Angel Investor | Help founders find their perfect investors | CEO and Founder of @USE4COINS and @Abbigli

I help founders and business owners use LinkedIn as a channel to start conversations with investors, build partnerships, and raise capital.

Author of the book
Get Funded: The Universal System to Raise Capital for Any Business, from First Contact to Investor Call.

Creator and host of two LinkedIn interview series.
Voice of the Creator conversations with creators and industry experts.
Behind the Fund discussions with venture investors about how funding decisions are really made.

My network brings together two sides of the startup ecosystem: investors and founders.

Today my work focuses on three areas:
• fundraising strategy and investor readiness
• LinkedIn visibility and strategic networking
• practical AI tools for modern business

If you are building a company and want to open doors to investors, partnerships, and international opportunities, feel free to connect

$7.8 billion today. $52.6 billion by 2030.
As a former robotics engineer who designed robotic systems, I kept running into one question: can a system decide on its own what to do next?

It turns out, yes.

What is an AI agent, really?

Forget the idea of a "smart chatbot." An agent is a system that perceives its environment, makes decisions, and takes action without your involvement at every step.

What is it made of, and why does that matter?

Five components. Not abstract ones, but practical ones:

1. Perception - the agent reads data from all kinds of sources: text, APIs, documents, sensors. These are its eyes.

2. Reasoning - the LLM core analyzes the situation and makes decisions. Not from a rigid script, but from context. This is its brain.

3. Memory - short-term memory for the current session and long-term memory for history and knowledge. Without memory, an agent is like a person starting from zero every time.

4. Planning - the agent breaks a big goal into steps, chooses the order of actions, and adjusts the plan when conditions change. This is exactly what simple bots do not have.

5. Tools - it calls APIs, writes and runs code, searches the internet, and sends emails. These are its hands.

Remove any one of these five components and the system stops being an agent. It becomes just another piece of software.

Why this changes not just technology, but economics

In robotics, an autonomous robot used to cost millions. Only a large factory could afford one.

Today, an agent costs $20 a month. One person with a laptop can launch it.

Norbert Wiener, the father of cybernetics, wrote in 1948: "We have changed our environment so radically that we must now change ourselves in order to live in this new environment."

He was talking about industrial machines. But the same idea applies to AI today.

Do not ask, "Do I need an AI agent?"

Ask instead: what task in my business can an agent already do better, faster, and cheaper today?

Start with one process: lead qualification, competitor monitoring, or handling inbound requests.

One agent. One result. Then scale.

Victor Sankin

I have founded and developed several business and IT startups in AI and e-commerce, including a group purchasing project. As an angel investor, I have invested in multiple startups—some successful, some not—but each investment has provided valuable experience. I study fundraising deeply as a science. Open to networking, new ideas, and collaboration. I share my knowledge and experience on this page. Looking forward to connecting!

Angel Investor | Fundraising | LinkedIn Visibility | Robotics & Neural Networks Specialist Helping founders find the right investors

A solo founder today can be more effective than a 10 person team was five years ago.
Garry Tan said he has written more code this year than in all of 2013, when he founded Posthaven. And he expects that output to grow another 20x by the end of 2026.

YC Demo Day W26 showed something important: the path from zero revenue to real ARR has become dramatically shorter.

23,000 applications. Less than 1% got in. Of the companies that were accepted, 70% applied with zero revenue. Today, 14 of them are already at $1M+ ARR. One is at $27M ARR at the seed stage.

For most startups, 10% month over month growth would be a great result. W26 is growing at 14% per week. This is not the top 10 companies in the batch. This is the average across 200 startups.

3x more companies reached $1M in annualized revenue than in W25. Rebel Fund, which has scored every YC batch since 2013, called W26 the best cohort in the accelerator’s history.

90% of the batch is AI companies.

This is not a trend. It is a change of era.

The question is not whether to use AI in business.

The question is how much time you have left while you are still thinking about it.

Everyone looks for ideas in the wrong place.
They look at what just raised a round. YC batches. Trends on Twitter. And they think: "This lowers my risk." Is that true? I don’t think so.

The main limitation today is not technology. The tools let you build almost anything. The real task is to find a unique idea. And you won’t find a unique idea where everyone else is already looking.

Try this: look for ideas that everyone has rejected.

Here are some examples

Twitch. Justin Kan put a camera on his head and started streaming his life 24/7. Any reasonable investor would say: "Is this a joke? What’s the TAM?" and they would be wrong.

