A useful solution, built and tested
Work on a real problem, test it with the person it is for, and hand over the work with a short guide and its known limits.
For universities, organisations and foundations
We help the next generation find their path in the future of work.
Bring our four-week accelerator to the students you teach or the professionals you employ. Working on a real challenge set by an organisation doing work that matters, they develop the direction, skills and judgement to thrive with AI, and gain practical experience of the kind a first job used to provide.
Eight live sessions. No coding experience needed.
Organisations we have worked with
Why we do this
People should grow with AI.
AI should expand what people can do, not diminish it. It should give them more say over their working lives, and the ability to build things they once needed a whole team to attempt.
Yet the tasks that once taught young people how work is done are increasingly the ones AI does first. The experience that used to come with a first job is getting harder to find.
That is why human agency sits at the centre of what we do: young people's ability to learn, contribute and shape an AI-driven world. Participants work with organisations tackling challenges in areas such as humanitarian action, education and social development, learning by contributing to work that matters.
What each person takes away
Participants work in teams of three to five on a real problem from a Challenge Partner, an organisation that brings the challenge.
Their own AI workspace
Set up AI with their own materials and instructions. Practise giving it work, checking results and deciding what to use.
A plan for their next steps
Map how AI could change the work they do or want to do, and decide what to learn, try and pursue next.
Their own view of AI
Discuss difficult choices and write a stance they can explain, including which decisions they would keep for themselves.
We assess each person on their own work. Each participant demonstrates what they did and explains their decisions. The shared team result does not determine their individual assessment.
At the final, each person presents their AI workspace and contribution to the challenge, a career plan, and a brief connecting changes in AI to their own practice and stance.
How you can take part
Universities, organisations and foundations each play a part. Your institution can take on more than one role.
Host
Bring participants
Bring people you teach, employ or support, and help connect the programme with suitable Challenge Partners. A cohort can include up to 40 people.
Discuss hosting
Challenge Partner
Bring a real challenge
Bring a problem a small team can work on over four weeks, from humanitarian action to education and social development. Introduce it, help participants understand the problem, and review the final work.
Discuss a challenge
Sponsor
Fund someone’s place
Cover the cost for students or professionals who could not otherwise join. A host brings the participants and a Partner brings the challenge. You help make sure people who need it can take part.
Discuss sponsoringEach Challenge Partner works with at least two teams. Alongside the Partner's three meetings, the person who would use the solution takes part in testing during sessions 6 and 7.
Ugo and Madison currently lead all eight sessions, guiding participants through workspace setup, the project and the final presentation.
How the four weeks run
Every session combines work on your challenge, personal AI operating system, career roadmap and stance on AI. What you learn in one shapes the others.
Your challenge shipped
Your personal operating system
Your career roadmap
Your stance on AI
Week 1 Get started with your team and AI
Session 1 Set up your workspace
- Challenge
Meet your team and read the Challenge Partner’s brief.
- Personal OS
Set up your AI workspace with your files and instructions.
- Career roadmap
Map how AI could change your current or future work.
- Stance on AI
Discuss how AI could change your job prospects and your say at work.
Session 2 Define the challenge
Partner introduces the challenge- Challenge
Ask the Partner questions and agree what your team will work on.
- Personal OS
Write instructions that explain how you work and what matters to you.
- Career roadmap
Explain why this challenge matters to your next steps.
- Stance on AI
Examine when AI helps you learn. Write your first stance on using it.
- Challenge
Week 2 Understand the problem and explore approaches
Session 3 Understand the user’s work
- Challenge
Map the intended user’s work and identify where AI could help.
- Personal OS
Save useful context so you can build on previous conversations.
- Career roadmap
Choose who you want to help and the difference you want to make.
- Stance on AI
Consider who else is affected when you change how someone works.
Session 4 Compare possible solutions
- Challenge
Prepare three approaches for the Partner, including what each would test and cost.
- Personal OS
Question your AI’s answers and save instructions for a recurring task.
- Career roadmap
Choose what to learn next and find people learning it.
- Stance on AI
Examine the energy and resources your use of AI requires.
- Challenge
Week 3 Build, test and improve
Session 5 Build the first version
Partner chooses an approach- Challenge
Build the approach the Partner chooses and test it on a real case.
- Personal OS
Set limits on what AI can do independently as you build the workflow.
- Career roadmap
Choose a measurable result that shows your contribution.
- Stance on AI
Discuss how the location of your AI provider affects control over your data.
Session 6 Test with the intended user
- Challenge
Watch the user try your solution. Measure what changes as you improve it.
- Personal OS
Add an AI agent to check work against examples you graded yourself.
- Career roadmap
Map the people you can turn to and start one collaboration.
- Stance on AI
Discuss who owns AI-generated work and how its sources should be recognised.
- Challenge
Week 4 Hand over the work and plan what comes next
Session 7 Prepare the handover
- Challenge
Stop adding features. Watch the user follow your guide alone and improve unclear instructions.
- Personal OS
Schedule checks and review which files and actions your AI can access.
- Career roadmap
Share what you learned where the people you want to reach gather.
