Review hasn’t caught up. People are asked to trust work they didn’t write, without a shared standard for checking it.
Method.AI Foundations · a strategic team engagement
Make AI a way of working both teams trust.
Bring product and engineering into the same room. In two focused days, turn AI’s impact on delivery into clear agreements about how your team plans, reviews, owns and ships work.
Assessment. Two days together. A 30-day check-in. Designed around your team’s reality.
Product + engineeringBoth disciplines, together
2 working daysDesigned around your team
30-day check-inMake the change stick
Post-Series A teamsTypically 20–80 engineers
The gap after the pilot
Your tools changed. Did the way you work?
AI can make parts of engineering dramatically faster. But when the surrounding agreements stay the same, the gains stall - and friction moves somewhere else.
The obstacle is rarely access to another tool. It’s a shared understanding of what good work looks like now.
Estimates no longer mean the same thing. What got faster, what got riskier and what still takes time are unclear across the team.
Ownership is fuzzy. When an agent contributed, the team still needs clarity on who is accountable for the result.
Product was left outside the conversation. New engineering habits look like an experiment instead of a delivery practice.
What the team leaves aligned on
A shared foundation for delivery.
Not a set of rules imposed from outside. Product and engineering work through what changed, then create agreements they can both stand behind.
What AI changes
Identify what became cheaper, what carries new risk and what remains human work.
What good review means
Agree what review needs to do when the author and the tool are not the same thing.
How to estimate and plan
Rebuild shared expectations about scope, effort and the shape of delivery.
Who owns the outcome
Make responsibility clear from the decision to use AI through to what reaches customers.
What “finished” means
Define an outcome both disciplines can recognise and hold each other to.
Where Method.AI applies
Use the Method.AI principles in your delivery lifecycle, with the right level of guidance for your team.
One connected engagement
Designed to move from insight to habit.
A workshop day can create agreement. The package gives the team a reason to use that agreement, learn from it and adjust.
Assess the current picture
Product and engineering complete the AI Adoption Scorecard. A short conversation helps us shape the workshop around what it reveals.
Work through the changes together
Two days with both disciplines in the room. Split tracks where that helps, shared sessions where alignment matters.
Write your team’s 30-day plan
The people who will use it decide what happens next. That makes the plan practical and genuinely theirs.
Check what changed
Reconnect to look at what stuck, what got in the way and what the team needs next.
Built in, on purpose
The 30-day check-in is part of the engagement - not a courtesy call. It’s how the team learns whether its new agreements work in practice.
A good fit for teams ready to change together
Make the next stage of AI adoption intentional.
Foundations is for scale-ups with enough delivery practice to improve - and enough leadership alignment to do something about it.
Good fit if…
- You’re a post-Series A scale-up with roughly 20–80 engineers
- AI use has spread unevenly across product and engineering
- A board, enterprise customer or new CTO is asking about your AI approach
- Product and engineering are starting to disagree about estimates or ownership
Not the right format if…
- Your team is very small and has no shared practice to change yet
- You need a large-enterprise transformation programme
- You’re looking for an introductory prompting class
- Product leaders cannot join the conversation
A strategic engagement, scoped to your team
Start with the challenge you’re trying to solve.
Foundations combines an assessment, two days of cross-functional work and a 30-day check-in. We’ll talk through your context and confirm the right scope and investment before you commit.
Common questions
Before bringing the team together.
Does this give away the Method.AI methodology?
Foundations teaches the principles and helps your team practise them together. A deeper Method.AI engagement maps the methodology to your architecture, obligations and threat model.
Why does product need to attend?
AI changes decisions across delivery, not just how code gets written. Product and engineering need a shared view of scope, estimates, review, ownership and what “done” means.
Can you make it one day?
The two-day format gives both disciplines enough time to work through the changes and create a plan they can use. We’ll discuss your situation, but compressing it may reduce the time available to build shared agreements.
What if our team is sceptical about AI?
Scepticism belongs in the room. The work is to understand what has changed for your team, where it helps, where it adds risk and what your organisation should do about it.
Can you deliver remotely?
Foundations is designed for the product and engineering teams to work together. Tell us about your team and location and we can discuss the best format.
Turn scattered AI use into a shared practice.
Get product and engineering moving together.
Start with a conversation about your team, your friction points and what a useful change would look like.