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I am a business developer, sales professional, and FinTech strategist who strives to make an impact and change the world. For the better.

Although I have a bachelor's degree in Economics (with a major in Economics and Politics), I have been actively following and/or working in the Financial Services field since the very first year at university.

Because of the early start of my career and given opportunities to try myself out in different roles and different players in the world of finance (I worked at Western Union, Danske Bank, Norne Securities), quite quickly and easily I found myself being the most passionate about Financial Technology and its enormous potential to reinvent conventional finance and change the world for the better.

Now I am working in FinTech for more than 6 years, and every day I try to be a bit better and learn something new (and there are lots to learn!).

Currently, I am a part of Flutterwave, where I am scaling the business and leading company's expansion into Europe. Flutterwave is a Mastercard, VISA, Greycroft, Y Combinator, and Worldpay FIS-backed payments technology company headquartered in San Francisco. We're simplifying payments for endless possibilities. Flutterwave is trusted by leading companies like Uber, Facebook, TransferWise, Netflix, Jumia, Azimo, Binance, among other 90,000+ businesses. We were recognized as the #2 Most Innovative Company in Africa in 2019, according to Fast Company. We're part of 50 Future Unicorns🦄 according to CB Insights & Fast Company. Also, CNBC has included us in the Upstart 100, which lists the brightest, most intriguing, young startups promising to become the great companies of tomorrow. I am super excited to play an important part in the Financial Technology revolution, and having the ability to move the financial disruption forward.

I am highly interested in FinTech/TechFin, digital innovation (especially in banking, payments, and finance per see), and emerging technologies.

P.S. If you're passionate about FinTech as well as Blockchain & Cryptocurrency and always want to stay up-to-date, make sure to subscribe to my newsletter 🔔linas.substack.com🔔 and join over 111,000+ professionals globally who follow my work.

Linas Beliūnas

Can’t believe Linus Torvalds created Linux at 21 without Claude or AI.

→ He didn't even have a co-founder.
→ No VC funding.
→ No office.
→ No team.
→ Just a personal project

He posted this announcement on Usenet in 1991:

“I’m doing a (free) operating system (just a hobby, won’t be big and professional like gnu) for 386(486) AT clones.”

34 years later, it runs 96% of the world's servers, all Android smartphones, the International Space Station, most of the cloud (AWS, GCP, Azure), every major stock exchange, and basically is the internet’s backbone.

The most important software in history started as someone's side project.

Living legend.

P.S. check out how I built an AI operating system to run a startup with Claude 🤖: https://lnkd.in/dv7-ZRVc

Can’t believe Linus Torvalds created Linux at 21 without Claude or AI.  → He didn't even have a co-founder. → No VC funding. → No office. → No team. → Just a personal project  He posted this announcement on Usenet in 1991:  “I’m doing a (free) operating system (just a hobby, won’t be big and professional like gnu) for 386(486) AT clones.”  34 years later, it runs 96% of the world's servers, all Android smartphones, the International Space Station, most of the cloud (AWS, GCP, Azure), every major stock exchange, and basically is the internet’s backbone.  The most important software in history started as someone's side project.  Living legend.

This is the wildest AI breakthrough of the year: a tech founder with zero background in biology just saved his dog using a custom mRNA vaccine he designed with ChatGPT 😳

Sydney entrepreneur Paul Conyngham adopted Rosie knowing she had aggressive cancer.

Months to live.

Instead of accepting it, he tried something unusual.

He sequenced her tumor DNA and asked AI what to do next.

The result: a bespoke mRNA cancer vaccine designed for a single patient - his dog.

And here comes the wildest part.

→ $3,000 to sequence Rosie’s tumour genome
→ AI tools helped identify mutated proteins and potential drug targets
→ Conyngham used ChatGPT + AlphaFold to model the cancer biology
→ UNSW scientists helped manufacture the custom mRNA vaccine
→ After injections starting December 2025, a tennis-ball-sized tumour shrank by ~50% by March 2026 🤯

One researcher’s reaction: “Holy crap, it worked.”

But the most interesting part was not about science. It was the bottleneck.

Designing the vaccine took weeks.
Getting ethics approval took months.

In other words, the limiting factor in medicine may no longer be discovery.

It’s process.

AI is quietly turning biology into a programmable field. Like software.

When a determined founder can prototype a personalized cancer therapy for $3k and a chatbot, the implications get very big, very fast.

Most importantly, Rosie’s story isn’t about a dog.

