30 minutes with James Rooney to discuss your team, workflow and first scope.
For leaders whose teams have access to AI tools and need a shared way to use them, or who want their people to develop capability while a real delivery problem gets addressed.
Use the team's own requirements, examples and decisions. The people who understand the work help shape the method and can see where their judgement matters.
Turn practices that have been tried together into working guides, examples and review habits. Make it easier for another colleague to follow the same approach.
Look at how people complete a task, assess the output and improve it. Use that evidence to decide where further coaching, access or changes to responsibilities would help.
Use a 30-minute call to discuss the outcome your team needs.
Talk it throughFind a piece of work with a clear owner and a result the team can assess. Agree which roles need to participate and where learning fits into delivery.
Pair on requirements, implementation and review as appropriate to the engagement. Explain the decisions while making them, then give people room to try the next step themselves.
Agree responsibilities, review points and how the practice will be supported. Readiness establishes priorities, design shapes the working model, and a build team develops capability through delivery.
Ask how this approach would fit your data, systems and team on a 30-minute call.
Talk it throughDuring Tenhaw's six-month PPL engagement, a client engineer paired throughout a two-week working proof of concept. At its end, the engineer reported 70% confidence that they could follow the process independently. An eight-week project then developed operating guides across Product, Engineering and QA, with each step practised on live work.
Read how PPL developed its AI working practicesBook 30 minutes to ask James about the work and how it relates to your situation.
Talk it throughAgree the workflow, deliverables and team before work starts. These are the existing engagements this use case can sit within; prices exclude VAT.
Fixed price · £44,000
4 weeks
Find the AI workflows worth funding. Test them with your team.
See scope, team and terms£35k–£55k / month
2–4 months
A pair who design the AI-native operating model, and the agentic systems to run it at scale.
See scope, team and terms£70k–£85k / month
6–12 months
Build enterprise AI with an embedded team your people learn from.
See scope, team and termsUse a 30-minute call to decide which scope is a sensible starting point.
Talk it throughA 30-minute discovery call with James Rooney. Bring a workflow, product or team challenge and we will discuss a sensible first scope.
most start with a fixed-price AI Readiness Audit · £44,000 · 4 weeks · working prototypes
No time that suits? Email hello@tenhaw.com. Calendar not loading? Open it on cal.com.
Yes. Their work meets at requirements, acceptance decisions and feedback, so practising together helps each role understand the others. At PPL, the operating-method project covered Product, Engineering and QA, with design, build, testing, review and deployment practices developed on real work.
A real task, relevant examples and the authority to discuss how the work is done. Participants also need the agreed tools and access for that task. Their difficult cases help make the practice useful, and the engagement scope determines which activities we work through together.
Give them a small task, a worked example and someone to review it with. The operating guide should explain the decisions and checks as well as the steps. Comparing the new starter's attempt with the example shows where the guide or coaching needs improvement.