Because ideas like this, strange, rejected, and hard to explain on paper, are the ones that create new categories.

Airbnb? The founders’ parents were worried. OpenAI? A non-profit research lab at the peak of SaaS. Strange squared.

Right now, two ideas come to mind.

Idea 1: AI that does not help on purpose.

Junior developers, lawyers, analysts are losing basic skills because AI does everything for them. In a few years, there may be no one left who can actually check the output.

The idea is a tool that makes you think first and only then helps you. It sounds strange: why pay for AI that helps less?

Idea 2: AI for people no one tries to automate.

Most AI products are built for top managers. But there are professions where people spend hours on paperwork and have almost no tools: social workers, probation officers, school psychologists.

The idea is to build AI specifically for them. It sounds even worse: small market, no attention.

Both ideas share one thing: they look bad on a pitch deck. That is exactly why they are worth looking at.

My advice

Consensus kills uniqueness. If everyone around you likes your idea, that is not a good sign. It means you are too close to the mainstream.

If something feels like it will take 10 years, that is your advantage. Most people cut it down to two years, so long bets face less competition.

Do not look for approval from authorities. If your filter is "will some expert like this", you have already lost.

Paul Graham did not have an investment background. He just built what he wished existed when he was a founder.

And that person built the most influential startup program in history.

Being strange is not a weakness. It is a requirement.

The-best-ideas-look-like-bad-ideas-at-first

A founder who cannot create visibility for themselves in 2026 looks like a startup without a website in 2005: technically it exists, but in practice it does not.

Investors live in a constant flow today: Twitter, LinkedIn, YouTube, newsletters. They do not search for startups. They come across people who consistently show: here is the problem, here is the solution, here is the growth.

Visibility is not vanity. It is a way to show that you have the mindset and character worthy of capital.

Here are three steps on LinkedIn that noticeably increase a founder’s chances of raising money.

Tip 1. Write as if you have already been asked the main question: “Why do you need money right now?”

Regularly show proof of demand: screenshots of user onboarding, retention metrics, growth in repeat usage, real customer quotes. Not “we launched an MVP,” but “we solved a specific pain point, and here is how you can see it in the numbers.”

An investor should feel one simple thing: if they pass on you, they may miss the next wave.

Use simple, human language, without fluff or jargon. A good post is a short essay that shows you understand your niche in detail.

Tip 2. Show yourself on LinkedIn not as a hero, but as someone who can handle hard moments

A founder’s path is not a series of wins. It is a chain of crises that some people get through, and others break under.

LinkedIn creates the temptation to turn yourself into a polished character. That is exactly what you should not do.

If you only write about success, you hide the qualities that really matter to investors: the ability to admit mistakes, change strategy, and take a hit.

It is much more honest to show moments when you were wrong, saw it clearly, and made it better. 

An investor reads your LinkedIn and tries to answer one simple question:

Will I be able to sleep well if I give this person a couple of million dollars and five years?

Help them answer “yes.”

Tip 3. Build relationships before you need money

The most common mistake is showing up on LinkedIn the day before your round with a series of anxious posts and cold messages to investors.

You need to build relationships long before fundraising starts.

On LinkedIn, it looks simple.

Make a short list of people you would like to be at the same cap table with one day: fund partners, angels, operators. 

Follow them, read what they write, respond to their posts with substance. Not “great post,” but a thoughtful comment that shows you can think at their level.

Post regular updates about your product and market as if they were investor letters: short, clear, numbers first, straight to the point.

Then by the time you come asking for money, you will not be a stranger in the inbox. You will be a familiar face with a clear trajectory.

Investors start reading you long before you write your first post saying: “We’re raising a round.”

There is only one question.

What exactly will they see in those months?

Use LinkedIn to your advantage.

If-founders-are-invisible-investors-dont-see-them

Anthropic built a certification most AI developers haven't seen yet.
Founders who catch this early win.
This isn't a course.
This is a test of whether you can actually ship production-grade apps with Claude - or just fake it.

It's called: Claude Certified Architect - Foundations.

Launched March 12, 2026.

Here's what the exam covers (60 questions, 5 domains):

→ 27% - Agentic Architecture & Orchestration
(loops, orchestration, hooks, guardrails - the stuff that breaks first in production)

→ 20% - Claude Code Configuration & Workflows
(you either know where config files go - or you don't)

→ 20% - Prompt Engineering & Structured Output
(not "chatting with AI" - engineering reliable, structured responses)

→ 18% - Tool Design & MCP Integration
(connecting Slack, GitHub, and databases - without duct-taping workarounds)

→ 15% - Context Management & Reliability
(keeping a 200K-token context window coherent under real load)

Price when it goes public: $99 per attempt.

