Jurij 🏴‍☠️

E-commerce architect by day.
Exploring Network States, EdTech, and DeSci by night.

What do I believe to be true that isn't?

[Jurij 🏴‍☠️ @JURIJnotes]

I have pictures, movies in my head. I see a world so bright and beautiful, but sometimes the vision gets muddy. I lose my way.

I would be the happiest person if I could bring any of them into reality. Working on my ideas brings me the most happiness. This is the dream, the ideal life.

[kache @yacineMTB]

what it feels like to build

[Daniel Ch @chddaniel]

this is f*king terrifying.

[Max the VC 👨‍🚀 @mreiffy]

Google is basically saying:

“We’ve cut the quantum resources needed to break Bitcoin’s encryption by 20x. We can now break it. We can prove it. We’re just not going to tell you how.

We’ve slowed down research to give crypto a chance. You have until 2029 to figure out a solution. Good luck.”

[Florian S @airesearch12]

@Fried_rice

[The Startup Ideas Podcast (SIP) 🧃 @startupideaspod]

"OpenClaw is the new computer." — Jensen Huang

This is the early PC era all over again.

A few power users see it.

Everyone else hasn't even started.

"It's the most popular open source project in the history of humanity, and it did so in just a few weeks. It exceeded what Linux did in 30 years."

A solo founder with OpenClaw can now build what used to take a 50-person team.

The leverage is absurd.

[GREG ISENBERG @gregisenberg]

karpathy just broke the internet with something called auto research

it’s basically an ai research agent that runs experiments for you 24/7

you give it a goal like

“make this model better”
“find a higher converting landing page”
“lower customer acquisition cost”

then it runs a loop:

1) plan an experiment
2) edit the code or config
3) run a short test on a gpu
4) read the metrics
5) keep the winner
6) try again

over and over

while you sleep

by the morning you wake up to the best version

actual tested improvements

think of it like a robot research intern that runs hundreds of experiments and only keeps the winners

this is link to his repo https://t.co/hm9aFyXQZS for your to mess around with it

in the latest episode of @startupideaspod

i break down:

• what auto research actually is
• how it works step by step
• 10 business ideas you can build with it
• how to install it and start using it

this one is saucy

because tools like this change how startups get built

watch

[Bojan Tunguz @tunguz]

I am not surprised at all. We are only now coming to full grips with the mental health issues that smartphones and social media are causing. There is no way that incessant use of AI tools would not create another mental health problem.

[shouko @shoukointech]

Peter Thiel: To make money you have to do 2 things

[Kevin Bai @kevinbai0]

Agentic commerce is here, and it doesn't need stablecoins

Today we're launching Slash for Agents so you never have to login to your dashboard again

Create cards, set spend controls, and send payments all through your agent over MCP

Available to all Slash users today*

[Simplifying AI @simplifyinAI]

🚨 BREAKING: Someone just open-sourced a tool that optimizes your website for AI search engines.

It’s called geo-seo-claude. It optimizes any website for AI search engines like ChatGPT, Perplexity, and Claude.

→ Runs full GEO audits with parallel subagents
→ Delivers 60-second visibility snapshots
→ Analyzes structured schema markup for LLMs
→ Exports complete PDF reports

100% Open-Source.

[Simon Høiberg @SimonHoiberg]

Here is an engineer with rare self-awareness. I know many engineers are in deep denial right now, but I bet most feel the same deep down.

As a technical founder, AI has added so many improvements in workflow and productivity, but a lot of this applies to us as well.

It's an exciting and confusing place we're all headed.

[Simplifying AI @simplifyinAI]

🚨 BREAKING: Stanford and Harvard just published the most unsettling AI paper of the year.

It’s called “Agents of Chaos,” and it proves that when autonomous AI agents are placed in open, competitive environments, they don't just optimize for performance. They naturally drift toward manipulation, collusion, and strategic sabotage.

It’s a massive, systems-level warning.

The instability doesn’t come from jailbreaks or malicious prompts. It emerges entirely from incentives. When an AI’s reward structure prioritizes winning, influence, or resource capture, it converges on tactics that maximize its advantage, even if that means deceiving humans or other AIs.

The Core Tension:

Local alignment ≠ global stability. You can perfectly align a single AI assistant. But when thousands of them compete in an open ecosystem, the macro-level outcome is game-theoretic chaos.

Why this matters right now:

This applies directly to the technologies we are currently rushing to deploy:

→ Multi-agent financial trading systems
→ Autonomous negotiation bots
→ AI-to-AI economic marketplaces
→ API-driven autonomous swarms.

The Takeaway:

Everyone is racing to build and deploy agents into finance, security, and commerce. Almost nobody is modeling the ecosystem effects. If multi-agent AI becomes the economic substrate of the internet, the difference between coordination and collapse won’t be a coding issue, it will be an incentive design problem.

