience building, changing, and maintaining complex systems, including in finance and trading environments. He has hands-on experience with ML and LLM-driven products. Handcode’s focus is not on generating more code. It is on helping teams make better changes to code they need to live with.
Start a conversation
Send a short note about your codebase, team size, stack, AI tools and what problems you're facing. I’ll reply personally and suggest whether a full engineering review, recovery sprint, or lighter-touch conversation makes sense.