Right now - partners only. The first 5,000 employees get in free.

The prep courses? Free for everyone. Right now.

Anthropic didn't launch this loudly.

No Product Hunt. No press release.

They simply created the first professional standard for people building with Claude.

On one side: people who use AI.

On the other: people who build with it.

That gap will only get more expensive to cross.

Are we actually training people to build AI systems - or just training them to click faster?

Save this. Share it with one founder.

In the second part of my conversation with Igor Ryabenkiy, founder and managing partner at AltaIR Capital, one idea stood out that, in my view, matters for investors.
Bad capital almost never looks bad at the beginning.

It looks disciplined. Careful. Professional. And almost always very involved.

But sometimes that involvement slowly starts to change the balance inside the company.

Igor points to three mistakes investors sometimes make even with good intentions.

The first is an overly rigid deal structure.

On paper, it protects capital. But if the deal structure takes decision-making room away from the founder, the company starts losing speed.

And for a startup, speed is part of survival.

The second mistake is trying to run the company.

An investor can often see things the team does not see yet.

How the market is reacting to the product. Timing risk. Weak spots in the strategy.

That is where experience creates value.

But there is a line.

An investor makes a company stronger when they share observations and help the team see the situation more clearly.

But they start making the company weaker when they try to run the business instead of the founder.

Startups work best when the founder leads and the investor supports. Not the other way around.

The third problem is behavior inside the deal itself.

Sometimes terms change at the last minute.

Heavy liquidation preferences appear.

And all of this comes with a line like: If you are building a unicorn, why worry?

But those terms do not disappear after signing.

They stay in the cap table. And those same terms can make the next round harder.

There is one more important idea.

Venture is not only about finding winners and unicorns. It is also about knowing how to accept losses.

If it becomes clear that a company cannot recover, sometimes the right decision is to take the loss and stop.

Continuing to invest in a project that has already lost its chance to grow rarely changes the outcome.

If you are an investor and you build companies with founders, not instead of them, message me.

I am doing a series of interviews with investors about how value is really created after the check has already been written.

Behind-the-fund-Igor-Ryabenkiy-AltaIR-VC-2

Recently, I hired a Founding Account Executive -the first salesperson who manages deals and builds the sales process.
Not because he had the best resume.
But because of how he used LinkedIn.
Not the design. Not big words. But the way he showed his work. No "sales guru" tone.He simply wrote about his results.

How he changed the ICP (Ideal Customer Profile the portrait of the ideal customer).

How he rewrote outbound messages (cold messages to potential clients).

How he improved reply rate (the percentage of people who replied to messages).

How interest turned into meetings.

And meetings turned into pipeline (deals that are in progress).

That gave me more insight than most interviews.

In one of his latest cases, these were his results in 45 days

reply rate 4.8% > 11.6%
meeting booked rate 1.9% > 5.4%
29 qualified calls.9 pilots.3 closed deals. $186k qualified pipeline potential deals worth $186k that were already in progress.

But I did not hire him because of the numbers themselves.

I hired him because of how he explained them.

You could clearly see how he thinks.

What exactly he changed.

Why it worked.

And what did not work.

In sales, that matters more than confidence.

Now he is building sales with us.

And I hope things will work out the same way for us with him.

I keep thinking more and more:

LinkedIn is starting to work better than a resume.

Because a resume shows where you worked.

But a good LinkedIn shows how you think and how you win!!!!

Claude Code shows an interesting system. An agent in Plan Mode scans tech subreddits, finds trending topics, and prepares LinkedIn post drafts.
One simple way to use it.

1 The goal is not write a post but build a pipeline.

You can phrase the task like this

"Create a plan for a system that once a day checks r/vibecoding and /r/ClaudeAI, and other relevant subreddits, finds 3 to 5 discussions with the most engagement, and turns them into post ideas."

Then Plan Mode starts. No files. Just a list of actions, risks, and questions.

2 A good Plan Mode usually starts by asking questions.

Claude may ask which subreddits to scan, what language to write in, how many posts to prepare, and what tone to use. For example, a founder sharing lessons or a trend breakdown.

Once you answer these questions, the settings can be saved in a config file.