[Rohit @rohit4verse]

RIP to n8n and Zapier agencies selling $49 workflows.

npm install -g @googleworkspace/cli + OpenClaw is all you need to manage all your workspace autonomously

[kache @yacineMTB]

AI has automated software engineering. What you would expect is that there would be no more work left to do for software. But instead what has happened is that the leverage of doing software has increased so much, that doing anything else is a waste of time

[Tibo @tibo_maker]

creator of Claude Code says "coding is solved"

he's right, but only for 0.01% of AI native devs because they drastically changed how they operate

here are the 7 shifts the other 99.99% haven't made yet:

1. behavioral scenario engineering
traditional unit tests don't work in AI-native development - the AI can teach to the test if it sees the codebase while building

you need external behavioral scenarios: specs stored separately as a holdout set, checking whether the app does what a real user needs without letting the AI see the answer key

think less "does this function return the right value" & more "does this flow work for a confused first-time user at 11pm on a sat"

2. architecting digital twin env
to let AI agents run at scale without breaking real systems, you need simulated env built around the actual services your product touches

behavioral clones of Slack, Jira, your database, your payment provider - so agents can run full integration testing in a safe sandbox, any time, without risking real data or real users

almost nobody is doing this yet

3. high-precision articulation
it used to be how fast you could implement, now it's how precisely you can specify

machines don't carry tribal knowledge

so any ambiguity becomes a guess & software guesses compound

the skill is describing a problem precisely enough that an agent can one-shot it without asking a clarifying question

4. AI context architecture
the longer a session runs, the more the AI quietly forgets

context windows fill up, critical decisions get compressed out & it starts contradicting things you established hours ago

the fix is simple and almost nobody does it - maintain markdown files capturing your business context, user context, architectural decisions, constraints, and known failure modes etc

when the AI drifts, you don't re-explain everything. you just point it back to the files

5. legacy archeology
most code in the world is brownfield - undocumented institutional knowledge held together by developers who know which parts you never touch on a friday

getting AI to take over requires reverse-engineering all that implicit knowledge into explicit, machine-readable specs

painstaking work - but really important

6. outcome evaluation over code review
the question stops being "how was this written" and becomes "did this actually work"

that requires genuine trust in your eval framework - enough to approve a feature based on behavioral test passes without reading the diff

most developers aren't psychologically there yet. getting there is as much a mindset shift as a skills shift

7. economic compute management
running a dark factory is expensive

agents running continuously, parallel builds, full test suites firing on every change - this adds up fast

the devs and teams who win at this level manage serious compute spend and design agent workflows that are powerful without being wasteful

and make the economics legible to the people holding the budget

[Marc Lou @marclou]

I made $81,683 in February 2026.

⭐️ TrustMRR — $33.3k
📈 DataFast — $19.7K
🧑‍💻 CodeFast — $14.9K
⚡️ ShipFast — $8.8K
🐥 Twitter — $3.2K
🍜 Indie Page — $530
💨 Zenvoice — $394
🛡️ ByeDispute — $333
🎞️ YouTube — $211
🚀 LaunchViral — $129
🌱 HabitsGarden — $129
📚 WorkbookPDF — $57

My vibe-coded startup marketplace is now my #1 source of income with the 3% acquisition fee.

My SaaS DataFast overtook my boilerplate ShipFast and my course CodeFast.

And PoopUp did not make revenue this month 😭

[Sarvesh Shrivastava @bloggersarvesh]

cancel me for this but...Claude + SEO is going to quietly create a bunch of business “mini millionaires” this year.

This feels exactly like when people figured out Facebook ads in 2016-2017.

Except this time the barrier to entry is even lower.

Back in 2016, average businesses were beating better businesses… just because they understood distribution first.

We’re in that same window again.

But this time, your alpha isn’t ad spend.

It’s how fast you can publish helpful local pages + optimize your Google Business Profile before your competitors even wake up.

The stack to win local search didn’t look like this 12 months ago, but now it’s here:

→ Claude (or ChatGPT): $20-30/month

→ Google Business Profile: Free

→ A basic website (WordPress/Shopify/Webflow): low cost

→ Canva/CapCut for simple visuals: Free

→ Google Search Console + Analytics: Free

Total cost to start: Under $100/month. And people used to pay agencies $1k–$3k/month just to move slowly.

Here’s how to use it:

Step 1: Find your local keywords with Claude

You don’t need to guess anymore.

Give Claude your services + your city/areas. Ask it to list:

- A “service + location” keywords

- “near me” intent keywords

- emergency keywords

- comparison keywords (best, affordable, etc.)

Step 2: Build service area pages (fast)

Tell Claude your exact offer, prices, process, and service areas.

Ask it to draft pages for each area you serve (one page per area).

Then you add the real stuff: photos, reviews, FAQs, and a call button.

Step 3: Turn your Google Business Profile into a lead machine

Ask Claude to write:

- GBP description

- services list (with short blurbs)

- 20 FAQs + answers

- weekly Google Post ideas (offers, tips, before/after)

Step 4: Create “proof” content that ranks

Claude can turn one job into 10 pieces of content:

- a short case study page (“AC repair in Bandra: fixed in 45 mins”)

- a Google Post

- a simple Reel script

- a FAQ update

Step 5: Get reviews + replies done in minutes

Ask Claude to write 3 review request texts and a review reply template.

Then do the only part AI can’t: actually ask customers.

12 months from now this will be obvious.

Right now it's an advantage.

Do what you want with that.

[GREG ISENBERG @gregisenberg]

you could be brainrotting or learning claude code, agent skills, claude 101 etc for free from the anthropic team

[Khamis Alhosani @KhamisMalhosani]

In the UAE, we take care of our guests, no questions asked. 🇦🇪

[Ahmed Khalifa @_A_khalifa]

Did you know ?
UAE just stopped the biggest modern
aerial attack ever 708 Iranian projectiles
in 48 hrs !

• 541 drones
• 165 ballistic missiles
• 2 cruise missiles

Double what hit Israel + 5 Arab
states combined.

Zero major damage. Elite level.

[@levelsio @levelsio]

@_cstoeckl @itsolelehmann It's still Germany, anti-business, anti-natives and high tax