PitchLens

What Greylock looks for in a pitch deck

Greylock aims to be a founder's first partner from day one: with Greylock 17, 'over 80% of the investments we made were Pre-Seed, Seed, or Series A,' and the firm 'expect[s] that every company will become an AI company.' Partners back highly technical, customer-obsessed founders building AI-first software that can rebuild existing categories from scratch — and they weight unique market insight and durable moats (data, network effects, scale) over headline TAM.

Stage focus: seed, Series A · Sectors: ai, cybersecurity, infrastructure, saas, consumer, marketplaces and commerce, fintech and crypto, vertical ai

What Greylock wants on each slide

Problem

Lead with the problem you are solving and the unique insight behind it; Greylock's own pitch checklist opens with the problem before the solution.

“What's the problem you are solving?” — How can I Pitch my Startup to Greylock?
“What's your proposition?” — Greylock
“Making the right foundational decisions, beginning with market identification and product definition, can have compounding effects.” — Saam Motamedi

Solution

An enduring, AI-first product (not a thin feature or wrapper) that uses technology to rebuild a category, ideally generating proprietary data through usage.

“I want to back founders who are willing to take the risk to build enduring, AI-enabled products that will change how people work and live.” — Product-Led AI | Greylock
“AI agents will perform the majority of the work and humans will check.” — Christine Kim
“Better data over better models.” — Christine Kim

Market size

A unique insight on a real, often constrained market beats a big top-down TAM number; Greylock partners are skeptical of TAM theater.

“I rarely pay attention to TAM. Instead, I look for a unique insight on a constrained market.” — Mike Duboe | Greylock
“AI is an enabling technology wave and it's shifting every category that we invest in.” — Saam Motamedi
“underserved but quickly growing segment...accounting for nearly 80% of the $320B total in the U.S.” — Christine Kim

Traction

Evidence of progress and learning velocity; a retentive foothold in one defined segment is a stronger signal than broad shallow usage. Greylock explicitly asks for traction and data.

“What traction (or other data) can you provide us to show your progress?” — How can I Pitch my Startup to Greylock?
“We built a solid foundation of highly retentive customers within one defined segment.” — Mike Duboe
“Growth is about building systems to accelerate a company's pace of learning.” — Mike Duboe

Team

Highly technical, customer-obsessed founders with one foot in industry and one in technology, deep market knowledge, and an obsessive drive — including early-career founders with unique insight.

“I love backing founders who are highly technical and customer-obsessed.” — Saam Motamedi | Greylock
“Why are you and your team the right folks to succeed on this opportunity?” — Greylock
“The best founders I work with are deeply curious & steeped in their market, yet maniacally driven to reinvent it.” — Mike Duboe
“We welcome founders with limited experience — in fact, I find partnering with early career founders with unique market insight, relevant technical expertise, and who are deeply commercial especially exciting.” — Saam Motamedi

Business model

A defensible model — beware being a thin layer on a model provider; build advantage through data, distribution and category ownership rather than a wrapper.

“If your theory of the game is a thin layer around the AI model, you'd better be playing on the trend of the large models, right?” — Intelligent Money | Greylock
“the most strategic advantage [of applications] is that you can coexist with several systems of record and collect all the data that passes through your product.” — Jerry Chen
“Who has invested in your company to date, or is committed to this round?” — Greylock

Competition

A real, durable moat — data specific to an industry/company, network effects, or scale. 'The new moats are the old moats.' Attack where incumbents aren't competing.

“The new moats are the old moats.” — The New New Moats | Greylock
“Products that use data specific to an industry or unique to a company to solve a strategic problem begin to look like a pretty deep moat.” — Jerry Chen
“the more data you generate and train on with your product, the better your models become and the better your product becomes.” — Jerry Chen
“Rather than being intimidated by the data and distribution advantage of incumbents, I encourage founders to find angles where incumbents are not competing at all.” — Seth Rosenberg

Why now

A credible reason this is the moment — the AI wave built on internet/mobile/cloud, with models improving fast enough to make previously impossible products viable.

“This is a wave that couldn't happen without the internet, couldn't happen without mobile, couldn't happen without cloud. But it's building upon all three. It's the crescendo of them.” — AI's Transformative Power | Greylock
“The thing that continues to surprise even us is how quickly and how significantly these models are improving.” — Saam Motamedi
“We expect that every company will become an AI company.” — Greylock

The ask

Clarity on company status and round: where the company is, who's already in, and what's committed. Best entry is a warm intro to the relevant partner.

“What status is your company/opportunity?” — How can I Pitch my Startup to Greylock?
“A warm introduction helps us tremendously.” — Greylock
“a bespoke company building program designed to advance select pre-idea, pre-seed and Seed founders...from inception to product market fit, with fully flexible financing options” — Greylock

What Greylock rewards and penalizes

What excites Greylock

  • Highly technical, customer-obsessed founders, including early-career founders with a unique, hard-won market insight
  • AI-first product that rebuilds a category from scratch rather than bolting AI onto a legacy workflow
  • Proprietary data flywheel — product usage generates a dataset that compounds the moat
  • A retentive foothold in one clearly defined segment, with evidence of fast learning velocity
  • Agentic products that perform real high-value work, not just copilots
  • Warm introduction to the relevant partner and a concise problem-first pitch

Watch-outs for Greylock

  • A thin wrapper / 'thin layer around the AI model' with no defensibility beyond the model provider's trend
  • Leading with a big top-down TAM number instead of a specific, unique market insight
  • Pursuing multiple business lines at once instead of dominating one segment ('trying to pursue three business lines at once was ultimately our achilles heel' — Mike Duboe)
  • Founders intimidated into competing head-on with incumbents' data/distribution rather than finding uncontested angles
  • Vague company status / unclear who is committed to the round

Who decides at Greylock

Saam Motamedi — General Partner (enterprise, AI, security)
“I love backing founders who are highly technical and customer-obsessed.”
Reid Hoffman — Partner (co-founder of LinkedIn; Inflection)
“This is a wave that couldn't happen without the internet, couldn't happen without mobile, couldn't happen without cloud. But it's building upon all three. It's the crescendo of them.”
Jerry Chen — Partner (enterprise, infrastructure, data/AI)
“The new moats are the old moats.”
Mike Duboe — Partner (consumer, commerce, marketplaces, growth)
“I rarely pay attention to TAM. Instead, I look for a unique insight on a constrained market.”
Seth Rosenberg — Partner (fintech, AI, consumer)
“I want to back founders who are willing to take the risk to build enduring, AI-enabled products that will change how people work and live.”

What Greylock actually backs

Where Greylock is thinking now

Greylock's published guidance

Benchmark your deck against Greylock →

PitchLens grades your deck slide-by-slide against Greylock's own published playbook, with a citation on every point.

← Browse all 124 VC firms · PitchLens home