How to raise money: Advice from a founder who raised $1 billion. | VC & Startup Jobs.
CAIR metric can predicts your AI product success & Data room guide for founders.
👋 Hey, Sahil here! Welcome to this bi-weekly venture curator newsletter, where we dive into the world of startups, growth, product building, and venture capital. In today’s newsletter -
Deep Dive: How to raise money: Advice from a founder who raised $1 billion.
Quick Dive:
The overlooked metric- CAIR, that predicts AI product success.
The data room guide you’ll ever need as a founder: download these templates.
Major News: Musk’s SpaceX may invest $2 billion in xAI, OpenAI delays release of open model indefinitely, Goldman Sachs is testing viral AI agent Devin, Apple Vision Pro 2 could launch this year, AWS to launch AI agent marketplace & Google adds image-to-video generation to Veo 3.
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📜 TODAY’S DEEP DIVE
How to raise money? - Advice from a founder who raised $1 billion.
The probability of success for a high-growth company is predicated on your ability to raise capital. As a leader, you will never achieve your maximum entrepreneurial potential without being able to raise capital quickly and successfully.
Capital is the lifeblood of any high-growth company. It has to be treated as a key priority. It can never be outsourced or downgraded to a second priority.
Brett Adcock, the founder and CEO of Figure AI, secured $70 million in its Series A funding round in 2023. Also his previous ventures, Adcock has successfully raised significant capital: Vettery was acquired for $110 million, Archer Aviation went public with a valuation of $2.7 billion and raised over $1 billion.
He shared the framework for founders to raise capital. So read along -
“Remember - Investors are looking for certain traits. Without these, you have little chance of raising a single dollar. Let's talk about how you can use the formula to build a repeatable process for raising capital.
Fundraising Formula:
You need to maximise the number of shots on goal in fundraising. Aim to get as many meeting attempts with investors as possible. The above formula for capital raising is a combination of -
The number of qualified investors you are targeting, combined with
The company's idea & overall branding.
The first step in the fundraising process is defining success.
The ultimate goal is to raise capital successfully. If you work backwards from there, getting to a lead investor's "term sheet" is the next clear milestone. And if you work backwards once more, the goal is to maximise the number of unique investor meetings.
The Fundraising Formula is a way to compute how to maximise the number of qualified investor meetings. Fundraising is about talking to 200 investors and finding the 1 person who will take a bet on you. I've always experienced low conversion rates in these efforts - it's never been easy for me to raise capital. And that's quite normal.
Here is the sensitivity to each part of the formula:
Qualified investors: You want to drive this number as high as possible. I speak to so many founders who are "waiting for referrals". This inevitably means this number is too low. You want to identify every possible investor on the planet, or else your equation will point to low odds of success.
Outreach: This is your outreach process to investors. I gauge this as a percentage conversion rate. This will be really sensitive to the way you are reaching out (referral vs. cold email) and the messaging associated with the reach-out process (e.g. subject and body of a cold email). There is an art to this. The percentage conversion rate can greatly increase if you treat it as a recursive project to get better.
Idea: This is the company's idea, and it's fixed. There is very little you can do besides pivot your company to a new idea. The idea will instantly either A) resonate or B) turn off investors based on their industry focus or their internal thesis of the market/industry.
Branding: This is how well-branded or attractive your company is at first glance. You have a limited time to impress an investor enough for them to commit to a meeting. There are many ways to drive this up, including a nice investor deck. But ultimately, that's a small lever, so don't stress too much over this.
Investor Meetings: This is the output of all your hard work. The goal is to drive up the number of qualified investor meetings as high as possible. You want to do 50-200 of these meetings. The more qualified investor meetings, the higher your odds of raising capital.
Building the Fundraising Machine:
I believe in building and executing on a highly structured "machine" for fundraising processes. This machine is something you can wash, rinse, and repeat. This should be similar to how you would run a sales or marketing team.
I track this process in a Google sheet, similar to how you track items in a CRM. Let's break down the key elements of the formula so you can go out and execute it yourself.
