marcin strzalkowski

Build. Develop. Breath. Repeat.

[Arnaud Bertrand @RnaudBertrand]

By the way, in order for AI to indeed create wealth and "abundance", it needs to increase productivity - which pretty much means it needs to replace some jobs.

That's one of the contradictions in today's public discourse on AI: we simultaneously scaremonger around it destroying jobs and hope it creates unprecedented abundance, without acknowledging that the latter requires the former.

The thing people should be more scared by, IMHO, is if AI does NOT increase productivity because it'd mean the size of the cake stays the same, only distributed differently.

That's, in a way, the core of the battle between closed source and open source: the Anthropics and OpenAIs of this world want to appropriate, thanks to AI, a big share of the global wealth cake, while open source ensures the AI cake slice gets shared rather than captured.

You want open source to prevail even if the cake overall gets bigger but you REALLY want it if the cake stays the same size, because then it's a zero sum game - purely a question of who takes from whom.

That would be the real AI dystopia: AI not increasing productivity and closed source winning. In that scenario, AI becomes nothing more than a wealth transfer mechanism to major AI firms.

It's also, unfortunately, probably the most likely scenario.

First of all, there is a precedent: it's exactly what happened with the internet. Contrary to popular belief, the internet did not increase productivity: Total Factor Productivity growth fell from 1.4% (1950-1999) to 0.9% (2000-2024) (https://t.co/8FB0O9iDGS). So: peak internet penetration coincided with the worst productivity performance on record.

In effect, what that means is what we all witnessed: the so-called FAANG captured a massive share of the economy's value without actually expanding it. They became trillion-dollar companies not by making the pie bigger, but by redirecting where the money flows - from Main Street retail to Amazon, from local advertising to Google and Facebook, from the entertainment industry to Netflix.

It's also what initial data on AI's impact on jobs suggests: so far the displacement isn't showing up anywhere. Anthropic's own economists (https://t.co/NZQxtSctTD), an NBER study of 25,000 Danish workers (https://t.co/kQTrFNTvcw), the Stanford AI Index (https://t.co/YAOXvB1LJ7) - all three reach the same conclusion: no aggregate job losses. Which, if you follow the logic above, is exactly the bad news.

And it's of course what AI frontier labs keep lobbying the US government for: they want to deploy lawfare against Chinese open source precisely because they understand better than anyone that their trillion-dollar valuations depend not on AI growing the economy, but on establishing a toll booth position to extract rent from it.

In fact it's a vicious circle: the more successful closed source labs are at extracting rent, the more the economy's AI gains go to them rather than to the businesses that could use AI to actually produce more. Rent-seeking and productivity growth actively work against each other.

So, yes, paradoxically the best-case scenario is the one the media scaremonger against: AI replacing jobs and Chinese open source prevailing. Because the first means the cake is actually growing, and the second means no one gets to hoard it.

[Ole Lehmann @itsolelehmann]

should be obvious by now, but OpenAI and Anthropic are just gonna keep cannibalizing all their biggest customers.

it’s simply too profitable for them to resist. and it’s already happening:

1. Figma partnered with Anthropic on AI design tools. then Anthropic’s product chief quit Figma’s board, and 3 days later Anthropic launched Claude Design to compete with Figma. CEO Dylan Field said Anthropic was “not consistently candid.”

2. Novo Nordisk uses Claude to help develop drugs. now Anthropic is developing drugs of its own.

3. Microsoft poured billions into OpenAI. now OpenAI is building a Jobs Platform to compete with LinkedIn, and reportedly a code repository to compete with GitHub. Microsoft owns both.

4. Harvey uses Claude to sell AI contract analysis, due diligence, and litigation tools. now Anthropic sells those same workflows through Claude for Legal.

5. Intercom used OpenAI’s Realtime API to build Fin Voice. now OpenAI sells its own voice-and-chat support agent through Presence.

6. Abridge and Ambience build clinical documentation products on OpenAI. now OpenAI sells ChatGPT for Healthcare directly to hospitals with clinical documentation built in.

