Not a classroom.
A proper workshop.
Everything you need to go from model idea to deployed product — in a community that will push you harder than you'd push yourself.
Weekly Model Sprints
Every week, the Labs run a focused experiment — a new model architecture, a new dataset, a real deployment challenge. You show up, you build, you share results. The pace is deliberate.
Shared GPU Compute
Serious model training requires serious hardware. Lab members get access to shared GPU resources so you can run the experiments that matter — without worrying about your cloud bill.
Global Dataset Library
A curated library of real-world datasets — agriculture, health, financial services, natural language. Real data from real contexts globally. Cleaned, documented, and ready for production-grade experiments.
Experiment Tracking
Shared MLflow and W&B workspaces so you can version runs, compare results, and build intelligently on each other's work. Science requires records.
Domain Expert Pairing
Every sprint pairs AI engineers with domain experts who understand the problem firsthand. Context — not just code — is the variable most AI projects get wrong.
Monthly Lab Showcases
Once a month, teams demo working software. Not slides, not decks — deployed products. The best work moves into the incubation pipeline. The rest teaches the whole community something real.
Build systems that
touch the physical world.
Software alone cannot solve the challenges facing agriculture, healthcare, infrastructure, and conservation. This track teaches you to deploy intelligence into the real world — through hardware that senses, decides, and acts.
You will design sensor networks, write production firmware, build real-time data pipelines, and deploy systems that operate under genuine constraints — unreliable power, no connectivity, harsh environments, and communities that depend on uptime.
Six capabilities.
One physical world.
The IoT track covers every layer of the stack — from firmware on the chip to dashboards in the operations centre.
Embedded Systems Programming
Write production firmware in MicroPython and C++ for Raspberry Pi, ESP32, and Arduino. Learn to think in microseconds, interrupts, and memory constraints — not abstractions.
Sensor Networks & Edge Computing
Design distributed sensor arrays that pre-process data at the edge. Understand power budgets, duty cycles, and why sending raw data to the cloud is always the wrong answer.
Real-Time Data Pipelines
Stream telemetry through MQTT brokers into time-series databases. Turn 10,000 sensor readings per minute into actionable operational intelligence.
Robotics Integration
Control servos, motors, and actuators with precision. Combine computer vision with ROS2 to build robots that perceive their environment and make real decisions.
Remote Monitoring Dashboards
Build operational dashboards in Grafana and Node-RED that field teams trust with their lives. Real-time alerting, anomaly detection, and multi-site visibility across unreliable networks.
Field Deployment Challenges
The lab simulates real-world constraints: intermittent connectivity, solar power budgets, dust, humidity, and hardware that fails at 3am. Build systems that work — not just in the lab.
Win the hackathon.
Then build the company.
Most teams lose before the judging starts. Not during the build — during the planning. They pick vague problems, build for imaginary users, and run out of scope with 12 hours left. This is the framework that fixes that.
A hackathon is 48 hours of compressed founding decisions. The problem you pick, the user you talk to, the feature you cut — all of it mirrors a real startup call made under real pressure. The teams that win are not faster. They are clearer. They made fewer wrong calls in the first three hours.
Six places teams lose
before judging starts.
Experienced judges see the same mistakes every event. These are the six. Most teams get two or three right. Get all six and you are already ahead of the room.
Clear Problem Statement
Write one sentence that names the problem, the person who has it, and what changes when it is solved. If three team members write this separately and the answers disagree, resolve it before anything else. Every build decision for the next 48 hours flows from this sentence.
Defined Team Roles
Assign three responsibilities before the clock starts: who builds the product, who tests it with real users during the build, and who owns the pitch. Gaps and overlaps in these roles cost more time than any technical problem you will encounter.
Controlled Scope
Identify the single user action that proves your solution works. Write it on a whiteboard. Every feature suggestion during the build gets measured against it — if it is not required for that action to succeed, it is out of scope.
Early User Validation
Before writing code, speak with two people who have the problem today. Ask what they currently do about it and what it costs them. Build for the person you interviewed. The insights from those two conversations will shape your pitch more than any feature you can add.
