
System Capabilities
Every component of the accelerator is designed to produce artifacts, maintain pacing, and ensure founders ship — not just learn.
Structured execution-first learning from AI literacy to scale
Every lesson produces tangible outputs, not just knowledge
Time-budgeted lessons with difficulty ratings and duration labels
Real-time progress tracking, pacing adherence, and execution scores
AI interaction frameworks, prompt templates, and automation pipelines
Built-in guardrails prevent overbuilding and cognitive overload
What You Will Use Every Week
Interactive previews of the tools you will use daily — dashboard templates, artifact submission flows, progress metrics, and execution streak tracking.
82%
Execution Score
14/42
Lessons Done
8/28
Artifacts
4 wks
Weekly Streak
Know Before You Start
Every phase and lesson has estimated video time, execution time, and total weekly load. No surprises — you know exactly what each week requires.
13h
Total Program
1.1h
Avg Weekly
3h
Video/Reading
10h
Execution
8–12 hrs/week
Recommended pace for on-track completion
Execution-Heavy
70%+ of time is hands-on building, not watching
Adaptive Pacing
Go faster or slower based on your schedule
Mission Trajectory
A structured journey from AI literacy to scalable product, with validation gates at every phase to prevent overbuilding.
Build your foundational understanding of AI systems, tools, and thinking frameworks. Learn to evaluate AI capabilities, understand automation boundaries, and develop your AI interaction model.
Identify and validate real problems worth solving. Use AI-assisted research to find underserved markets, validate pain points, and build your problem hypothesis.
Design your solution with AI-native thinking. Build your MVP specification, define your technical architecture, and create your execution roadmap.
Execute your build plan. Ship your MVP using AI-assisted development, automated testing, and rapid iteration cycles.
Put your MVP in front of real users. Run structured validation experiments, collect feedback, and iterate based on evidence.
Prepare for controlled live deployment. Build your launch strategy, set up monitoring, and prepare your go-to-market materials.
Tune your system for scale. Simplify workflows, refine pacing, eliminate friction, and improve artifact clarity for sustainable growth.