7. Benchling uses Claude to power its biotech R&D platform. now Anthropic sells its own scientific workbench through Claude Science.

the frontier lab playbook is simple:

1. sell their models to the world’s most valuable businesses
2. help wire them into those companies’ most valuable and sensitive work
3. map the business from the inside and find where AI can take over
4. turn those capabilities into their own products and become the customer’s competitor

[Aakash Gupta @aakashgupta]

Four months ago this level of agentic performance shipped only in Anthropic's most expensive model. Today it's the default model for free accounts.

That's the actual story, and Sonnet 5 is almost incidental to it.

The numbers: Sonnet 5 hits 63.2% on agentic coding versus Opus 4.8's 69.2%. Call it 91% of the flagship. On at least one knowledge-work benchmark it edges Opus 4.8 outright. Intro pricing is $2 per million input tokens and $10 per million output, and it's what every Free and Pro user now gets by default.

A capability that was a premium, paywalled moat in February is the commodity baseline in June.

Run that cadence forward. Frontier intelligence is depreciating on roughly a four-to-six month half-life. Whatever sits at the top of the price-performance curve today drops into the cheap tier before most teams finish the deck explaining why they need the expensive one.

If your product's moat was access to expensive intelligence, that moat is a lease, and the lease keeps resetting in someone else's favor.

The real product Anthropic shipped today is that depreciation schedule. And it discounts everyone's pricing power, Anthropic's included.

[Patrick OShaughnessy @patrick_oshag]

Three years ago, two Harvard dropouts set out to build a better AI chip than the largest companies in the world.

Almost everyone I called at the time said it was impossible.

Today, Etched (@Etched) comes out of stealth with $800M total raised, $1B in signed customer contracts, and a working next-gen AI chip.

This was my excuse to ask the two founders, @UbertiGavin and @robertwachen, every question I have about compute and inference.

We discuss:
- Why they built an entire rack and not just a chip
- The two technical bets behind their architecture no one else has tried
- How two founders in their twenties recruited industry legends
- The night they nearly ran out of money
- Why whoever produces the most tokens wins

If you care about the future of compute, Gavin and Rob are two people to know. I think you will find the story of what they have built hard to forget.

Enjoy!

TIMESTAMPS
0:00 Intro
1:00 Why Nobody Believed Etched Would Work
14:06 Why Inference Is the Bottleneck
22:27 Gavin and Rob’s Origin Stories
33:24 Taking Huge Risks to Move Faster
49:43 Kernels, Compilers, and the AI Stack
1:02:08 Raising $100M to Survive
1:16:00 The Future of Models, Agents, and Intelligence

[Mo Elgaraihy @EngMoElgaraihy]

الصين تفجر أكبر قنبلة علمية وتدخل بالذكاء الاصطناعي إلى عصر "الماتريكس" الفعلي؛ فريق Qwen الشهير بنى شيئاً مرعباً سيغير طريقة تطوير الـ AI للأبد

​الفكرة ببساطة: بدلاً من تدريب الذكاء الاصطناعي على كيفية استخدام الإنترنت أو نظام الأندرويد أو اللابتوب، قاموا ببناء موديل خارق اسمه Qwen-AgentWorld ومهمته أنه "يحاكي ويتخيل" أنظمة التشغيل والإنترنت والـ Terminal بالكامل داخل عقله البرمجي!

​يعني الموديل أصبح عبارة عن "عالم افتراضي كامل" يضم 7 بيئات تشغيلية ضخمة داخله؛ يتفوق في دقة محاكاتها على أعتى الموديلات الحالية مثل GPT-5.4 و Claude Opus 4.8

[𝐊𝐚𝐦𝐢𝐥 𝐏𝐚𝐰𝐥𝐢𝐤 @plKamilPawlik]

Japoński startup Sakana AI zaprezentował system Fugu: nowy typ architektury, w której jeden model pełni rolę „orkiestratora” dla wielu wyspecjalizowanych modeli dostępnych przez jedno API. Model sam deleguje zadania, weryfikuje odpowiedzi i może rekurencyjnie wywoływać samego siebie przy bardziej złożonych problemach.

