Methodology
How I evaluate projects.
I look at every project on Lookout through seven axes — a framework I built after three years of asking the same questions in founder meetings and finding the same answers either short-circuit conviction or earn it.
The output is a tier, not a score. Numbers pretend to a precision the underlying judgement does not have. A tier is honest about that.
Framework
The seven axes.
- 01
Team & Execution
Who's shipping. Past output, founder pedigree, and the gap between what's promised and what's been built in the last 90 days. I care more about repeat builders than first-time pitchers.
- 02
Tech & Differentiation
What's actually new. Whether the core innovation is technical, distributional, or financial — and whether competitors can fast-follow in a quarter. I downweight 'AI + Crypto' framings that don't survive a second question.
- 03
Tokenomics & Economics
How value accrues. Supply schedule, sink/source balance, holder concentration at TGE, and whether the token has a real utility loop or is decoration on top of equity-style economics.
- 04
Traction & Adoption
Signal vs. noise. Real users, real revenue, real on-chain activity — not airdrop farming or wash transactions. Cohort retention beats top-line TVL every time.
- 05
Funding & Backers
Who's at the table. Investor quality, round structure, valuation discipline. A great lead investor signals diligence I don't have to redo. A messy cap table is a tell.
- 06
Narrative & Market Fit
Why now. Whether the project rides a structural shift or piggy-backs on a hype cycle. Lookout coverage favors projects positioned for 24-month theses, not 24-hour rotations.
- 07
Risk Vectors
What kills it. Regulatory exposure, smart-contract surface area, founder concentration, jurisdictional risk. Every project has risks — I name them before recommending.
Tier system
Three conviction levels.
Conviction
High confidence. Actively tracking for deal flow, intros, and follow-on coverage. These are the projects I'd put my own time and reputation behind.
Watching
Interesting but needs more signal. Strong on some axes, unproven on others. Worth following — not yet worth introducing to funds.
Skeptical
Red flags present. Tracking for learning only. Public exposure helps me document why I passed, so the next time the pattern shows up I move faster.
Ethics
I only introduce projects I personally back. If I have an advisory relationship with a project I’m recommending to a fund, I disclose it upfront. No hidden kickbacks, no pay-to-play coverage on Lookout.
AI-assisted research, human judgment. Not financial advice.