- Stance on AI
Decide what needs human supervision and what a scheduled checker should record.
Session 8 Present your work and take it forward
Partner receives the handover- Challenge
Demonstrate your solution to the Partner and hand over the files.
- Personal OS
Adapt your personal operating system to a task from your week.
- Career roadmap
Finish your roadmap, including work boundaries, and discuss it with your team.
- Stance on AI
Examine how AI influences your choices and finish your stance.
- Challenge
Where we are going
The Accelerator is where we start
The four-week Accelerator is our first programme, not our whole purpose. Everything we do serves one aim: young people with the capabilities, judgement, creativity and agency to take part in, and help shape, a society changed by AI.
We are building an international network of partners around Future of Work Lab, with each relationship contributing practical support to our programmes through funding, expertise, real challenges or delivery.
Over time, we will prepare other facilitators to deliver the programme, extending its reach beyond the founding team. We also expect to widen our programmes beyond AI skills to the broader capabilities young people need.
FOUNDERS
Meet the founders
Ugo Bot
CO-FOUNDER, FUTURE OF WORK LAB
Ugo co-founded Future of Work Lab to give young people the experience their first jobs used to provide, by working on real challenges set by partner organisations. He has worked with the United Nations on systemic problems, set up and ran an innovation accelerator for social change in San Francisco, and led talent accelerators for students and professionals across Europe, Latin America, Africa, the Middle East and the Gulf.
His current focus is personal AI operating systems, which help people use AI to widen what they can imagine and build while keeping the decisions that matter in their own hands.
Madison Bonovich
CO-FOUNDER, FUTURE OF WORK LAB
Madison co-founded Future of Work Lab around one question: what is meaningful work when intelligence becomes abundant? She ran her own company for more than eight years, worked at the United Nations on complex global challenges, and works with universities and leadership programmes to bring AI and new ways of working into their curricula.
Her approach is that people should direct AI the way a good manager leads a team: brief it well, delegate real work, review the output and raise the standard.
Questions you may have
When could it run?
Four weeks, eight live sessions, two a week, online or in person. We set the start date with you so it fits a term or a quarter.
What does it cost?
We price a cohort, not a seat. A cohort is up to 40 people in teams of three to five, with one Challenge Partner for every two teams. A host or a foundation can fund the whole cohort, or a sponsor can pay for individual places. Tell us how many people you have in mind and we will come back with a figure.
How much time does it take?
Eight live sessions of three hours over four weeks, two a week. Between sessions, teams work on their challenge and each participant on their own setup. How much time that takes depends on the setting: a university that offers credit will ask for more documented hours than a company. We agree the load with you.
What do participants need?
A laptop they can install software on: a Mac running macOS 13 or later, or a Windows 10 or 11 machine. Any laptop from the last five years is fine. Locked company laptops are the usual problem, so if your participants use one, we talk to your IT team before the cohort starts. Included in the price: two months of a Claude or ChatGPT Team subscription per participant, the desktop app (Claude Code or Codex) the personal AI OS runs on, and a Slack workspace for the cohort.
Who finds the Challenge Partners?
We do, with you. Each accelerator runs on a challenge theme, and we curate Partners around it: organisations from a host's network, from a sponsor's, or from ours. A host introduces us to the ones they would like to involve, and we take it from there. Sponsors and foundations often become Partners themselves.
What does a Challenge Partner commit to?
About eight hours of one person's time over four weeks. A one-page brief before the cohort starts. Presenting it to the team in session 2. Choosing between the team's three options in session 5. Receiving the handover in session 8. One person from the Partner who will actually use what is built joins testing in sessions 6 and 7. After the handover, the Partner can implement the solution on its own, or continue with the team if everyone involved wants to.
Can a university offer credit?
Yes. The programme fits the shape universities already recognise: an internship-substitute or laboratory activity worth around 6 credits, with 24 contact hours plus documented individual and team work, assessed on the outputs and a live final demonstration. We adapt the hours and the assessment to your regulations and can share the proposal text as a template.
Who owns the work?
Three things are built and they have three owners. Each participant owns their personal AI operating system and takes it with them. The team's solution to the challenge is handed to the Partner in session 8, with the Partner and the team free to continue together or apart. What each person learned is theirs to show, and we ask permission before we share any of it.
How is sensitive information handled?
By default, teams work only on public material and on what the Partner chooses to share in the brief. A Partner who wants the team to use internal data signs a confidentiality agreement with the participants before the cohort starts, and we help draft it. Nothing a Partner shares is used outside the team that received it.
What does a sponsor receive as evidence?
Three things, at the end of the four weeks. An invitation to the final session, where each team demonstrates its solution live to its Challenge Partner. A short report from us on the cohort: attendance, what each team built and handed over, and what the participants say they will do next. And, where participants agree, their own work: the personal AI operating system they built, the roadmap they wrote, and a line from them on what changed. We ask each participant's permission before anything with their name on it reaches a sponsor.
Let's build a pro-human future together.
We build each accelerator around you: your organisation's focus, and what the students and professionals you work with need. Tell us who they are and whether you would like to host, bring a challenge or fund someone's place.
ugo@futureofworklab.co