It’s about what happens when AI meets biology, and stubborn humans who refuse to give up.

AI + Biology will change the world.

P.S. check out how I built an AI operating system to run a startup with Claude 🤖: https://lnkd.in/dv7-ZRVc

This is the wildest AI breakthrough of the year: a tech founder with zero background in biology just saved his dog using a custom mRNA vaccine he designed with ChatGPT 😳  Sydney entrepreneur Paul Conyngham adopted Rosie knowing she had aggressive cancer.  Months to live.  Instead of accepting it, he tried something unusual.  He sequenced her tumor DNA and asked AI what to do next.  The result: a bespoke mRNA cancer vaccine designed for a single patient - his dog.  And here comes the wildest part.  → $3,000 to sequence Rosie’s tumour genome → AI tools helped identify mutated proteins and potential drug targets → Conyngham used ChatGPT + AlphaFold to model the cancer biology → UNSW scientists helped manufacture the custom mRNA vaccine → After injections starting December 2025, a tennis-ball-sized tumour shrank by ~50% by March 2026 🤯  One researcher’s reaction: “Holy crap, it worked.”  But the most interesting part was not about science. It was the bottleneck.  Designing the vaccine to

The biggest AI breakthrough of the year? Google just released TurboQuant, an algorithm that makes LLM’s 6x smaller & 8x faster, without losing any quality 😳

Buried in Google Research is a simple idea:

Don’t scale the model.
Compress its memory.

Every LLM relies on a KV cache that grows with every token.
Longer context = more VRAM, slower inference, higher cost.

TurboQuant attacks that directly.

→ ~6× smaller KV cache
→ Up to 8× faster attention (H100)
→ Compresses to ~3-3.5 bits (from FP16/BF16)
→ Zero accuracy loss on long-context tests (100k+ tokens)
→ Already replicated on Apple Silicon (~4.9× smaller via MLX)

Same model.
Same outputs.
Massively cheaper to run.

That changes the economics:

→ 100k-1M token context becomes practical
→ On-device AI suddenly viable (laptops, phones)
→ Inference costs (the real spend) collapse
→ Edge computing starts to win again

The wildest part?

Turns out, we’ve been scaling the wrong thing.

AI didn’t need more compute.
It needed better compression.

Which is exactly why Apple never rushed into the GPU arms race.

Because the AI race isn’t just about intelligence anymore. It’s about who uses memory best.

More importantly, the next AI winners won’t be trained differently.

They’ll run differently.

P.S. also check out how I Turned Claude Cowork Into My Personal COO that does work while I sleep 🧠: https://lnkd.in/eS6JCk2G

The biggest AI breakthrough of the year? Google just released TurboQuant, an algorithm that makes LLM’s 6x smaller & 8x faster, without losing any quality 😳    Buried in Google Research is a simple idea:    Don’t scale the model.  Compress its memory.    Every LLM relies on a KV cache that grows with every token.  Longer context = more VRAM, slower inference, higher cost.    TurboQuant attacks that directly.    → ~6× smaller KV cache  → Up to 8× faster attention (H100)  → Compresses to ~3-3.5 bits (from FP16/BF16)  → Zero accuracy loss on long-context tests (100k+ tokens)  → Already replicated on Apple Silicon (~4.9× smaller via MLX)    Same model.  Same outputs.  Massively cheaper to run.    That changes the economics:    → 100k-1M token context becomes practical  → On-device AI suddenly viable (laptops, phones)  → Inference costs (the real spend) collapse  → Edge computing starts to win again    The wildest part?    Turns out, we’ve been scaling the wrong thing.    AI didn’t need mo

Stop paying $20/month for Claude Code. Chipotle’s AI bot is FREE.

Someone asked Chipotle’s support assistant Pepper how to reverse a linked list in Python.

It answered correctly.

Not burrito recommendations.
Actual code.

A fast-food chatbot quietly passing a classic computer science interview question wasn’t on my 2026 bingo card.

We’re at peak AI now.

P.S. on a serious note, check out how I Turned Claude Cowork Into My Personal COO that does work while I sleep 🧠: https://lnkd.in/eS6JCk2G

Stop paying $20/month for Claude Code. Chipotle’s AI bot is FREE.  Someone asked Chipotle’s support assistant Pepper how to reverse a linked list in Python.  It answered correctly.  Not burrito recommendations. Actual code.  A fast-food chatbot quietly passing a classic computer science interview question wasn’t on my 2026 bingo card.  We’re at peak AI now.