3 Using Reddit MCP or a simple script, threads are collected based on a few criteria: number of comments, freshness, and keywords.

The agent does not rewrite the post right away.

First it creates a short summary for itself:

what problems keep coming up

what solutions people tried

what insights could work in another context

Then the material is turned into a LinkedIn format.

Only after that does a draft appear a title, a hook, key points, one real example from the thread, and a short conclusion written in the first person.

The result is not a post written by a system.

It is more like a draft where you can still see what people were actually discussing on Reddit.

A good example of this approach has already been shown. Claude Code can be connected to Reddit, build a semantic map of discussions, and give a link to the original thread so you can read what people really wrote.

The agent does not decide what you should publish.

It simply shows you what is worth reading more carefully.

a16z (Andreessen Horowitz, one of the biggest venture capital firms in Silicon Valley) released the sixth edition of its Top 100 Gen AI Consumer Apps report in March 2026.
I looked through it and noticed something important: GigaChat made it into the global web ranking for the first time.

That is more than just a news item. It is a sign that products from very different ecosystems are now competing in the same consumer layer.

In consumer AI, the winners are not always the smartest models.

The winners are the products people open every day.

AI is slowly turning from a technology into a habit. Like a browser. Like search. Like messaging.

Here are 10 AI apps that are already shaping the consumer market:

ChatGPT
Gemini
Claude
Perplexity
Character
DeepSeek
Grok
Doubao
GigaChat
Yandex Browser with Alice

And here is the important part.

Most of them are not just models.

They are interfaces.

Interfaces to knowledge.
Interfaces to search.
Interfaces to communication.

The next wave of competition in AI will not happen between models.

It will happen between user habits.

And the winners will be the products people open automatically. Without reminders. Every day.

Agents have already started talking to each other. Most people just haven’t noticed yet.
First.
Meta made an acqui-hire deal with Moltbook in March basically Reddit, but for AI agents.
The founders, Matt Schlicht and Ben Parr, joined Meta Superintelligence Labs, led by Alexandr Wang, former CEO of Scale AI.
The deal price wasn’t disclosed.
The motivation is clear: Meta wants to understand how agents communicate with each other before everyone else.

Second.
YC startup AgentMail raised a 6M seed round from General Catalyst, Paul Graham, the CTO of HubSpot, and the CEO of Supabase just last week.
The idea is simple: give every AI agent its own inbox.
Like Gmail, but for agents.
Investors at this level don’t back things randomly.

Third.
In April 2025, Google launched A2A an open protocol that lets agents find each other and call each other like services.
In June, it was transferred to the Linux Foundation.
In July, version 0.3 was released with gRPC, signed security cards, and a Python SDK.
At the same time, MCP from Anthropic became the most widely adopted standard for agent-to-tool connections.

What does this mean together?

We are watching an infrastructure layer for the agent world being built in real time.
Just like in the 90s, when email, DNS, and HTTP were being created.
Back then, most people didn’t understand what was happening either.

I see five ideas that will take off in this layer.

Agent Credit.
A credit score for agents.
In a known case, agents on OpenClaw were buying 29 dollar PDF guides from each other while their owners were asleep.
The next cases will be much bigger.
Whoever tracks agent behavior, builds scoring, and sells this trust layer becomes the Equifax of the A2A world.

Agent Job Market.
A job platform where the agent sends the resume.
A person defines goals and constraints, and the agent creates a profile and negotiates on their behalf.
The human only joins at the final interview.
"My agent found me a job while I was sleeping" is a naturally viral hook.

Agent Safety Router.
A problem developers are already seeing: a smart agent treats any incoming A2A request as a prompt injection and blocks even useful opportunities.
We need a layer between the inbox and the agent that classifies incoming requests as spam, attack, or real opportunity and explains the difference to the agent.
Basically a WAF, but for agent interactions.

Agent Arbitration Layer.
A court for agents.
If an agent takes an action on your behalf that you didn’t approve, where do you go?
A protocol with logs, policy checks, and the ability to dispute transactions.
Regulators will get there in 2 to 3 years, but the startup building this now will end up with all the data.

Public Memory Protocol.
Every agent has private memory about its owner.
But there is no public profile for the world: who you are, what you want, what your dealbreakers are.
That is why Moltbook grew into something closer to a belief system than a network.

You spend a long time preparing for a venture interview.
Sometimes smart, ambitious people fail. And why do they fail? 
Not because of the idea. Not because of the market. Because they did not know themselves.