Key Elements of a Fundraising Machine:
Qualified List of Investors: This is a list of investors who are tailored specifically to your company. Start with investment groups that match well with your company sector. Research to find an investment partner who covers your specific industry and maturity. Ideally, you have found 100% of every investor on the planet that you think could give you a term sheet.
Outreach Process: Reach out to investors to set up a meeting. Try to get as many referrals as possible, then move to outbound for the rest.
Pitching: Your first interaction with the investor includes them previewing the deck. Optimise the conversion rate from the first meeting to the term sheet.
Term Sheet: Receiving a term sheet is the ultimate goal for the first leg of capital raising. Negotiate quickly and fairly to get the lead investor signed up.
The entire process from start to finish will take at least 3 months.
Spend 30 days preparing the investor deck, data room, mapping out investors, and your cold email template.
The next 30-60 days are for investor outreach and meetings. Once you have a term sheet, it generally takes <10 days to negotiate and sign, and you usually close in 30 days.
Additional Capital Raising Insights:
Show metrics and customers that can potentially correlate to long-term success for early investors to understand your product's potential.
Understand VC mandates and match them to your industry to avoid spinning your wheels.
Showcase your "Championship Team" - there's no way you're building a great product without a #1 team.
Aim for 80% of investor pitches to come from outbound processes (cold calls or emails) and 20% from inbound processes (referrals).
Build a well-branded investor deck as it's often the first impression investors have.
Recognise that interested investors move quickly. If they're not hurrying, it's likely a sign you don't have a deal.
Focus on finding a "lead" investor who can give you a term sheet and lead your round.
Balance fundraising time with product development, as fundraising can be distracting for founders.
Remember, fundraising is a competitive process. Once the round is complete, put your attention back to the product and get building.
I suggest setting up a quarterly "nurture" sequence to keep investors updated.”
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📃 QUICK DIVES
1. The overlooked metric-CAIR, that predicts AI product success.
If your AI product isn’t seeing adoption, the issue might not be the tech; it might be how confident users feel using it.
Most teams building AI products obsess over model accuracy. They test precision, tune parameters, and improve performance. But after watching dozens of launches and failures, product leaders like Assaf Elovic (Head of AI at Monday) realised something strange:
Some AI products with mediocre models gain traction fast. Others with great accuracy completely flop.
So what’s going on?
The answer lies in a concept called CAIR - Confidence in AI Results. It’s a simple but powerful idea: People don’t adopt what they don’t trust.
And trust isn't just emotional, it's designable, measurable, and improvable. CAIR gives teams a framework for doing exactly that.
What is CAIR?
At its core, CAIR is a score that reflects how confident a user feels in the AI's output.
The formula is: CAIR = Value ÷ (Risk × Correction Effort)
Here’s what each variable means:
Value: How helpful the AI is when it works.
Risk: What goes wrong if it makes a mistake?
Correction: How much effort does it take to fix a bad result?
If an AI tool saves you time and is easy to undo if it fails, CAIR is high.
If a mistake has big consequences and is hard to fix, CAIR drops fast.
This metric explains why even good AI gets ignored and how to fix that.
Example: Why Cursor’s AI coding tool took off
Cursor, the AI-powered code editor, became a favourite among developers. But coding is risky; what if the AI writes buggy code?
Let’s break it down:
Risk: Low — the AI runs in a local editor, far from production.
Correction: Low — devs can delete or overwrite code instantly.
Value: High — saves hours on repetitive coding tasks.
Result: High CAIR - Developers trust it. They feel in control. They adopt it.
Now, imagine Cursor's auto-deployed code to production servers. The Risk jumps to High, even if Correction stays manageable.
New CAIR = Much lower - Adoption would likely suffer, even with the same model accuracy.
What about AI tools like Monday.com?
Monday AI can automate workflows instantly. That’s powerful, but also risky. What if it triggers the wrong action across a business-critical board?
Risk: Medium — real data, real impact.
Correction: Medium — complex to undo across systems.
Value: High — major time savings.
CAIR: Moderate.
Here’s the insight: Adding a preview screen could change everything. If users see what the AI will do before it’s deployed, the Risk drops from Medium to Low.
Result: Higher CAIR → More adoption.