Claude AI is eating the world: Microsoft just shipped its “digital coworker” for 365, and the brain behind it isn’t OpenAI. It’s their biggest rival Anthropic 😳

Microsoft CEO Satya Nadella just unveiled Copilot Cowork - an autonomous agent that can plan and execute multi-step work across Outlook, Excel, PowerPoint, Teams, and your entire Microsoft 365 stack.

You give it intent: “Prepare me for the Q2 review with Acme.”

It builds the plan.
Pulls the data.
Writes the deck.
Schedules prep time.
Drafts the emails.

And runs the workflow in the background.

The agentic orchestration layer powering it comes from Claude Cowork, Anthropic’s technology.

That makes this one of the biggest enterprise wins the $380 billion AI lab has landed so far 🤯

It could change the enterprise AI game significantly thanks to:

↳ Massive distribution

Microsoft 365 has hundreds of millions of seats. Copilot already has 15M+ paid users and 90% of the Fortune 500.

↳ Enterprise trust unlocked

Claude’s agentic tech is now wrapped in Microsoft’s security stack: Purview, Entra, audit logs, and compliance.

↳ Strategic signal

Microsoft’s deepest AI partner is OpenAI (it has 27% stake).
Yet the system executing long-horizon work plans now runs Anthropic’s stack.

↳ A learning flywheel

Every enterprise workflow running inside Copilot now trains Claude on real office work.
This alone could be a huge unlock for real-world workflows.

My takeaway is this:

The biggest shift we’re witnessing now is not about better chatbots or the latest LLMs.

It’s all about software that plans and executes knowledge work while you watch the progress bar 🤖

Anthropic built the AI agent that made Microsoft nervous.

So Microsoft turned around and shipped it to the corporate world.

Now the operating system of global office work runs on Claude AI.

Anthropic just can't stop winning, & ClaudeOS is eating the world.

P.S. check out how to Turn Claude Cowork Into Your Personal COO that does work while you sleep 🧠: https://lnkd.in/eS6JCk2G

Claude AI is eating the world: Microsoft just shipped its “digital coworker” for 365, and the brain behind it isn’t OpenAI. It’s their biggest rival Anthropic 😳  Microsoft CEO Satya Nadella just unveiled Copilot Cowork - an autonomous agent that can plan and execute multi-step work across Outlook, Excel, PowerPoint, Teams, and your entire Microsoft 365 stack.  You give it intent: “Prepare me for the Q2 review with Acme.”  It builds the plan. Pulls the data. Writes the deck. Schedules prep time. Drafts the emails.  And runs the workflow in the background.  The agentic orchestration layer powering it comes from Claude Cowork, Anthropic’s technology.  That makes this one of the biggest enterprise wins the $380 billion AI lab has landed so far 🤯  It could change the enterprise AI game significantly thanks to:  ↳ Massive distribution  Microsoft 365 has hundreds of millions of seats. Copilot already has 15M+ paid users and 90% of the Fortune 500.  ↳ Enterprise trust unlocked  Claude’s agen

Nailed it! Software developers 2 hours before the deadline 👏😂

Claude Code & chill.

P.S. for more great stuff, check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets AI. For founders, builders, and leaders.

Stack Overflow went from 300,000 questions/month to almost 0 after ChatGPT launched, and yet its revenue is now up 2x to a whopping $115 million 😳

Shortly after OpenAI launched ChatGPT, the internet’s most important developer forum basically stopped being used.

And yet Stack Overflow’s revenue doubled, and is now at $115M/year.

How?

Instead of fighting AI, Stack Overflow sold itself to AI.

Here’s how they pulled off one of the wildest pivots in tech 👇

While developers stopped asking questions, AI companies started buying answers.

15+ years of human-crafted answers.
58M+ Q&A pairs.
Millions of real bugs.
Edge cases.
War stories.

The internet’s highest-quality coding dataset, so Stack Overflow licensed it.

And then they did the smartest move of all.

They stopped chasing public traffic and went inside companies.

Launched “Stack Internal”, a private GenAI tool trained on Stack Overflow’s knowledge, plugged directly into enterprise workflows.

Private. Secure. Inside companies.

Used by 25,000+ organisations already.

Not a forum.
Not a community.

An internal AI brain for developers 🧠

Here’s the uncomfortable truth:

The internet’s open knowledge era is collapsing.

Not because knowledge vanished.
But because it got privatized.

Volunteers built it for free.
AI monetizes it at scale.

And that’s the biggest lesson for every platform, founder, and creator:

Data now is the ultimate moat.