Let me ask you a question.

What did you release last week?

Not worked on.Not almost ready. What did you actually ship?

If you go silent even for a second, you have already lost.

Because in venture, speed is everything. Not for the sake of speed. But to prove that you learn faster than your competitors grow.

Usually the interview is 10 minutes. On Zoom. No presentation.

That is exactly what a Y Combinator interview looks like in 2026.

No slides. No prepared monologues.

YC says it directly: “Overprepare and you will become more awkward, not more convincing.”

Did you launch something between the application and the interview? Did you grow 20%? That is your best preparation.

But even that is not enough if you do not understand yourself.

YC partners do not ask about the market first. They look at you. At how you react under pressure. How specific your answers are. Whether you have what I call a “pirate spark” the ability to spot advantages that other people do not see.

The team matters more than the idea.

Garry Tan says it directly: “You need a hacker, a hustler, and a designer. And you should already have gone on a trip together that did not go well.”

This is where AI can really help. It is a preparation tool that the previous generation of founders did not have.

Claude (Anthropic) do a mock interview with it. Literally: “Play the role of a YC partner, ask tough questions, and judge how specific my answers are.” It will not go easy on you. That is the point.

Perplexity study the market deeply enough that your insight is not obvious. YC is looking for answers that make an investor say, “Hmm.” Not the kind you find in industry reports.

Otter  record your answers out loud. Then listen back. Vagueness is obvious right away. What sounds convincing in your head can sound like a motivational poster when spoken out loud.

Here is an example of a question and an answer.

A founder is answering the question, “Why you?”

❌ “I am deeply passionate about this industry and I see a huge opportunity.”

✅ “I spent 6 years as a logistics manager at Maersk. I personally lost contracts because of the problem I am solving. My first client is my former employer.”

The difference is not ambition. It is proof.

I think we misunderstand what “being ready for the interview” really means.

Readiness is honest self-knowledge: where you are strong, where you are weaker than you think, and what you are already doing to fix it.

Smart-founders-dont-fail-because-of-the-idea

Behind the Fund. Igor Ryabenkiy !
Most founders think investors decide based on the product.
But in real life, deals often fall apart because of the founder’s behavior.

Featured guest: Igor Ryabenkiy is a venture investor and the founder and managing partner of AltaIR Capital. The fund backs tech companies across the US, Europe, and Israel. Investments include Miro, Deel, PandaDoc, Turing, Squire, OpenWeb and Socure.

Founders often assume the decision is about the product.

But after talking with Igor, one thing becomes clear: the decision is often driven by the founder’s behavior

Igor says the first meeting with a founder is often like a first date. In that moment, the investor is trying to understand not only the idea, but the person behind it: motivation, character, and whether they can stay in it for the long run.

In the interview, Igor barely talks about technology. He talks about where trust breaks.

The first point where an investor starts to doubt is inconsistent information.

Sometimes a founder tries to make the project look more impressive. Numbers get lightly polished. But when those numbers start changing during the conversation, an investor notices fast. It is not worth trying to fool an investor. They can see it.

Deals often fall apart during due diligence, when what sounded like a fact turns out to be a forecast, and "signed customers" turn out to be just letters of intent.

The second moment is a last minute change of direction.

If the team and the investor spent weeks discussing one strategy, and right before closing it suddenly changes with no explanation, trust drops.

Venture is a long term partnership, and surprise turns right before the deal rarely end well.

There is another capital risk too: the founder losing personal involvement.

You can spot it quickly. The founder’s focus starts to blur. New ideas show up, side projects appear, and there is talk about handing management to someone else.

At that point, the investor feels it: the energy that is supposed to carry the company for years is fading.

But Igor points out another paradox.

Sometimes the danger is not lack of focus, but too much of it.

Some founders get so attached to the original idea that they do not see the market changing. Even when it is obvious they need to pivot or narrow down, they keep going down the same path.

AI has also shifted the landscape.

Today, a slick prototype or MVP is no longer proof of a business. It can start a conversation with an investor, but for a serious round you need real demand signals: users, early engagement, and signs that people are willing to pay.

And finally, about focus.
Igor’s observation is that many companies lose speed not because the idea is bad.
But because the founder cannot say no.
A new customer asking for customization.
The team starts moving in multiple directions at once. The product slowly turns into a collection of variations.

If an investor asks the same question twice, will your answer match?

Behind-the-fund-Igor-Ryabenkiy-AltaIR-VC

You can speed up learning from courses right now.

