METR measured AI as 20% faster in theory and 19% slower on mature codebases.
METR found developers believed AI made them 20% faster. Measured output on mature codebases was 19% slower. The workshop makes that gap visible on your own product surface.
AI Agents + AK Way for Product Building
Free Workshop
Free Workshop
AI is writing more product code than most teams can safely review before it ships. The debt arrives a quarter later.
This workshop shows what has to change in your engineering foundation before that speed is worth having. Two hours on your codebase with the solution architects who would run the engagement. You leave with a first-sprint change map and a list of fixes worth making even if you never hire us.
2 hours
Free
Virtual
Your codebase
Run by solution architects
Why This Exists
The question stopped being whether AI can produce code. It is now whether your team can trust the code it produces.
Most teams have already seen the upside: boilerplate lands faster, refactors start with less friction. The problem sits one layer below, where naming drift, hidden coupling, thin test contracts, and undocumented product decisions make the new speed hard to trust.
AI can move faster than your review discipline.
Veracode found 45% of AI-generated code failed security tests. In the session, tests, review gates, and Inspector show where that risk appears and how to stop it sooner.
DORA: AI helps teams who already had strong delivery foundations. Without those, it amplifies the gaps.
DORA showed AI helps most when teams already have strong delivery foundations. This workshop translates that into product-engineering reality: tests, boundaries, observability, governance, and measurement.
You need a clearer first sprint, not another AI deck.
The point is not to leave excited about agents. The point is to leave knowing exactly what has to change first, what a pod would change in sprint one, and what your team should fix anyway.
Agenda
Four sessions running on one real codebase from your team, not on a reference repo.
Two hours. Your code. Every gate visible.
The visual on the left tracks the session you are on. Every session ends with a tangible artefact, not a takeaway slide.
Session 01 . 20 min
Pick the product surface that matters now.
We choose one slice of your codebase worth examining now, then map the delivery risks around it: missing tests, weak boundaries, hidden dependencies, review bottlenecks, and places AI would move faster than your team could safely verify.
Session 02 . 45 min
Run agents inside the AK Way.
You watch AI-assisted product work happen under real constraints. Amazon Q Developer and Kiro operate inside test contracts, architectural boundaries, scoped permissions, and observability. Inspector, CloudWatch, and review gates show what passes, what gets blocked, and why.
Session 03 . 35 min
Turn what we saw into a first-sprint change map.
We show what a pod would change first: where to tighten tests, where to redraw boundaries, where to add telemetry, where Bedrock AgentCore style workflows fit, and where agents should not go yet.
Session 04 . 20 min
Make the next step honest.
If a pod is the right move, we say what the first sprint should look like. If the foundation is not ready, we say that too. You leave with the work that matters either way.
What You Leave With
What you leave with is an operating map for the next sprint, not a slide deck and a feeling.
The output is practical. The exact product surface we focused on, the engineering gaps around it, the sequence we would change first, and the honest answer about whether a pod is the right next step.
First-sprint change map
The product surface, the gaps around it, and the order we would change first.
AK Way gap list
Where tests, boundaries, observability, governance, and DORA measurement are ready for agentic speed and where they are not.
Tool-fit recommendation
Where Amazon Q Developer, Kiro, Bedrock AgentCore style workflows, Inspector, and CloudWatch actually fit your delivery model.
Go or no-go recommendation
Whether a pod is the right move now, later, or not at all. Every output is yours.
Who Should Come
Bring the people who own delivery risk. Bring them with the engineers who would actually run the new tools day to day.
Must attend
CTO or VP Engineering
The person deciding whether faster product delivery is worth the risk profile underneath it.
Must attend
Principal engineer or lead architect
The person who can spot where agentic speed collides with reality in the codebase.
Recommended
Engineering manager or product engineering lead
The person who would own the first sprint changes and feel the impact day to day.
Recommended
Product lead for the surface in scope
The person who can say which delivery risks matter commercially, not just technically.
AI does not make product teams trustworthy. It makes the trust gap visible faster. This workshop shows where that gap is in your codebase and what it takes to close it.
Recent results
How we helped real customers ship on AWS.
It was very easy to be engaged. I was very impressed because I felt like we were moving forward with very good discussions, very smart people, and a lot of empathy and care. Of course, I'm also putting forward people whose expectations I'm trying to manage and how they see this. So yeah, I would agree, wonderful team for sure.
Book The Workshop
Bring one real product surface. Leave with a clearer first sprint.
Free. Virtual. Two hours. Your first conversation is with a solution architect, not a sales exec. If the workshop shows a pod is the right move, we'll tell you what the first sprint should be. If it shows the foundation needs work first, you'll leave with that list either way.