This shows how product design, not just model tuning, can dramatically increase AI success.
Some fields, like finance and healthcare, have built-in limitations:
Mistakes are expensive
LLMs aren’t great at math or precision
Regulations demand high reliability
Take tax software, for example.
An AI that auto-files returns without human checks? CAIR = Very Low
(High Value ÷ High Risk × High Correction)
But TurboTax uses a human-in-the-loop system. The AI suggests optimisations. A human approves. Confidence rises.
Same with Wealthfront and healthcare diagnostics: AI does pattern recognition, humans stay in charge of math and decisions.
Designing around limitations beats waiting for perfect models. So, how to improve CAIT ( Confidence in AI Results)
Here are 5 quick ways to boost your AI product’s CAIR, without changing the model:
Strategic human-in-the-loop: Add human checks only at key decision points to prevent major errors without slowing things down.
Reversibility: Make every AI action easy to undo to reduce anxiety and build trust.
Consequence isolation: Let users test AI safely with drafts, previews, or sandboxes before going live.
Transparency: Explain why the AI decided so that users can trust, verify, and fix when needed.
Control gradients: Start with low-risk features and gradually offer more power as user confidence grows.
Why this matters for product builders
Here’s the mindset shift:
Instead of asking, “Is the AI good enough?”, start asking, “Do users feel confident enough to use it?”
Because a well-designed, medium-accuracy AI can outperform a high-accuracy system with poor UX.
Your product’s success doesn’t hinge on a 99% model. It hinges on:
How mistakes are handled
How are risks communicated
How much control the user retains
And most importantly: How confident the user feels hitting that first button.
You can read the original article here.
2. The data room guide you’ll ever need as a founder: download these templates.
As a first-time founder, you might find yourself in a similar situation - excited about a positive response from a potential investor, but suddenly faced with an unfamiliar term: "data room."
A data room is essentially a secure, organised collection of documents that provides detailed information about your company. It's a tool for due diligence, allowing potential investors to dive deep into your business's financials, operations, and potential.
In early-stage venture deals, data rooms play a crucial role at two distinct stages of the investment process.
Stage 1: Pre-Term Sheet
At this point, investors typically have limited information about the company, relying mainly on the pitch deck, website, and publicly available data. They request access to a preliminary data room to perform a quick spot check and gather material for internal discussions with their partners.
This Stage 1 data room helps investors validate their initial interest.
Here’s a list of the 5 sections and types of content you’ll want to include in your stage 1 data room:
Business Summary / Company Overview
Purpose: provide an overview of the problem you are solving, your solution, and competitors - make it easy for the investor to create a deal memo
Docs to include:
1-page business overview
Links to your company website and social platforms
A PDF copy of your current pitch deck
Traction / Product Market Fit
Purpose: provide data that proves you’re solving a real problem - better yet, with a solution to a problem that a lot of people have and are willing to pay meaningful dollars for
Docs to include:
Market sizing - bottom-up or top-down TAM backed by relevant up-to-date data from reputable sources
Customer / User data - how many customers or users do you currently have, and how engaged are they
Competitive positioning / Unique Selling Proposition (USP)
Customer acquisition data - CAC, CAC payback
Financials
Purpose: provide a financial overview of your business from the day you started to the present day, with forward-facing projections.
Docs to include:
P&L / Income Statement, Balance Sheet, Cashflow Statement, Financial Projections 1-3 years in the future
Team & Roles
Purpose: provide an overview of your team, their experience, and the roles they play in your business
Docs to include:
Brief profiles on each team member, their role, their prior work experience, their time with the company, and links to their social channels (LinkedIn)
Cap Table
Purpose: provide an overview of who owns equity in the business today.
Docs to include:
Cap table summary
Stage 2: Post-Term Sheet
After receiving and negotiating a term sheet, you enter Stage 2 of the data room process. This stage is crucial for streamlining due diligence before any final agreements are signed.
It's wise to create a separate, more detailed data room for this phase, rather than just expanding your Stage 1 room.
This approach gives you better control and flexibility, especially when dealing with multiple investors at different stages.