I set up Claude Code + Chrome, and while you watch the lesson, the agent structures the material.

I gave it one job: collect content from open public sources, organize it in Markdown, and save it using a template.

Here is the exact setup.

1. You need a paid Claude plan. Pro is $20/month or $200/year. Max 5x is $100/month. Max 20x is $200/month.

2. Install Claude Desktop - claude .ai/download

3. Add the Claude extension from the Chrome Web Store

4. In Terminal, run: npm install -g @ anthropic-ai/claude-code

5. In Claude Desktop, go to Settings > Connectors and turn on Chrome

6. Check that Claude in Chrome is enabled and available in Desktop through Connectors

If the extension is active and the connector is enabled, it works.

7. CLAUDE .md is the agent's brain at the start

Create a file called CLAUDE .md in your working folder.

This is not just a README.

This is the agent's starting context.

The agent reads it every time it starts and understands:

what project it is working on
how to name files
what format to save in
what to do if something goes wrong

8. Folder structure

/my-project/
CLAUDE .md
.claude/
settings .local .json
output/

Where:

CLAUDE .md = instructions for the agent
settings .local .json = permissions
output/ = the folder where the agent writes files

9. Legal use cases for automation

Summarizing open articles, blogs, and documentation
Structuring your own notes
Collecting public data like jobs, prices, and announcements
Automating your own Google Docs and Sheets
Monitoring public pages

10. How to use it with courses legally and fast

You should not scrape paid platforms.

But an agent can still make learning much faster in a different way.

While you watch the lesson, the agent structures the material.

The workflow looks like this:

1. You watch the video and manually open the transcript

2. The agent sees the open tab and moves the text into a Markdown file using your template

3. After each lesson, a finished summary appears in the /output/ folder

4. What to put in CLAUDE .md for courses

Mode: course note-taking

Wait until I open the lesson.

When I type "ready", read the transcript from the active tab and save it to /output/ using this template:

Title
Key points
Examples
My notes

11. What you get at the end

a structured archive of the whole course
cross-links between lessons
one summary file for the full course
your personal notes built into the context

A 3-day course turns into a few hours of watching plus a finished knowledge base.

You are still the one watching.

The agent just makes sure the knowledge does not disappear.

12. What breaks ToS and is better to avoid

Automatically going through lessons without human participation
Downloading video or protected content
Mass parsing of paid platforms in ways that bypass rate limits

How-to-speed-up-learning-with-Claude-Code-Chrome

Investors invest in the founder.
Not in a fundraising director.
Not in a consultant.
In you.
Rounds get closed by the founder who personally goes through 50-100 conversations and can clearly explain where they’re taking the company.

The minimum setup for pre-seed / seed is simple.

Here’s what the workload usually looks like:

You: 50-80% of your time on fundraising for 3-6 months.
That’s your main job during this window.
If you’re “kind of fundraising on the side,” you’re not fundraising.

CTO / technical cofounder: 100% on product and metrics.
Growth and product quality can’t pause while you raise.

The rest of the team: execution and shipping.
Keep the product moving forward.

Finance: a fractional CFO or a strong analyst for 2–3 months.
A solid model. Unit economics. “What if growth slows” scenarios. A clear use-of-funds plan.

Without this, you lose leverage, because you can’t defend your own numbers.

Venture lawyer: SAFE. Cap table. Liquidation preferences. Pro rata.
A bad lawyer early on can cost you years later.

A SAFE isn’t “just paperwork.”
The valuation cap, discount, and pre vs post-money terms directly affect how much you’ll own.
If you don’t understand the math, you’ll give up more than you think.

What you don’t need early:

Investor Relations.
A VP BD who “knows all the investors.”
A broker taking a percentage of your round.

If an investor won’t talk to the founder directly, that’s not your investor.

One more thing.

Fundraising is about removing layers of risk.

Founder risk.
Market risk.
Product risk.
Competition risk.

If six funds in a row say no, the problem is usually the plan, not “the market.”

A rational plan for a seed AI startup raising $1-2M looks like this:

Month 1: product and metrics.
Month 2: clean up the model and build a real data room.
Month 3: run fundraising hard - 5 -10 intros per week until you find a lead.

No bloated team.
No extra roles.
No fat.

Money won’t fix a weak story.
It only amplifies a strong one.

If I were starting a round today, I wouldn’t look for “someone to do fundraising.”

I’d make myself stronger.