Podobno nawet bardziej zaawansowana wersja – Fugu Ultra – osiąga wyniki porównywalne z Claude Fable 5 i Mythos Preview od Anthropic. No ciekawie.

[Alvin Foo @alvinfoo]

Most executives are using AI like a chatbot.

The highest-performing executives are building an AI Operating System.

The difference is massive.

Instead of starting from scratch every day, they create systems that help them:

✓ Capture organizational knowledge
✓ Run projects faster
✓ Automate repetitive workflows
✓ Produce executive-level outputs consistently
✓ Make better decisions with less effort

That’s why I believe every executive needs an AI Operating System in 2026.

The framework is simple:

1️⃣ AI Workspace
Create a centralized knowledge hub for your business, role, and industry.

2️⃣ AI Projects
Build dedicated workspaces for strategy, operations, sales, marketing, and key initiatives.

3️⃣ AI Skills
Develop repeatable workflows for research, analysis, communication, and execution.

4️⃣ AI Execution
Turn insights into actions and scale your impact across the organization.

The executives who thrive in the next decade won’t necessarily be the ones who know the most.

They’ll be the ones who can leverage AI most effectively.

AI is no longer a tool.

It’s becoming your second brain.

How are you using AI in your daily workflow today?

PS. Get a FREE AI Diagnostic and subscribe to our AI newsletter at https://t.co/I4zR8aXpsx

[Hedgie @HedgieMarkets]

🦔GitHub Copilot switched to token-based billing this morning and users are already out of credits. Pro+ subscribers paying $39 a month are reporting 60% of their credits gone in two hours of normal use. One user lost 20% of their allowance from a single file review with no code changes. Another hit their monthly cap before the calendar even flipped to June.
Orgs with shared token pools have no way to see individual usage, so entire teams get cut off when one person runs a heavy prompt. Users are canceling and moving to Claude Code and Codex. GitHub community forums are on fire.

My Take
Flat-rate AI subscriptions were always subsidized. Everyone in the industry knew it. Today the subsidy ran out for a few million developers at once. The problem is a lot of companies already restructured around these tools. They cut headcount and told remaining engineers to lean on Copilot instead of building skills internally. Those companies now depend on a tool whose cost just became unpredictable and whose usefulness completely changes when you have to ration prompts to stay under budget.

The developers moving to Claude Code and Codex will hit the same wall eventually. Every AI provider faces the same unit economics. Anthropic filed its S-1 this morning, and the durability of its revenue depends on whether customers stick around once real pricing kicks in everywhere. If a $39 subscriber cancels after one day because the tool became unusable, multiply that across millions of seats and the churn risk becomes very real.

Today showed what happens when AI pricing meets reality. The companies that built their workflows around cheap tokens just discovered the tokens aren't cheap anymore and the people who knew how to do the work without them are already gone.

Hedgie🤗

[Tomasz Karwatka @tomik99]

One of the reasons I stopped investing in AI SaaS 2 years ago.

Most “AI startups” are just temporary wrappers around foundation models.

1. Writing tools.
2. Support AI.
3. Sales AI.
4. Knowledge management.

4 categories.

Billions in valuation.
Potentially collapsed into one AI workspace + connectors + skills.

The moat is disappearing faster than most founders and VCs want to admit.

[Founder Thoughts & Strategies @mogulinfluence]

Read this if you want to know what YC and Sequoia are actually betting on in AI space right now:

[Jukan @jukan05]

I read Goldman Sachs’ AI report, and I was genuinely impressed.

The core insight is as follows:

Agentic AI could turn AI from a capex-heavy cost burden into a business where usage growth drives margin expansion. As token costs fall, more complex agents become economically viable. These agents then consume far more tokens through longer context windows, repeated reasoning loops, validation, tool use, and always-on background monitoring.