If you own high-quality data, you have leverage.

If you don’t, you’re feeding someone who does.

P.S. check out how I Turned Claude Cowork Into My Personal COO that does work while I sleep 🧠: https://lnkd.in/eS6JCk2G

Stack Overflow went from 300,000 questions/month to almost 0 after ChatGPT launched, and yet its revenue is now up 2x to a whopping $115 million 😳  Shortly after OpenAI launched ChatGPT, the internet’s most important developer forum basically stopped being used.  And yet Stack Overflow’s revenue doubled, and is now at $115M/year.  How?  Instead of fighting AI, Stack Overflow sold itself to AI.  Here’s how they pulled off one of the wildest pivots in tech 👇  While developers stopped asking questions, AI companies started buying answers.  15+ years of human-crafted answers. 58M+ Q&A pairs. Millions of real bugs. Edge cases. War stories.  The internet’s highest-quality coding dataset, so Stack Overflow licensed it.  And then they did the smartest move of all.  They stopped chasing public traffic and went inside companies.  Launched “Stack Internal”, a private GenAI tool trained on Stack Overflow’s knowledge, plugged directly into enterprise workflows.  Private. Secure. Inside companies.

Nailed it! Silicon Valley predicted AI assistants 10 years early:

“You made an AI Gilfoyle, and I was talking to it??” 👏😂

In 2016, that was satire.
In 2026, it’s basically the product roadmap.

Look at what AI is doing now:

→ AI drafts your Slack and email replies
→ AI summarizes meetings you didn’t attend
→ AI agents schedule calls and answer questions
→ Founders are literally building “AI inbox managers”

Silicon Valley is the greatest show of all time, which was consistently ahead of its time.

Especially when it comes to artificial intelligence.

Absolute masterpiece.

P.S. on a more serious note, check out how I built an AI operating system to run a startup with Claude 🤖: https://lnkd.in/dv7-ZRVc

For two years, everyone said Apple was losing the AI race. Turns out Apple might have been playing a completely different game the whole time 😳

While the industry burned $1.4 trillion+ training frontier models, Apple quietly waited.

Then, in January 2026, it made a very Apple move - partnered with Google to power Siri with Gemini AI.

Not “build the biggest model.”
Pick the winner. Integrate it everywhere 🤖

And tomorrow, Apple flips the switch.

AI Siri → 2.5 billion devices.

While everyone else is fighting for AI users, Apple already owns the devices on which those users live.

The contrast is quite wild:

→ $1.4T+ spent across the industry training models since 2023
→ Apple pays ~$1B/year to integrate the best one

→ Rivals chase subscriptions ($20-$200/month)
→ Apple runs AI on-device: faster, cheaper, private

→ Startups race to build AI hardware
→ Apple ships iPhone, iPad, Mac, Vision, Watch powered by its own AI chips

→ Competitors fight for distribution
→ Apple flips a switch across 2.5B devices

Sure, Apple didn’t win the LLM race.

But the AI model race might not have been the real game all along.

The real game is distribution + hardware + ecosystem.

And in that game, Apple starts the match with billions of users already logged in.

Turns out “being late to AI” might have been the most Apple strategy imaginable.

Most importantly, the AI era may not be decided by who builds the smartest model.

It might be decided by who owns the device that model runs on.

P.S. check out how I Turned Claude Cowork Into My Personal COO that runs work while I sleep 🧠: https://lnkd.in/eS6JCk2G

For two years, everyone said Apple was losing the AI race. Turns out Apple might have been playing a completely different game the whole time 😳  While the industry burned $1.4 trillion+ training frontier models, Apple quietly waited.  Then, in January 2026, it made a very Apple move - partnered with Google to power Siri with Gemini AI.  Not “build the biggest model.” Pick the winner. Integrate it everywhere 🤖  And tomorrow, Apple flips the switch.  AI Siri → 2.5 billion devices.  While everyone else is fighting for AI users, Apple already owns the devices on which those users live.  The contrast is quite wild:  → $1.4T+ spent across the industry training models since 2023 → Apple pays ~$1B/year to integrate the best one  → Rivals chase subscriptions ($20-$200/month) → Apple runs AI on-device: faster, cheaper, private  → Startups race to build AI hardware → Apple ships iPhone, iPad, Mac, Vision, Watch powered by its own AI chips  → Competitors fight for distribution → Apple flips a sw

The most uncomfortable meme in AI right now compares OpenAI to Yahoo 😳 At first, it sounds ridiculous. Then you look at the data…

For a while, OpenAI looked like Yahoo in 1996: the portal everyone starts from.

