Ship fast.
Validate unit economics.
Scale, improve, or stop.
Level Up Factory researches markets, ranks ideas, builds with AI agents, generates and uploads ads, tests demand, and feeds every result back into the next decision.
The bottleneck moved from writing code to choosing what should exist.
AI makes building cheaper. The harder problems are selection, distribution, unit economics, and knowing when to keep going.
Selection
934 ideas are scored by buyer type, Max ARR, market size, users, build days, blockers, LTV/CAC, and strategy.
Runtime
DoItFor.Life turns OpenClaw into a managed product: dedicated Google Cloud VM, Gemini configured, chat connectors ready.
Feedback
Gemini-generated ads, Meta and Google publishing, activation data, objections, support notes, and ROAS feed the next ranking pass.
One loop turns market evidence into better products.
Every launch is both a product test and a factory training run.
The factory gets stronger even when a product does not work, because each result improves the selection engine, ads playbook, launch checklist, and scale/stop thresholds.
DoItFor.Life turns OpenClaw into a managed consumer agent.
A user registers, gets a dedicated Google Cloud VM with OpenClaw and Gemini configured, then delegates through Telegram or WhatsApp. The target is non-technical users who want outcomes, not infrastructure.
What gets provisioned
- Dedicated Google Cloud VM per user
- OpenClaw installed and preconfigured
- Gemini API configured through Vertex AI
- Telegram/WhatsApp connector ready for first task
- Guardian and support automation for runtime health
Early signal
The core asset is a self-learning research dashboard.
The engine ranks opportunities before build, then learns from product launches, ad results, support signals, and founder notes.
Products are proof points. The factory is the compounding asset.
Level Up Basketball
Flagship proof: 500K users, AI Coach growth, and consumer distribution experience.
DoItFor.Life
Managed OpenClaw runtime and current agent-infrastructure wedge.
Deck Review
Productized selection framework for startup and market research.
DoneCo
Internal dashboard connecting founder tasks and agent work reports.
Speedrun materials in website form.
Short, linkable pages for a16z Speedrun review and warm introductions.
Technical founder plus paid-growth scar tissue.
Eugene previously led MAPS.ME to 150M users and helped grow LitRes from $50K MRR to $15M ARR. Danil adds deep product and engineering leadership. The edge is combining AI infrastructure with funnels, creative testing, paid acquisition, and unit economics.