A Single Primary Metric
Agree on the one number your solution moves — time saved, cost reduced, cases detected per hour. Every product decision during the build is evaluated against this metric. If a feature does not move it, remove it from scope.
Demo-First Execution
Describe the demo out loud before a single line is written. Every screen, every transition, the exact moment the metric changes. Build only what that walkthrough requires. Scope creep always looks reasonable at hour five — and costs you the win at hour 47.
Finish something.
Not everything.
The graveyard of hackathon losses is full of half-built products with ten features. Four principles. Apply them before hour five and you will ship something that actually runs on demo day.
Define the Core User Action
Write one sentence: who does what, and what result they see. This sentence is the decision filter for every build choice from hour one to hour 47. When someone suggests adding a feature, measure it against this sentence. If it is not required for that action to succeed, remove it from scope.
Choose Your Execution Stack
Use the tools your team can debug under pressure without documentation. The right stack for a hackathon is the one you know well enough to fix at 3am on three hours of sleep. Performance and elegance are not the goal. A working endpoint in a familiar framework beats a half-built system in the optimal one.
Build a Visible Evidence Layer
Replace any placeholder data with real inputs and real outputs as early as possible. The demo needs something that changes on screen — a cost dropping, a classification appearing, a count incrementing. Judges assess working evidence, not described potential. If the number does not move, the value is not visible.
Document Your Fallback Protocol
For every live component — API call, model inference, database query — record a working result before demo day. Define each failure scenario and its response in advance. You have 48 hours of work invested. Do not allow the venue WiFi or an API rate limit to determine whether judges see it.
Judges have seen
a thousand demos.
What they almost never see is a team that can answer six business questions without fumbling. Know the answers before you walk in. That alone puts you ahead of most of the room.
Customer Definition
Name the specific person, not the category.
The county extension officer who spends three hours per week on manual crop reports. There are 40,000 of them in Kenya. This level of specificity is what separates a researched team from a guessing one — and experienced judges can tell the difference immediately.
Value Delivered
Describe their day without you, then with you.
Two sentences — what they do today and what changes when your product exists. If the difference is not concrete in those two sentences, the value proposition is not clear yet. This is the only element of your pitch that has to be genuinely undeniable.
Revenue Model
Who pays, how much, and when?
Name the payer — the user, their employer, a hospital, a government procurement office. Give a single number, not a range. Judges who have built companies will test this directly. A staged freemium plan is not a revenue model until you name the conversion point.
Market Size
Build your number from the ground up, not from a report.
40,000 maize farmers in Nakuru. Each loses Ksh 12,000 per season to late irrigation. Multiply. That is a credible bottom-up market calculation. A TAM figure from an industry research report carries no weight — your own arithmetic does.
First 100 Users
Name the specific channel and the specific first contact.
A WhatsApp group admin who manages 300 smallholder farmers and will send your onboarding link to the group on launch day — that is a distribution strategy. Social media is not. Name the person who gets you from zero to user one hundred without a paid budget.
Competitive Position
What does your team have that the next team cannot acquire in six months?
Field access accumulated over a year. A proprietary labelled dataset. An existing clinical relationship. A live user base. The answer that wins is specific and non-transferable. If a well-funded competitor could replicate it quickly, keep looking — there is usually a real advantage underneath.
Run it once before
it counts for real.
The Labs run a full hackathon simulation each quarter. Real brief, real judges, the same 48-hour window. Members who have done one simulation before entering a national event win at a rate that is hard to argue with.
Do the reps first.
One simulation before the real event. Low stakes, real pressure. The teams that have done it show up differently — and judges notice.
Join the LabsThe Robotics & IoT stack you'll master
The AI production stack you'll master
Lab access is for
serious builders.
You don't need to be an expert. You need to be willing to show up, run experiments, and learn in public — even when your model doesn't converge or your sensor gives the wrong reading at 3am.
Lab access is free.
Both tracks — AI Lab and Robotics & IoT — are included with every AI School membership. No extra cost. Just show up.
Join the LabsThe next sprint starts
when you show up.
AI, Robotics, IoT — the problems are real. The hardware is real. The community will not let you take shortcuts. Show up and build something that matters.
Get Lab Access