Here’s a list of additional sections and content you’ll want to include:
Entity Formation Documents
Purpose: These documents are mostly needed by the legal team and are a set of documents used to certify your business’s good standing. These docs are going to fluctuate based on where your business is incorporated and the type of business entity you’ve chosen.
Docs to include:
Shareholder certificate documents
Local/state/federal business licenses/letters of good standing
Articles of incorporation
Bylaws, Tax ID number, Operating agreement between founders, Shareholder meeting minutes/board minutes, Annual meeting notes/minutes
Customer & Partner Contracts
Purpose: Material agreements will vary from company to company based on the nature of the business, but the general gist is to include anything that could significantly impact the business
Docs to include:
Standard terms of service or use between your business and customers
Any agreements or understandings between your company and others with obligations exceeding $25K
Property leases (real estate and personal)
Licenses of any company's IP to 3rd parties
Proof of Intellectual Property
Purpose: If your company has IP and that was part of the pitch, you’re going to have to show proof of that IP. This includes patents, trademarks, copyright, and design
Docs to include:
Evidence that you have the right to the IP that you’re developing
Patent information (proof of filing/issuing)
Trademark registrations
Copyrights
Full cap table documents
Purpose: If you’ve followed this guide, you’ve already shared a summary of your cap table. At stage 2, you’ll likely need to divulge additional details such as:
Docs to include:
Details of previous fundraising rounds or liquidity events
Shareholder certificates
Vesting schedules
ESOP details
Tax Filings
Purpose: Proof that your company is in good standing with the IRS
Docs to include: Tax History, Previous filings, Previous audit statements and any third-party financial evaluations
Information on Any Outstanding Litigation
Purpose: This one is key…failure to divulge pending or outstanding litigation can and will likely result in a very bad outcome for you and your business. Be honest here, have a hard conversation with the investor at this stage in the process.
Also, we have created a detailed guide and included all relevant templates that you need for your data room. All these curated with the help of startups attorneys, VCs. You can access it here:
Startup Legal Document Pack – Essential Legal Docs for Founders.
THIS WEEK’S NEWS RECAP
🗞️ Major News In Tech, VC, & Startup Funding
New In VC
Propel Venture Partners, a San Francisco, CA-based seed-stage venture capital firm investing in the infrastructure, closed its Fund V at $100m. (Read)
Multiball Capital, a Los Angeles, CA-based venture capital firm, is raising $25m for its maiden fund. (Read)
Sarah Smith Fund, a solo GP firm founded by ex-Bain Capital Ventures investor Sarah Smith, has closed a $16M Fund I. (Read)
Major Tech Updates
OpenAI CEO Sam Altman announced an indefinite delay of its open model release, citing the need for further safety testing and risk reviews. (Read)
Goldman Sachs is piloting Cognition’s AI coding agent Devin to augment its 12,000-person developer workforce, potentially deploying thousands of instances. (Read)
OpenAI’s $3 billion deal to acquire AI coding startup Windsurf has fallen through; instead, Google DeepMind is hiring Windsurf CEO Varun Mohan, co-founder Douglas Chen, and top researchers. (Read)
Google has introduced image-to-video generation to its Veo 3 AI model through the Gemini app, following an earlier rollout in the Flow tool. (Read)
The new Apple Vision Pro will reportedly feature an M4 chip, a significant performance upgrade compared to the M2 chip found in the original headset. (Read)
New Startup Deals
SpaceX is reportedly set to invest $2 billion in Elon Musk’s AI startup xAI as part of a $5 billion equity raise led by Morgan Stanley. (Read)
Blok, a San Francisco, CA-based startup that builds AI agents to improve product experimentation, raised $5m in seed funding. (Read)
RealSense, a Santa Clara, CA-based company which specializes in AI-powered computer vision, raised $50M Series A funding. (Read)
Harmonic, a Palo Alto, CA-based artificial intelligence lab leading the development of Mathematical Superintelligence (MSI), raised $100m in Series B funding. (Read)
Knox, a NYC-based federal managed cloud provider, raised $6.5M in Seed funding. (Read)
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Thanks for sharing, very good read.