Huge user base.
Massive brand.
Default homepage of AI.

But the momentum in the dev + enterprise layer is clearly shifting.

↳ Enterprise LLM spend: OpenAI fell from ~50% share to ~25-27%. Anthropic climbed to ~32-40% 📈

↳ Coding benchmarks: Claude leads SWE-bench (~76-81% tasks solved) 🤖

↳ Developer sentiment: many teams now treat Claude as the default coding model 🧠

↳ Product focus:

OpenAI → consumer features, multimodal, scale.
Anthropic → code, agents, enterprise workflows.

Sound familiar?

→ Yahoo tried to build the entire internet portal.
→ Google was obsessed over one thing done insanely well.

And that focus compounded.

To be clear, OpenAI isn’t Yahoo (yet).

ChatGPT still dominates consumer AI.

But the highest-value layer in this market isn’t chat.

It’s the models that developers and companies build their products on.

That’s where the real platform wars are happening.

Consumer mindshare might win headlines, but developer mindshare is what wins decades.

P.S. check out how I built an AI operating system to run a startup with Claude 🤖: https://lnkd.in/dv7-ZRVc

Are we cooked? OpenAI co-founder & former Head of AI at Tesla Andrej Karpathy just mapped the entire job market against AI, and the results are very uncomfortable 😳

Turns out, if your entire job happens on a screen, AI is coming for it.

Andrej Karpathy scraped data on 342 occupations from the U.S. Bureau of Labor Statistics and asked an LLM a simple question:

How exposed is this job to AI? 🤖

Then he visualized the entire economy, and the results are… uncomfortable.

White-collar work is far more exposed than most people expected.

Not because AI replaces it overnight.
Because AI multiplies productivity inside it.

Some interesting numbers from the dataset:

→ Average AI exposure: 5.3/10 across all jobs (4.9 when weighted by employment)
→ ~25 million jobs fall into the “very high exposure” category (8-10)
→ $3.7 trillion in wages tied to highly exposed roles
→ 10/10 exposure: medical transcriptionists
→ 8-9 exposure: software developers, analysts, paralegals
→ 0-1 exposure: roofers, janitors, construction workers

The pattern is quite striking.

↳ If the output of your job is purely digital - code, text, analysis, documents - exposure is high.
↳ If it requires hands, presence, or real-time human interaction, exposure drops dramatically.

Of course, we must note that the scores come from one LLM (Google’s Gemini) applying a rubric to job descriptions.

Real-world work is much messier than a BLS description, and technology also evolves.

More importantly, exposure ≠ extinction.

Engineers using AI today are already 2-3× more productive.
Writers, analysts, and designers are seeing the same thing.

AI doesn’t just replace work. It compresses it.

Which means the winning strategy isn’t avoidance.

It’s aggressive augmentation.

Treat AI like a junior team that works for you 24/7.

Because the real risk isn’t that AI takes your job.

It’s that someone using AI will.

P.S. check out how I Turned Claude Cowork Into My Personal COO that does work while I sleep 🧠: https://lnkd.in/eS6JCk2G

Are we cooked? OpenAI co-founder & former Head of AI at Tesla Andrej Karpathy just mapped the entire job market against AI, and the results are very uncomfortable 😳  Turns out, if your entire job happens on a screen, AI is coming for it.  Andrej Karpathy scraped data on 342 occupations from the U.S. Bureau of Labor Statistics and asked an LLM a simple question:  How exposed is this job to AI? 🤖  Then he visualized the entire economy, and the results are… uncomfortable.  White-collar work is far more exposed than most people expected.  Not because AI replaces it overnight. Because AI multiplies productivity inside it.  Some interesting numbers from the dataset:  → Average AI exposure: 5.3/10 across all jobs (4.9 when weighted by employment) → ~25 million jobs fall into the “very high exposure” category (8-10) → $3.7 trillion in wages tied to highly exposed roles → 10/10 exposure: medical transcriptionists → 8-9 exposure: software developers, analysts, paralegals → 0-1 exposure: roofer

Wild: Scientists just built a biological computer that runs DOOM using living neurons. No AI model was involved, and the entire system fits in a shoebox 😳

Australian startup Cortical Labs just showed a system where ~200,000 lab-grown human neurons control the classic shooter Doom.

No code runs inside the cells.
No gradient descent.
No training dataset.

