6ixcore, under my leadership as Founder and CEO since March 2020, focuses on delivering innovative solutions that drive business growth and strategic transformation. With a deep commitment to entrepreneurial leadership and business innovation, we empower organizations to adapt and thrive in competitive markets. My role emphasizes fostering collaboration, enabling impactful strategies, and advancing the company’s mission toward sustainable success.

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Ben Zheng

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

Victor Sankin

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.

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

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

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.

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

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

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.

Most truly new ideas look strange at first.
In 2008, when Airbnb suggested that people sleep on an air mattress in a stranger’s living room, many investors were skeptical.

"This isn't a business. It's a hobby."

But Airbnb was not trying to make hotels better.

They created a new category.

At first it looked unusual. Later it became obvious.

Peter Thiel calls moments like this the jump from 0 to 1.

Not a step forward.
More like a step sideways.

Not better.
Just different.

Ideas like this often cause confusion.

Not because they are bad, but because they don't fit familiar patterns.

Stripe once looked like two developers building a payments tool.

Next to PayPal and the banks, it seemed like a small story.

But they did one thing much better: accepting payments for developers.

And that was enough to build a company worth billions.

If Airbnb had looked like a future global platform from the start, it probably would have seemed like just another hotel chain.

Sometimes a strange idea is simply a new category the market has not learned to recognize yet.

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