Stani retweeted
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
It’s well within Anthropic’s rights to compete in any market they choose.
What’s funny, in this instance, are the number of Pharma companies, who through their unchecked use of Anthropic, are driving revenues into what they think is a model provider but is in fact a competitor lurking in the shadows thereby accelerating their own demise.
I suspect any end market with reasonable ROCE that could be AI accelerated is on the table.
If I were them, I’d probably do the same.
Coinbase:
AI-native pods: We’ll be concentrating around AI-native talent who can manage fleets of agents to drive outsized impact. We’ll also be experimenting with reduced pod sizes, including “one person teams” with engineers, designers, and product managers all in one role.
This is an email I sent earlier today to all employees at Coinbase:
Team,
Today I’ve made the difficult decision to reduce the size of Coinbase by ~14%. I want to walk you through why we're doing this now, what it means for those affected, and how this positions us for the future.
Why now
Two forces are converging at the same time. We need to be front footed to respond to both.
First, the market. Coinbase is well-capitalized, has diversified revenue streams, and is well-positioned to weather any storm. Crypto is also on the verge of the next wave of adoption, with stablecoins, prediction markets, tokenization, and more taking off. However, our business is still volatile from quarter to quarter. While we've managed through that cyclicality many times before and come out stronger on the other side, we’re currently in a down market and need to adjust our cost structure now so that we emerge from this period leaner, faster, and more efficient for our next phase of growth.
Second, AI is changing how we work. Over the past year, I’ve watched engineers use AI to ship in days what used to take a team weeks. Non-technical teams are now shipping production code and many of our workflows are being automated. The pace of what's possible with a small, focused team has changed dramatically, and it's accelerating every day.
All of this has led us to an inflection point, not just for Coinbase, but for every company. The biggest risk now is not taking action. We are adjusting early and deliberately to rebuild Coinbase to be lean, fast, and AI-native. We need to return to the speed and focus of our startup founding, with AI at our core.
What this means
To get there, we are not just reducing headcount and cutting costs, we’re fundamentally changing how we operate: rebuilding Coinbase as an intelligence, with humans around the edge aligning it. What does this mean in practice?
- Fewer layers, faster decisions: We are flattening our org structure to 5 layers max below CEO/COO. Layers slow things down and create coordination tax. The future is small, high context teams that can move quickly. Leaders will own much more, with as many as 15+ direct reports. Fewer layers also means a leaner cost structure that is built to perform through all market cycles.
- No pure managers: Every leader at Coinbase must also be a strong and active individual contributor. Managers should be like player-coaches, getting their hands dirty alongside their teams.
- AI-native pods: We’ll be concentrating around AI-native talent who can manage fleets of agents to drive outsized impact. We’ll also be experimenting with reduced pod sizes, including “one person teams” with engineers, designers, and product managers all in one role.
In short: AI is bringing a profound shift in how companies operate, and we’re reshaping Coinbase to lead in this new era. This is a new way of working, and we need to leverage AI across every facet of our jobs.
To those who are affected
I know there are real people behind these decisions — talented colleagues who have poured themselves into this company and our mission. To those of you who will be leaving: thank you. You’ve helped build Coinbase into what it is today, and I am sincerely grateful for everything you've done.
All impacted team members will receive an email to their personal account in the next hour with more information, and an invitation to meet with an HRBP and a senior leader in your organization. Coinbase system access has been removed today. I know this feels sudden and harsh, but it is the only responsible choice given our duty to protect customer information.
To those affected, we will be providing a comprehensive package to support you through this transition. US employees will receive a minimum of 16 weeks base pay (plus 2 weeks per year worked), their next equity vest, and 6 months of COBRA. Employees on a work visa will get extra transition support. Those outside of the US will receive similar support, based on local factors and subject to any consultation requirements.
Coinbase prides itself on talent density. Our employees are among the most talented people in the world, and I have no doubt that your skills and experience will be highly sought after as you pursue your next chapters.
How we move forward
To the team that is staying, I know this is a difficult day. We’re saying goodbye to colleagues and friends you've been in the trenches with. But here’s what I want you to know as we move forward together:
Over the past 13 years, we have weathered four crypto winters, gone public, and built the most trusted platform in our industry. We’ve made it this far by making hard decisions and by always staying focused on our mission. This time will be no different – nothing has changed about the long term outlook of our company or industry. And most importantly, our mission has never been more important for the world. Increasing economic freedom requires a new financial system, and we’re building it.
The Coinbase that emerges from this will be more capable than ever to achieve our mission.
Brian
🚀 Releasing nathan-cli
One CLI. 400+ integrations. No proxy, no cloud, no cost, runs 100% local.
npm install -g nathan-cli
GitHub, Slack, Jira, Airtable, HubSpot, OpenAI… all of n8n’s node ecosystem, directly from your terminal.