Just biology learning 🧠

The setup is almost surreal:

→ A shoebox-sized biological computer called CL1 keeps neurons alive with nutrients, temperature control, and waste removal.
→ Game information is sent as electrical signals directly to the cells.
→ The neurons’ spikes are decoded into game actions: move, turn, shoot.
→ The culture learns during the session, adapting to threats and navigation.

This builds on their earlier DishBrain experiment that learned to play Pong.

But Doom is different.

Now you need 3D movement, aiming, and threat detection - all handled by a tiny living network.

And the energy numbers are wild:

↳ A rack of ~30 CL1 units runs on under 1 kW
↳ That’s orders of magnitude less power than comparable silicon AI workloads

Which means that ontelligence may not require massive GPU clusters.

It might emerge from physics + feedback.

Silicon gives us speed.
Biology gives us efficiency and plasticity.

The interesting future might be hybrid systems - chips doing math, neurons doing adaptation.

And if we can grow intelligence, we may soon need to rethink what actually counts as a computer…

P.S. also check out how to Turn Claude Cowork Into Your Personal COO that does the work while you sleep 🧠: https://lnkd.in/eS6JCk2G

Nailed it! Ex-Google CEO Eric Schmidt on the future of AI:

"If you really want to make money, found an agentic AI company. I mean, build an agent to do something. This is the agentic period in AI. Everyone's going to build agents. The agents are all going to compete."

And he’s right. The LLM race is maturing, while the AI agent race is just getting started.

For two years, we were obsessed over parameters, benchmarks, and leaderboards.

Meanwhile, AI stopped just answering questions and started taking actions.

→ Enterprises are already deploying agents internally at scale (McKinsey has reportedly rolled out tens of thousands).

→ AI Agents can now update CRMs, reconcile invoices, draft memos, ship code, and trigger workflows.

But the most underrated part is this: the agent itself commoditizes fast.

The moat is proprietary data, embedded workflows, and distribution.

Build accordingly.

P.S. check out how to Turn Claude Cowork Into Your Personal COO 🧠: https://lnkd.in/eS6JCk2G

The Apple App Store moment for AI is finally here: Anthropic quietly launched Claude Marketplace, and it might be the most important enterprise AI infrastructure move this year 😳

Claude Marketplace lets enterprises buy specialized AI platforms using their existing Claude spend.

No new vendor contracts.
No security reviews.
No procurement cycles.

Just allocate part of your Claude budget.

That small detail solves the biggest bottleneck in enterprise AI: deployment friction.

The first partners show where this is going:

→ Harvey - legal AI for contracts, due diligence, litigation
→ Rogo - finance models, research, and pitch decks
→ Replit - natural-language software development
→ GitLab - DevOps and code lifecycle automation
→ Snowflake - governed data agents
→ Lovable - prompt-to-app builder for non-technical teams

The interesting part? Anthropic takes 0 commission.

Because the real strategy is not about marketplace revenue.

It’s turning Claude into the enterprise AI operating system 🤖

One intelligence layer.

Legal questions route to Harvey.
Financial analysis to Rogo.
Apps built in Replit.
Data queried through Snowflake.

All powered by the same Claude brain - under one bill.

If this model works, companies won’t buy 15 separate AI tools.

They’ll adopt one AI platform and plug specialized agents into it.

That’s a very different competitive game.

Whoever becomes the enterprise AI OS will own the next decade of software.

P.S. check out how to Turn Claude Cowork Into Your Personal COO that does work while you sleep 🧠: https://lnkd.in/eS6JCk2G

The Apple App Store moment for AI is finally here: Anthropic quietly launched Claude Marketplace, and it might be the most important enterprise AI infrastructure move this year 😳  Claude Marketplace lets enterprises buy specialized AI platforms using their existing Claude spend.  No new vendor contracts. No security reviews. No procurement cycles.  Just allocate part of your Claude budget.  That small detail solves the biggest bottleneck in enterprise AI: deployment friction.  The first partners show where this is going:  → Harvey - legal AI for contracts, due diligence, litigation → Rogo - finance models, research, and pitch decks → Replit - natural-language software development → GitLab - DevOps and code lifecycle automation → Snowflake - governed data agents → Lovable - prompt-to-app builder for non-technical teams  The interesting part? Anthropic takes 0 commission.  Because the real strategy is not about marketplace revenue.  It’s turning Claude into the enterprise AI operating s

Nvidia CEO just said Agentic OS is the future 😳

“Every software company needs an OpenClaw strategy” - Jensen Huang

At GTC 2026, Jensen compared OpenClaw to Linux, HTTP, Kubernetes.