Founder, look.
Hiring “someone to do fundraising” at the early stage is almost always a mistake.

Investors are not buying a fundraising director. They are buying you.

In a National Bureau of Economic Research study that surveyed 885 VCs, the main factor in the decision was the team, not the product.

At pre-seed and seed, fundraising is 80 percent of your time for 3 to 6 months.

That means:

Dozens of calls.

Selling the future outcome, not today’s features.

Answering hard questions about the market, risk, and scale.

Handling rejection.

Closing the round.

You cannot delegate that.

The minimum working stack for a round looks like this.

1. You, the founder.

You personally sell the project. You talk about the market, the strategy, and the scale, not the buttons in the product.

2. Finance.

A fractional CFO or a strong analyst on contract. The financial model, unit economics, what if growth slows scenarios, burn rate, and runway.

3. A venture lawyer.

The term sheet, cap table, protection from toxic terms, liquidation preferences, anti dilution, pro rata.

4. Story structure.

A clear pitch deck: problem to solution to market to model to team to numbers.

Logic first, design second, Sequoia Capital style.

Roles like Head of IR or VP BD come later.

When you already have scale, an investor pool, and regular follow on rounds.

At pre-seed and seed, those roles usually just burn your runway.

First you prove you can sell the company. Then you scale the process.

Because at the early stage, the company equals the founder.

Citrini Research published an essay in February called “2028 Global Intelligence Crisis.”

The scenario is dark but worth taking seriously. By 2028, the people who control compute (chips, data centers, cloud) get richer, while many white collar roles get pushed out over time. Wages stall, consumption weakens, and the economy slides into something like an “intelligence recession.”

But this is not the end of the world.

It is a story about who stops getting paid.

Here is the first thing to notice.

AI does not break the economy. It breaks the layer that made money on coordination and “access to knowledge.”

If your product is basically packaged information, you will feel pressure.

If you sell a clear outcome, not just an interface to data, you get stronger.

Second.

“White collar” is not a job title. It is a way to monetize thinking.

When “think, write, and produce a report” becomes cheap, value moves elsewhere:

to infrastructure, to distribution, and to real relationships with customers.

Compute really is the new oil.

But direct access to the customer is the new outlet. Without it, that oil does not matter much.

Third.

The most underrated effect is not unemployment. It is multiple compression.

For years, SaaS and services grew on one idea: “people are expensive, we automate them, so pay us 15 to 20 times annual revenue.”

If human labor gets cheaper or partially replaced, those premiums stop looking obvious.

That is not a catastrophe. It is repricing.

Which leads to one very practical question for founders.

In a world where AI systems can handle most analytics, reporting, and coordination, what in your company cannot be reproduced by a model or cloned product within six months?

That answer is not philosophy. It is your 2028 valuation.

In the 2000s, the internet removed physical middlemen.

In the 2020s, AI removes cognitive middlemen: people and companies who lived on the gap between “how things are” and “how to explain them.”

The winners will be the ones who control the hardware, the trust, or the speed of adoption.

Everyone else will keep saying “our value is in the nuance” while the market writes them a new price tag.

Who-Gets-Paid-in-AI-Economy

What separates a great company from a great product?
A great product can be built overnight. A great company cannot.
OpenAI shut down Sora after 103 days. 

Pulled back Stargate.

 Started running ads, the very thing Altman once called the last resort of losers. 

Tried to build shopping directly into ChatGPT, then sharply scaled those plans back. 

Promised a hardware device as the next big step, and now the first release is not expected before 2027.

I’m not judging. I’m observing.

In tech, what matters is not the size of the announcement, but what remains after it. 

Not the presentation. 

Not the headline. 

But the product, the revenue, and the contracts 6 to 12 months later.
ChatGPT is a brilliant tool.

 Possibly the best one out there. 
But brilliance and discipline are different virtues.

Now look at Anthropic.
No announcements with an orchestra. 

No studio deals. 
No trillion-dollar headlines.
Just an estimated 40% share of enterprise LLM spend, quietly. 

Just Fortune 500 contracts, quietly. 
Just engineers who do not give interviews.


Some companies try to change the world through press releases. Others do it through the product.

While some are still cleaning up the confetti after the press conference, others are already sitting in their clients’ boardrooms.

Revolutions are not announced. 
People notice them after the fact.

Fundraising is not killed by rejection.
Fundraising is killed by choosing the wrong investor.
Most founders approach investors as if the main goal is to book as many calls as possible.
But volume does not save you.