Stop writing MCP servers for every integration your agent needs.
npmjs.com/package/nathan-cli
#AIAgents #CLI #n8n #DevTools #automation
Perfect for AI agents with shell access.
Let them discover tools autonomously:
nathan plugin list → what’s available
nathan describe slack → what can I do?
nathan describe slack message post → what params?
Self-documenting. No custom tool definitions needed.
Stani retweeted
GraphQL to TypeScript type, no code gen.
Written purely in TypeScript type.
With Prisma-like query syntax fully type-safe.
Should cover almost all of the GraphQL specs, now.
Here's a demo.
Stani retweeted
Stephen Hawking ist in der Nacht zu Mittwoch gestorben. heise.de/news/Stephen-Hawkin…
Readers added context they thought people might want to know
Stephen Hawking starb nicht in der Nacht von Dienstag, 27.06.2023 auf Mittwoch, 28.06.2023; sondern am 14.03.2018.
Quelle: de.m.wikipedia.org/wiki/Stephen_H…
Stani retweeted
Attention Street Design Nerds! One of the most intriguing cities in recent years at reconsidering streets for people instead of just for cars, Oslo Norway, has translated their Street Design Manual into English and put it on-line. Worth digging into. #Oslo
oslo.kommune.no/getfile.php/…
Stani retweeted
Interesting article on why Japanese websites look so different to Western sites.
medium.com/@mirijam.missbich…
Stani retweeted
The new Next.js website is one of the best websites I've had the pleasure to work on together with @glennui. Here's a breakdown of some design details that were particularly exciting to craft.
rauno.me/craft/nextjs
Stani retweeted
The city of Melbourne 🇦🇺 did a study looking at how protected bike lanes change peoples willingness to bike:
participate.melbourne.vic.go…
Stani retweeted
AI hype is beginning to resemble the web3 and metaverse hype trains before it. No matter where you look on Twitter, you see folks making bold claims about the recent advances in AI.
Three sad realities of growing a Twitter following converge in the case of trends like metaverse in 2021, web3 in 2022, and AI in 2023:
1. Writing about trending topics works.
2. Making readers feel “I can’t believe that!” drives things to go viral.
3. Companies building on the latest trend are eager to advertise with large accounts.
This means that content creators have every incentive - from growth to engagement and monetization - to be as excited and uncritical as possible. As a result, every progression in AI is heralded as the next big thing.
The latest dubious claim from this hype train is that AutoGPT signals a turn to Artificial General Intelligence (AGI). This is usually accompanied by ominous pictures of Mr. Smith from The Matrix.
But, the fact is: GPT-4 and AutoGPT aren’t close to artificial general intelligence (AGI).
GPT-4 is dumb. It’s like the person at work who always sounds good, but never actually guides the company toward good decisions. GPT-4 sounds really smart. But it’s just a large language model (LLM). Its faculty with language and code has pulled the veil over everyone’s eyes.
GPT-4 can write beautifully for you. It can reconstruct what you want to say in one-hundred different ways. It can search the web and piece together intelligence from different parts of the web much faster than any human.
But once you ask GPT-4 to make hard decisions for you, it loses any ability to actually analyze the situation. That’s because it’s just a language model. It lacks a logical-semantic underneath to understand what it’s writing.
Auto-GPT is even dumber. For the 99.9% of people who can’t get off the GPT-4 waitlist, it runs on GPT-3.5. So it’s already at a disadvantage. On top of that, it’s just a large language model that can run other large language models. Its ability to give itself tasks has fooled everyone into thinking it’s a breakthrough.
GPT-4 and Auto-GPT have many limitations as artificial intelligence systems. They do not have a deep or broad understanding of the meaning or context of what they generate. They do not have a robust or flexible ability to reason, learn, or adapt beyond their training data. They do not have a clear or reliable way to explain their outputs or correct their mistakes. They do not have a direct or effective way to interact with the real world or achieve any goals.
These are some of the essential features of artificial general intelligence (AGI). AGI is the ability of a machine to perform any intellectual task that a human can do. AGI is not just a bigger or better version of GPT-4 or Auto-GPT. AGI is a fundamentally different kind of intelligence that requires new approaches and paradigms.
So don’t fall for the hype that we have “baby AGI.” Most of that is actually just semantic confusion, because one of the AutoGPT projects is named BabyAGI (made by my inimitable Twitter friend Yohei Inakajima).
These projects are a great step towards AGI, but they are not AGI.
Visited x.com it said it's not safe.
Stani retweeted
"I feel terrible about it because Ukraine is a very important country and I feel a personal stake because I got them to agree to give up their nuclear weapons and none of them believe that Russia would have pulled this stunt if Ukraine still had their weapons" - Bill Clinton in an interview to @MiriamOCal for @RTEOne





