Not a tool - a new layer of computing.

And that’s the shift most people are missing:

We’re not upgrading software.
We’re replacing who uses it.

From humans clicking dashboards → agents running workflows.

Which means that SaaS isn’t becoming AI-powered.
It’s becoming agent-consumable.

That flips the entire model.

→ OpenClaw/AI agents don’t just answer - they act
(read/write files, run code, book meetings, open PRs)

→ They run 24/7 with memory + scheduled tasks
(not prompt → response, but continuous execution)

→ NVIDIA’s NemoClaw adds sandboxing + policy engines
(agents with guardrails = enterprise-ready)

→ Real workflows already chain agents together
(sales → scheduling → fulfillment, no human in the loop)

→ 22% of employees are already running agents at work
(most without IT approval)

This means that:

Your product is no longer the interface.
It’s a tool an agent calls.

Your moat is no longer UX.
It’s orchestration + security.

And your competition is no longer just another SaaS.
It’s someone else’s AI agent doing your job faster.

In the agent & machine economy, the interface will become optional.

And the winners won’t build better tools - they’ll build better agents.

P.S. check out how I built an AI operating system to run a startup with Claude 🤖: https://lnkd.in/dv7-ZRVc

Vibe Design is here: Google just launched Stitch, an AI that designs full websites & apps from a single prompt. And it makes Figma look like Microsoft Paint 😳

Stitch is not just another AI design tool.

It’s a canvas that turns ideas → interactive product in minutes.

→ Prompt: “matcha green wellness app” → full UI, instantly
→ Voice edits: “make it calmer, add forest imagery” → updates live
→ DESIGN dot md → one file controls brand, colors, typography across every screen
→ Auto-stitches flows → clickable prototypes without manual linking
→ Export to code or Figma → design + dev collapse into one step

That rewires who gets to build.

Before: idea → designer → wireframes → revisions → prototype → dev
Now: idea → working prototype (same person, same hour)

This means speed just went vertical.

The gap between “idea” and “usable product” also collapsed.

But originality didn’t.

And that’s exactly why the role of designers will shift:

Less execution.
More taste, systems, and judgment.

Because when design is instant, taste becomes the ultimate advantage.

P.S. check out how I built an AI operating system to run a startup with Claude 🤖: https://lnkd.in/dv7-ZRVc

Anthropic just dropped the biggest AI product launch of the year so far: Claude can now control your entire computer autonomously & complete all your tasks for you 😳

Anything you can do on a computer, Claude AI can do it too.

Open apps.
Click buttons.
Fill spreadsheets.
Sends emails.

It’s like having your very own digital employee.

We didn’t just upgrade AI. We gave it control.

↳ Full macOS control: cursor, keyboard, browser, files
↳ Plain English commands → real execution (“update CRM → send report”)
↳ Works without custom integrations (uses software like a human)
↳ Pair with “Dispatch”: assign tasks from your phone, come back to done work

We have finally transitioned from AI helps you do the work to → AI does the work for you.

This is the JARVIS moment for AI.

P.S. also check out Andrej Karpathy’s Method To 10X Your Claude Skills 🧠: https://lnkd.in/dAg2yXVJ

I gave Perplexity Computer access to my portfolio & told my AI trader:

“Turn this into $10M. Make no mistakes.”

It wrote 69 strategies.
Generated 1,500+ research reports.
Spun up 19 new algos.

It scraped X, Reddit, Instagram, and LinkedIn.
Mapped sentiment.
Read every chart pattern it could find.

It traded 24/7.

It lost everything.

But boy was it beautiful.

P.S. on a serious note, check out how I Turned Claude in Excel Into My Senior Financial Analyst 📈: https://lnkd.in/gAD58P2V

Brilliant: A mom uses AI to make her children's messes look like they're on the news 👏😂

One of the most creative ways to use AI I've seen.

Need to try this with my kids...

P.S. for more great stuff, check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets AI. For founders, builders, and leaders.

Anthropic quietly dropped a 23-page breakdown of how its teams use Claude Code internally. It basically rewrites how modern companies operate 😳

Surprisingly, it’s not about replacing engineers.
It’s about everyone else becoming one. 

Here’s what that actually looks like:

↳ Growth (team of one)

→ Cut ad copy creation from 2 hours to 15 minutes.
→ Built a Figma plugin generating 100 ad variants in half a second.
→ 10x creative output - no dedicated engineers.

