Spec-driven development
Writing clear tasks and acceptance criteria so people and agents know what to build.
Offering 02 — Hands-on Team Enablement
Help your engineers get more from AI.
Your team may already use AI every day. We teach the engineering practices that help them achieve more, through pairing, code review and hands-on work in your codebase. The project can be any software your team builds.
Your time
Engineers with time to learn and apply the practices to their work.
Our team
Senior engineers who teach through pairing, code review and practical examples.
A real project
We work on your existing codebase or a new project your team wants to ship.
Your practice
Practices adapted to your team and documented in your repositories.
How it works
Learn together. Apply it to your work.
We start with how your team works today and choose the practices that will help most. We agree the scope, time commitment and checkpoints up front, then teach and review as your engineers apply them to real changes.
- 01Understand how you use AI todaytogether
- 02Choose the practices to work ontogether
- 03Teach through real changeswe pair
- 04Apply the practices to your workyou lead
- 05Review progress and document what workstogether
What your team learns
Practical habits for better engineering with AI.
Agent-ready codebases
Context files, module boundaries and fast tests so agents do real work safely.
Choosing and using agents
Choosing tools for your tasks, giving agents useful context and knowing when to step in.
Reviewing AI-written code
Checking the design, behavior and maintainability of a change before it ships.
Testing and verification
Using tests, CI and independent checks to verify agent work. Adding evals when the product uses models.
Making the practices stick
Building what works into planning, code review and everyday development.
Is this the right fit?
Hands-on Team Enablement, or Done for You?
Hands-on Team Enablement fits when
- Your engineers use AI, or are getting started, and want to get more from it.
- You want practical guidance on specs, agents, testing and review.
- You can give a team real time on the project each week.
- You want your team to keep using the practices after we leave.
Done for You instead when
- Your engineers are committed elsewhere, or you do not have an engineering team.
- You need one team accountable for delivery itself.
- You would rather we keep running the system after launch.
What you get
We focus on the practices your team needs and apply them to a bounded piece of real work. We review progress against the goals we agreed at the start.
What you get
- 01
Hands-on learning
Pairing and review on real changes, with feedback your engineers can use immediately.
- 02
A better development workflow
Improvements to context, specs, tests and review that fit your codebase.
- 03
Your team playbook
Examples and conventions your engineers can use and share, written down in the repo.
Done when
Your engineers can apply the agreed practices to a change, verify the result and explain their decisions without our guidance.
Capabilities we draw on
- AI-Native Engineering →
The codebase, spec and review practices we set up with your team.
- AI-Native Playbook →
The working rules we teach, published in full.
- Model Testing & Evals →
How we evaluate models when your product depends on them.
- Wharf research →
Our benchmark of models and agent harnesses on real engineering tasks.