Monday I start building the AI Native team
Twelve weeks. A real AI native team. A product you can show.
Cohort 2 of the AI Native Practitioner Programme kicks off August 17.
We can’t get AI native experience from a course. We get it from shipping something real with a team that holds a bar. With layoffs, roles removed, and FOMO to lose our jobs, this is a chicken and egg problem.
That is what I try to solve with the AI Native Practitioner program; Twelve weeks. One cross functional AI native team. One product from idea to launch, using the Working Backwards method I ran at Amazon.
Arturo went in as Frontend Engineer and came out as AI Engineer.
Li-Chieh went from UX Designer to AI Augmented UX Researcher.
Diana from Business Analyst to AI Augmented Product Manager.
They can say they had those new roles because of what they learned and shipped within a real team, working with real customers.
What AI native means
Everyone has the tools now. What matters is where we put our judgment. An AI-dependent team asks the model what to build, accepts what comes back, and ships it. An AI-native team decides what problem is worth solving, writes the spec before the code, hands execution to the agents, settles guardrails and evals, reviewing the output against a real bar.
Agents execute. We think. The bar holds.
The roles open
Product Manager: Leads the team through Working Backwards. Owns the PRFAQ and PRD. Makes prioritisation calls, presents to the leadership review I will run. It is the hardest role in the cohort, the one people underestimate most, and what is most needed this era.
Engineer: Designs the technical architecture, estimates effort, and builds features using AI coding tools with specs first. Bridges product ideas to technical reality. Reviews the PRD for feasibility and uses it as spec. Holds the review bar with me.
UX Designer: Creates wireframes, design principles, and the hi-fi prototype. Owns the visual language. Collaborates with research on synthesis. Generates the HTML and submits it to Github. Leads design review and a mentor holds its bar.
UX Researcher: Designs and runs user interviews. Leads Jobs-to-be-Done synthesis. Plans and runs usability tests. Grounds every product decision in real evidence. Reviews synthesis with Nick, Senior UX Researcher in my previous team AWS Resource Management.
TPM: Manages the team's delivery. Sets up and maintains the workspace. Runs the risk register. Ensures rituals are done and deliverables ship on time. Documents decisions. Team up with me to manage the roadmap.
Engineering Manager or Team Lead: Leads the product planning, unblocks, and runs the launch call. Holds the delivery bar without doing everyone else's work. Syncs with me.
The roles are the same, the deliveries as well, what changes is the AI-native execution. You choose one main role but can train other role tasks since now role boundaries got blurrer. No prior AI experience is required. What is required is agency to learn and executing independently and a minimum of tech experience.
Judgment while executing AI is what gets trained.
Some people already joined at different roles and levels. I am building a two pizza team (4-8 people) and multiple AI native pods. Roles assignment starts on Monday. Every day that passes before August 17 leaves fewer roles available.
What it costs you in time
Minimum you will need 4 hours a week. We will execute a sprint per main delivery. Will start with a live team session to kick off the sprint and review the roadmap that holds you accountable. The rest will be async work or whatever the team needs. At the end of the sprint, we do live review sessions with the main delivery mentors.
If something slips, we adapt. Life happens. Though your commitment is critical.
You can do this alongside a job. Cohort 1 members did and shipped.
What you leave with
A product taken from idea to launch, with your name on it, that you shape and ship.
12+ portfolio artefacts. PRFAQ, specs, research, reviews, evals, and launch processes.
A role you have actually performed within an AI native team, not one you studied.
A work life balance team. Adaptable to life events. A team where you will practice EQ. The date doesn’t move, you ship it or write a COE (Correction of Error) with a documented path to launch.
A COE is what my AWS team wrote when we had to move the launch day of the Resource Search for 6 months weeks before the launch.
You will practice a real team experience with humans and agents.
Testimonials from Cohort 1
“Before joining the WonderLead program, I knew how to build projects, but I was more familiar with the way we create in startups. During the program we built the product from scratch. The turning point for me was learning how to approach problems the way they do at Amazon: focusing heavily on the customer pain point and working backwards from the client’s perspective. As a result, I learned techniques that work for me in the long run, like productization, AI, and communication methods.”
— Arturo Ortega, from Frontend Engineer to AI Engineer (watch video here)
“For those who want to explore different roles while working toward a clear goal, this cohort provides an excellent training environment. It offers both guidance and a supportive space to experiment, practice, and grow. Most importantly, it enables you to turn your efforts into a tangible outcome, something real you can showcase at the end of the experience.”
— Li-Chieh Huang, from UX Designer to UX Researcher AI Augmented
Where this comes from
At AWS I ran an AI literacy and adoption program across multiple organizations in Berlin. After nine months of getting engineers, designers and managers to actually change how they work, I identified what professionals in tech really need to successfully transition in this AI era.
What moves is connection and a safe space to experiment and share. Best practices aligned to keep judgment, practised in a team, on real work, with humans holding the bar.
Additionally, as part of the Design Your Career WonderLead workshop I executed at the beginning of the year, I met career transitioners and job seekers who followed WonderLead in Tech and asked to practice supporting WonderLead. So I built this cohort to support their growth instead.
Join AI Native Practitioner Cohort 2
If you want to join Cohort 2, founding price is available until Monday for IC roles and for the Leadership Track, where you lead the team as Engineering Manager or Tech Lead. Instalments are available. Full refund through Week 2.
With my direct coaching you practise the roles and levels that fit you best, while also practising work life balance, emotional intelligence and leadership.
You will become a WonderLead in tech.
LEARN MORE AND JOIN HERE: https://site.wonderlead.tech/practitioner/
Not sure if it fits you? Reply or send me a DM and tell me where you are right now.
I will tell you honestly what next step should be, even if it is not this cohort.
This Cohort and Opinions are my own