Elad Gil Investments: Portfolio and Lessons for Angels

Brian Nichols is the co-founder of Angel Squad, an angel investing community where aspiring and active angels learn from Hustle Fund’s approach, review curated deal flow, and connect with peers.

Elad Gil’s investments span some of tech’s best-known companies. His operating background and public investment thinking offer lessons on judging founders, spotting changes in a market, and being useful after writing a check.

Elad Gil’s portfolio and investment firm

Gil runs Gil&Co, a multi-stage investment firm. His public investment list includes:

• Payments and financial technology: Stripe, Square, Coinbase and Brex.
• Software and business operations: Figma, Notion, GitLab, Gusto, Rippling and Deel.
• Marketplaces and logistics: Airbnb, Instacart and Flexport.
• Artificial intelligence (AI): OpenAI, Anthropic, Perplexity and Cognition.
• Defense, transportation and space: Anduril, Applied Intuition, Waymo and SpaceX.

These are selected investments he names publicly. They span industries and stages, so treating them as a list of identical early angel checks would hide important differences.

For example, Harvey named Gil among the participants in its 2023 Series A. Applied Intuition named Gil among the investors leading its 2024 Series E. A Series A usually comes earlier in a company’s funding history than a Series E. The announcements describe company fundraising rounds; they don’t disclose Gil’s individual check sizes.

His AI involvement also includes different roles. He describes investing early in or leading rounds for companies including Abridge, Harvey and Mistral. He has also helped start companies such as Braintrust.

In his investor biography, Gil reports investing in approximately 40 unicorns. A unicorn is a privately held startup valued at $1 billion or more. That count doesn’t reveal his entry prices, ownership, losses elsewhere in the portfolio, or cash returned to investors. A familiar company name gives you a starting point for learning, not enough information to judge an investment’s return.

From Google and Twitter to angel investing

Gil worked on AI and mobile at Google, co-founded Mixer Labs, which Twitter acquired, and served as a Twitter vice president. He also co-founded Color Health. That background put him inside the work of building products, hiring teams and scaling organizations.

Operating experience can help an angel evaluate a startup before investing and support it afterward.

You don’t need Gil’s résumé to have an edge. A finance operator might understand a buyer’s budget cycle. A product leader might spot an onboarding problem. Someone who has sold software to hospitals might recognize a purchasing obstacle that a generalist misses.

Start with the problems you know well enough to ask a good second question. Then distinguish what you understand from what you’re assuming. Domain familiarity can improve your judgment, but it can also make a familiar idea feel safer than it is.

In our angel-investing community, we combine investing education, curated deal flow and peer learning. Comparing how investors with different operating backgrounds assess the same company can help you challenge your assumptions.

Members of Angel Squad at a Peninsula and South Bay meetup.

Founder quality, market demand and timing

These three lenses help organize a startup evaluation. Each needs evidence, and a weakness in one can change how you interpret the others.

Founder quality: look for learning and relevant strengths

In a 2021 founder interview, Gil describes four qualities he looks for: founder-market fit, rapid learning, ethics, and complementary team strengths.

Founder-market fit means the team’s skills and experience suit the problem. Rapid learning means taking in useful information and adapting. Complementary strengths can include someone who builds the product and someone who persuades customers, recruits or investors to commit.

In a founder conversation, ask for a recent example of customer feedback changing a decision. Listen for what the team heard, what it changed, and what happened afterward.

Consider a hypothetical team building scheduling software for clinics. A founder who can explain why its first pilot failed, how staff actually used the product, and what the team changed gives you more to evaluate than a polished claim about being customer-obsessed. Confidence matters less when it comes without evidence of learning.

Market demand: identify the buyer and the recurring need

A large market estimate on a pitch slide doesn’t tell you whether this startup can win paying customers.

For the clinic software example, separate the person using the tool from the person approving the purchase. Understand how clinics handle scheduling today, what the problem costs them, and what would make them switch. Then examine whether the startup can reach those buyers at a cost its business can support.

Gil also distinguishes metrics by stage in the same interview. Early on, adoption and retention can reveal whether users need a product. Retention is whether customers keep using or paying for the product.

Later, revenue growth, churn and expansion become more informative. Churn is the loss of customers or revenue. Expansion means existing customers spending more.

A pre-revenue pilot and an established subscription business need different evidence. Five enthusiastic pilot users don’t establish a repeatable sales process. Equally, demanding mature revenue metrics from a product still testing its first use case can obscure what you need to learn next.

Timing: explain what changed and why buyers can act

Timing needs a specific explanation. A new technical capability, lower cost, changing customer behavior or new distribution channel can make a business possible.

In his AI market analysis, Gil argues that improving model capabilities can unlock new applications. He also identifies obstacles beyond model performance, including buying behavior, distribution, difficulty switching from existing vendors and the team’s ability to build.

For our hypothetical clinic startup, suppose better speech recognition makes capturing appointment requests cheaper. That is a technical change. The commercial question is whether clinics trust the workflow, can integrate it into existing systems, and will pay for the result.

Write down both parts of the timing thesis: what became possible and what enables adoption. A wave of interest in AI, by itself, answers neither.

Useful support changes with the company

In the High Growth Handbook, Gil describes different levels of help across his investments. Some companies needed meaningful support; in others he was largely an observer. Needs also change over a company’s life.

An angel can apply that lesson by offering specific help and letting the founder decide whether it’s useful.

For the clinic startup, that could mean introducing an experienced clinic administrator, reviewing a sales-hiring plan, or helping the team understand a purchasing process. An introduction earns its value when the recipient is relevant and both sides want the conversation. Ten loosely targeted introductions can create work for the founder.

Agree on the scope of your help. Respect the team’s decisions and be candid about where your experience ends. Our guide to being a startup advisor explores that kind of practical support.

Turn the lessons into an evaluation process

A written process makes these lessons easier to apply across deals. Keep a short record for each company you evaluate:

1. Founder fit and learning. Record the relevant experience, complementary skills and a concrete example of adaptation.
2. Customer demand. Identify the buyer, current alternative and evidence that the need recurs. Match the evidence to the company’s stage.
3. Why now. Name the change enabling the business and the obstacles that could still slow adoption.
4. Your contribution. Specify one useful thing you can realistically do. Leave this blank if you have no relevant help to offer.
5. Reasons to pass. Write down the strongest objection, what remains uncertain and what evidence would change your view.

Use the same questions across deals, then revisit your notes as new information arrives. This makes it easier to spot when you consistently overvalue a compelling founder story or overlook a difficult sales process. Your decision also depends on the valuation and investment terms, even when the business looks appealing. Sandy Naidu’s five-part evaluation framework brings together team, target market, technology, traction (evidence of customer progress) and terms.

Our co-founder and general partner Elizabeth Yin writes in Democratizing Knowledge, “The more disciplined you are in your thought process/rubric, the more you can improve over time.” A written process gives you something to improve.

Portfolio thinking belongs alongside deal evaluation. In the same book, Elizabeth Yin writes, “Select a portfolio.”

A list of successful investments leaves out the uncertainty that existed when each decision was made. Luck affects outcomes, and thoughtful investors can disagree about the same company. Startup investing is risky, most bets may fail, and diversification cannot prevent losses.

Set a total startup-investing budget you can afford to lose before deciding how individual deals fit within it. Avoid sizing a check around a famous investor’s participation.

If you want to practice evaluating startup deals with other investors, apply to Angel Squad.

This content is for educational purposes only and is not investment advice or a recommendation to buy or sell any security. Startup investments are speculative, illiquid (hard to sell) and long-term, and you can lose your entire investment.