This increase in token usage improves infrastructure utilization, strengthens unit economics, and gives hyperscalers and model providers more room to reinvest in model quality, distribution, and capacity.

In other words, the bull case for AI capex is not simply that usage will grow. It is that this usage growth can increasingly flow through at attractive incremental margins. Goldman Sachs argues that this margin inflection is beginning to appear from 2026 onward.

[OpenAI @OpenAI]

GPT-5.5 Instant is starting to roll out in ChatGPT.

It’s a big upgrade, giving you smarter, clearer, and more personalized answers in a warmer, more natural tone.

And it's also more concise, which we heard you wanted. We think you'll love chatting with it.

[Rohit @rohit4verse]

https://t.co/8j0qNyJCYF

[vas @vasuman]

https://t.co/YlOT9k0U7E

[Mgoes (bio/acc 🤖💉) @m_goes_distance]

most people have no idea what is coming

- genome sequencing just crossed $100, down from $100M in 25 years
- peptides just went from felony to federal policy
- psychedelics just got a presidential executive order
- epigenetic reprogramming just entered human trials for the first time in history
- embryo editing is no longer a thought experiment: it is a clinical conversation

every single thing bio/acc has been bullish about for 2 years is breaking out simultaneously

honestly not a trend anymore

this is an inflection point

the next 6-12 months will be the most important period in the history of human biology

bio/acc

[Aakash Gupta @aakashgupta]

Microsoft just turned an $11 billion startup into a Word feature.

Harvey raised $200M at an $11B valuation in March on the bet that legal AI is its own surface. The numbers held that up. $190M ARR per TechCrunch's December reporting. 100,000 lawyers across 1,300 organizations including the majority of the AmLaw 100. Around $1,200 per lawyer per month per Sacra. Big firms paid because Harvey was the only tool in the category that worked.

Brad just stapled a legal agent directly inside Microsoft Word, shipping in the $30 per seat Copilot subscription every law firm already pays for. Same surface every lawyer drafts in. Same .docx that gets sent and redlined. No second login, no procurement cycle, no migration. The price gap is roughly 40x.

The interesting tell: Microsoft built the agent with legal engineers, many of them from Robin AI, a legal AI startup that recently went under, per Artificial Lawyer's reporting. The talent that knew how to make legal AI work for lawyers landed at Microsoft after their startup couldn't survive standalone. That's the legal AI category in one sentence.

Distribution was always the constraint here. Lawyers don't switch tools. Word is where contracts get drafted, redlined, and tracked. Whichever AI lives inside that .docx wins the default workflow, and Microsoft just walked through the door uncontested.

Harvey's surviving moat is the AmLaw 100 partner workflow. Domain training, agentic litigation prep, deep integrations with iManage and NetDocuments. Real moat for $1,500-an-hour partners running M&A and complex litigation. It does not extend to the millions of lawyers globally drafting NDAs, redlining vendor contracts, and updating templates. That layer is exactly what Word Legal Agent goes after, and Microsoft can ship it as a feature inside a $360-a-year subscription.

The $11B valuation pays out only if legal AI work stays its own surface. Microsoft just absorbed the surface.

[Szymon Rybczak @SzymonRybczak]

More Polish founders 🇵🇱 are showing up in YC and SF, and I’m excited to help build the “Polish mafia” 😁

Had a really great chat yesterday with @brycent!

If you’ve been thinking about applying to YCombinator, this might be your moment, application deadline is May 4!

[Mario Nawfal @MarioNawfal]

Elon summed up his entire philosophy in 3 words:

“My philosophy is curiosity & adventure.”

No corporate fluff. No mission statements.

Just pure wonder + the balls to explore the universe

He’s him.

[Micah @HowToUseAI_]

@doodlestein In a positive light, you can imagine so many concepts now, illustrate them quickly, and then the real work is all around bringing those concepts to life. Which is way better than spending months just trying to get to the point of inspiration.