Better ways to do your work.

Bring the codebase, design workflow, research process or recurring piece of analysis that you want to improve. We build the teaching around your work, experience and constraints.

A session can combine demonstration, guided practice and making a small tool. A longer engagement can include workflow changes, development environments, custom software and support while the team puts the new approach into practice.

Good training gives people ways to evaluate the work as well as produce it. We make room for uncertainty, practical concerns and the parts of a profession that need to remain under a person’s control.

For teams using AI, the work includes deciding what to delegate, how to check a result and where the tools are a poor fit. We agree the boundaries around confidential information and professional responsibilities before using work materials.

We combine education with hands-on changes to repositories, development tools and delivery practices. The goal is a team that can use the approach in its own work, with an agreed way to judge whether it is helping.

The same approach can support visual exploration, document workflows and other specialized tasks. A useful technique may involve a sequence of tools or software built for your profession, rather than a single prompt.

Speciate is one example of our own tool-building around visual exploration. We can use work like this to make a teaching technique concrete.