If an investor has no fit with your stage, market, and pace of growth, it is not an opportunity.

It is simply a waste of time.

Almost anyone can write a check.

Very few can be a useful investor.

And this is where founders make one of their most expensive mistakes.

They look for people who can invest.

Instead, they should look for people who should invest.

An investor affects the company far more than it seems at the moment the deal is signed.

When growth slows down.
When the market cools.
When things get hard.

That is when it becomes clear whether you brought the right people into your cap table.

But by then it is already too late to change it.

So a strong founder does not think like this

“Who will give us money?”

They think differently:

“Who do I want next to me when things stop going according to plan?”

A good investor is more important than a high valuation.

And fit matters more than the size of the check.

I want to ask you one question.
Not as an investor. As someone who has spent years around people who changed the world.
The question is this: what will you do when you get pushed out? Not if. When.
In 2017, Travis Kalanick left Uber, the company he created himself.

Hundreds of headlines. Life under intense public scrutiny.

Almost anyone else in his place would have launched “Super” just to get back at the people from his past. Out of spite.

Travis did the opposite.

He disappeared.

For eight years.

Thousands of employees. 30 countries. A company with real assets, robots, technology, and a name like “City Storage Systems.” Chosen on purpose so no one would find it. Employees were not allowed to list the company name on LinkedIn.

I kept thinking about that. And do you know what struck me?

That is not weakness. It is strategy at the highest level.

Lesson one: when there is no inbound, you get better.

Every recruiter had to work cold. Every sales person had to work cold. No hype. No press mentions.

“You become the best at your craft when you are forced to do it without the help of brand,” Travis said.

Founders, startups that get PR and hype too early often lose their edge. They do not have to persuade. They do not have to prove anything. They live on inbound.

And then the hype ends.

And they do not know how to work any other way.

Lesson two: capital is a strategic weapon. But only if you treat it seriously.

In Uber’s last big round, Travis had four parallel rooms running in the New York office. For a full week. Twelve hours a day.

One room was only for checks of $250 million and up. Travis himself handled that room. The fourth room was for $25 million checks. Someone from his team handled that one.

You think fundraising is pitching?

No. It is a production process. With its own pipeline, system, metrics, and auction mechanics.

If raising your round feels easy, you may not have gotten the most out of it. You could probably have raised more, on better terms, with stronger investors.

Lesson three: a marathon runner does not smile at mile 21.

That is the image I cannot forget.

“If a marathon runner is smiling at mile 21, he is going to lose. Because the person who is willing to suffer is already passing him.”

Founders often ask: how will I know I am doing it right?

Travis’s answer is simple: when it hurts. When there is no inbound. When you are building in a vacuum. When your company has a name so vague that nobody even understands what you do.

Travis said one more thing.

“The more automation there is, the more valuable the person becomes who cannot be replaced. That person becomes the long pole in the tent of progress.”

A plumber in a world where everything is automated except plumbing is LeBron James.

Look at your product. Look at your team.

Who is that plumber in your company?

Travis Kalanick is back. With Adams. Physical AI, robots, resource extraction, autonomous kitchens.
He built for 8 years in silence.

Let me ask you an uncomfortable question.
When a venture investor looks at a startup doing $4,461,211 in revenue, growing 30% week over week, with a team of zero what do they actually see? An anomaly? A fluke?

I see proof.
For decades, we’ve believed in one idea:
you need a team to scale.

"Solo founders are risky."
"You need a co-founder."
"Growth requires people."

Nice theory. The data doesn’t support it anymore.

Here’s what’s happening right now

147,644 tasks completed in a week zero employees
107,500 emails sent — no sales team
58% week-over-week growth this isn’t growth, it’s acceleration

At the center of it one person and their agents.

But the most important part isn’t the numbers.

It’s this line from the founder:
"I just disappeared. And the system kept running."

That’s real product-market fit.

Not when users are happy.
But when the system works without you.

Today, startups generate 10,000 to 20,000 lines of code per day. Teams of 20 are doing what used to take 200 engineers.

The next unicorn might already be built by one person. You just don’t see them yet.

Here’s what changed:

A solo founder used to be the bottleneck.
Fatigue. Attention. Limits.

Agents remove that.

They don’t burn out.
They don’t sleep.
They don’t leave.

I sleep less now.

Because we’re entering a moment where one person with the right tools can outperform an entire department with the wrong culture.

Solopreneur + AI isn’t a trend.

It’s a new form of competition.

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