How do I pitch Air Street?

To pitch Air Street, practice against our AI simulation built from their investment thesis: I back AI-first companies where the model is the moat — founders who build intelligence into the product itself, not as a feature bolted on top. You have 30 minutes to answer real questions like What's the actual eval setup — public or private? and Where does the moat come from as foundation models commoditize?. Get a 12-dimension scored verdict.

What are Air Street's red flags?

Wrapper with no proprietary data or eval. No plan for evaluation at scale. Founders who don't engage with the actual research literature.

What sectors does Air Street invest in?

Air Street focuses on AI, Devtools.

What is the typical check size for Air Street?

Air Street typically writes checks between $1000000M and $10000000M.

AI simulation

How to Pitch Air Street

A practical guide based on our AI simulation of Air Street's investment thesis — distilled from public memos, interviews, and track record. Practice your pitch against the AI persona and get a 12-dimension scored verdict.

AI-generated from public data. Not official Air Street content.

Investment Thesis

I back AI-first companies where the model is the moat — founders who build intelligence into the product itself, not as a feature bolted on top.

What They Look For

Sectors

AIDevtools

Stages

SEEDSERIES_A

Typical check size: $1000000M – $10000000M

Red Flags

Things Air Street investors watch for — avoid these in your pitch.

Wrapper with no proprietary data or eval
No plan for evaluation at scale
Founders who don't engage with the actual research literature

Questions They'll Ask

Prepare answers for these. The AI persona will challenge you on them.

What's the actual eval setup — public or private?
Where does the moat come from as foundation models commoditize?
What data flywheel are you building?
How does this look when the underlying model gets 10x better?

1 AI Persona to Pitch

Nathan Benaich

Founder & General Partner

Highly technical, opinionated on architectures, follows the model landscape daily. · Sharp, technical, pushy on evaluation and benchmarks. Asks for actual evals, not vibes.

Pitch Nathan

Ready to pitch?

Pitch the AI simulation of Air Street's thesis. Get a 12-dimension scored verdict. If you pass, your report surfaces to the real fund.

See Air Street personas

2 free pitches to start · 1 free every day