↳ Data + Security

→ Kubernetes incident debugging: 10-15 minutes of manual scanning → ~5 minutes.
→ Terraform plans pasted in with one question: “Am I going to regret this?”

↳ Product team

→ Enabled “auto-accept mode” and let Claude run autonomous loops.
→ Built Vim mode with ~70% of the code written by Claude.

↳ Data science

→ Built a 5,000-line TypeScript React dashboard despite “very little JavaScript” experience.
→ 2-4x time savings on refactors.

↳ Legal

→ Built a custom accessibility app for a family member in one hour.
→ Created internal “phone tree” tools without traditional dev resources.

The pattern is clear: non-technical teams now ship software, while engineers move from typing to steering 🤖

Without Claude Code:

↳ Marketing waits for engineering
↳ Legal files tickets
↳ Designers hand off specs
↳ Data teams live in notebooks

With Claude Code:

↳ Marketing builds agents
↳ Legal ships prototypes
↳ Designers implement state changes
↳ Data teams deploy full React apps

Claude Code is not just a faster IDE.
It’s a leverage layer across the org.

Most importantly, the companies that win in the AI age won’t just have better models.

They’ll have more people who can build.

P.S. check out how I built an AI operating system to run a startup with Claude 🤖: https://lnkd.in/dv7-ZRVc

How Anthropic Teams Use Claude Code

Strategist | Growth Marketing🚀 | Fill My Funnel - The LinkedIn Ads Agency | Driving Pipeline for B2B Brands Globally

Hi, I'm Brinley👋

➡️ Faith-driven and passionate about growth marketing and digital strategy

➡️ Privileged to have helped over 125+ businesses grow their revenue, from bootstrapped and funded startups to agencies and enterprise companies with global portfolios. 

➡️ Key focus on growing revenue through RevOps and integrated growth marketing programs. 

➡️ Verticals include: Professional Service Businesses | SaaS | HRTech | FinTech | RegTech | AgTech | eCommerce | PropTech | HealthTech | EdTech 

➡️ I'm a senior strategist at Fill My Funnel, an official LinkedIn Marketing Partner. 

Europe's #1 B2B LinkedIn Ads agency with over £500M+ ad spend managed. Trusted by over 150 companies. We support growth by delivering predictable, qualified leads to accelerate pipeline and increase deal opportunities for startups, scaleups, SMEs, and multinationals.

Ready to scale your sales pipeline with LinkedIn Ads?
Learn more at: https://www.fillmyfunnel.co.uk/

====

🤝 Let's Connect: Send me a message to grab a virtual coffee!
👉 Follow me for insights and thoughts about Growth Marketing, Strategy, Faith, (and Cape Town!)

Brinley William Rebstein

Everyone says LinkedIn is too expensive.

Millions of customer journeys suggest it might be the most profitable B2B channel in the mix!

The latest Dreamdata Benchmarks Report is out!
(And it confirms something I’ve believed for a while)

LinkedIn is not “too expensive” as a marketing channel,
Truth is most marketers are measuring it the wrong way. 

Yes, LinkedIn clicks often look pricey.

BUT

Cheap clicks are completely overrated. Revenue in the bank is not!

According to Dreamdata’s 2026 benchmark report, #LinkedIn delivered the strongest return on ad spend of the major ad platforms at 121%, compared with 67% for Google Search and 51% for Meta. 

Point is, nobody marries on a first date, and in B2B the same principle applies before people buy.

People read.
They compare.
They ask colleagues.
And they forget about you.

Then, six months later, they suddenly “discover” the brand that has been showing up consistently all along when the decision hits their desk one morning.

The average B2B buying journey now takes 272 days and 81% of that journey happens before sales activity.

Simply said: most of the buying decisions happen before someone ever books a call with your team.

So if you are only judging LinkedIn by:
- cost per click
- leads this week
- last-click attribution

…you are probably completely undervaluing the channel that is doing all the heavy lifting early on.

It's the game most people miss.

TLDR

LinkedIn wins when you stop treating it like a cheap lead machine and start treating it like a trust-building, demand-shaping, pipeline-driving growth channel.

Not every click converts today.
But the right impressions compound.
The right message compounds. Being remembered compounds.

And in B2B, that is often where the real ROAS comes from.

Curious how other people are seeing this... Are most teams still too obsessed with cheap leads and not focused enough on revenue?

Source: Dreamdata’s LinkedIn Ads Benchmarks Report 2026 

(Download via link in comments)

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