AI-pill your whole company with the Every Agent: https://xitter.cf/t.co/ki3hyz8sVP
Joined September 2012
- Tweets7.6K
- Following140
- Followers58.2K
- Likes7.6K
Every 📧 retweeted
use artifacts to show you multiple layouts + product questions that you should answer
ask claude to make a video of the flow or concept (with the cursor moving and click/tap)
make personal tools. i made one to learn origami and another to quiz me on my draft PRs
Every 📧 retweeted
I am working on the Frontier at @every
Meet the team and more!
keeping up with AI is a full-time job. that's why every company needs a frontier team:
the frontier team's job is to keep up as models change. everyone else's job is to use what they learn
we made one @Every and it's completely changed how we work:
0:00 Introduction: Why every company needs a frontier team
2:42 Why the best frontier teams have pirates and architects
4:57 How Head of Evals @hammer_mt builds personal benchmarks
6:46 How Opus edited an explainer video using Slack messages and meeting notes
10:20 Working with AI means protecting other people’s attention
12:26 Why a frontier team needs a “wrangler” like Arielle Shipper
18:58 Why senior editor @jackcheng built a tabless browser
24:37 How resident writer @kplikethebird teaches her AI writing plugin who the reader is
30:51 Inside engineer @JannikJung’s personal AI orchestrator
35:41 Compound engineer @kieranklaassen uses AI to build power tools
Every 📧 retweeted
The frontier team is easily one of the coolest within @every and @kieranklaassen is like the frontieriest of the frontier
Every 📧 retweeted
I'm in the frontier team at a frontier company on the frontier of AI
keeping up with AI is a full-time job. that's why every company needs a frontier team:
the frontier team's job is to keep up as models change. everyone else's job is to use what they learn
we made one @Every and it's completely changed how we work:
0:00 Introduction: Why every company needs a frontier team
2:42 Why the best frontier teams have pirates and architects
4:57 How Head of Evals @hammer_mt builds personal benchmarks
6:46 How Opus edited an explainer video using Slack messages and meeting notes
10:20 Working with AI means protecting other people’s attention
12:26 Why a frontier team needs a “wrangler” like Arielle Shipper
18:58 Why senior editor @jackcheng built a tabless browser
24:37 How resident writer @kplikethebird teaches her AI writing plugin who the reader is
30:51 Inside engineer @JannikJung’s personal AI orchestrator
35:41 Compound engineer @kieranklaassen uses AI to build power tools
Every 📧 retweeted
keeping up with AI is a full-time job. that's why every company needs a frontier team:
the frontier team's job is to keep up as models change. everyone else's job is to use what they learn
we made one @Every and it's completely changed how we work:
0:00 Introduction: Why every company needs a frontier team
2:42 Why the best frontier teams have pirates and architects
4:57 How Head of Evals @hammer_mt builds personal benchmarks
6:46 How Opus edited an explainer video using Slack messages and meeting notes
10:20 Working with AI means protecting other people’s attention
12:26 Why a frontier team needs a “wrangler” like Arielle Shipper
18:58 Why senior editor @jackcheng built a tabless browser
24:37 How resident writer @kplikethebird teaches her AI writing plugin who the reader is
30:51 Inside engineer @JannikJung’s personal AI orchestrator
35:41 Compound engineer @kieranklaassen uses AI to build power tools
Every 📧 retweeted
Excited to be doing a live fireside with @Bencera and @bran_don_gell at @every’s Thesis in early November.
Polsia is about to hit $25M run rate.
Next stop: $100M ARR.
And things keep accelerating:
$0 → $1M in 12 weeks
$1M → $10M in 10 weeks
$10M → $20M in 6 weeks
I just published one of my favorite and most successful aisloP episodes yet: “The Run Rate.”
I tell the whole story, from idea to $20M, month by month.
The episode ends in Tokyo, where I went a few weeks ago.
Probably the best place on Earth to take a deep breath, get inspired, and rethink what’s possible.
I came back with an even bolder vision for Polsia.
The road from $25M to $100M is going to look very different.
Polsia v2 is coming soon.
Every 📧 retweeted
Re-upping this on main: I've been working in a Google doc in Claude's in-app browser all day and giving edits to agents to execute as suggestions, and they're going in like a dream.
As an AI-pilled writer, this is happiness.
Every 📧 retweeted
Remixed the interviews from @danshipper's Codex piece into a playable visual novel and cut a trailer for it
Every 📧 retweeted
For the design of @every's How Codex Happened, we started with the history of thinking, machines, and thinking machines.
I did some experiments with Codex (obviously), we got ideas and feedback from @danshipper, and then @dealville brought it all to life.
See the results (and read the piece for free) here: every.to/p/how-codex-happene…
Every 📧 retweeted
A must read from @every and its free.
Our definitive history of how Codex happened.
Read for free: every.to/p/how-codex-happene…
Every 📧 retweeted
Amazing encapsulation of @ajambrosino.
One time a waiter in Palo Alto thought Andrew *was* BJ Novak and Andrew just let it ride. Never corrected him.
Great piece @danshipper.
Codex is one of the most important untold stories in the history of technology.
A year ago, it was a scrappy effort in a quiet corner of @OpenAI. Its cloud product hadn’t found PMF, and the team was starting over from scratch.
Less than 12 months later:
- Codex swallowed the flagship ChatGPT desktop app from the inside (it literally runs as com.openai.codex on your Mac)
- Codex and ChatGPT for Work hit 40M+ weekly users across engineering and knowledge work
- Its leader @thsottiaux was elevated to run all of OpenAI’s core products, including ChatGPT, Codex, and the API
How did they pull it off?
They trained their own dedicated model line, separate from ChatGPT, with researchers and product builders sitting on the same team
They built four different products in a single year (cloud → terminal → IDE sidebar → a desktop app with no code editor at all) as every model leap made a new form factor possible
They used Codex to build Codex—so a handful of people could prove a new product in weeks instead of arguing for it in meetings
I had a front-row seat to the whole arc—from their failed Cloud launch, to OpenAI’s offices the night before GPT-5 dropped, to the day Codex took over ChatGPT.
And I spent months interviewing @gdb, @thsottiaux, @embirico, @mia_glaese, @aambrosino, and @edbayes to get inside how it all went down.
Here is the full, behind-closed-doors story of the team that remade OpenAI:
every.to/p/how-codex-happene…
We’re pushing the boundaries of how stories like this are told.
This piece is completely agent-native—designed to be read alongside your agent inside ChatGPT’s in-app browser:
- Every interview transcript is included in full: Click any quote and you (or your agent) can see the exact conversation it came from.
- Built for your agent to explore: Ask your agent to pull out product lessons for your team, cross-examine the transcripts, or find insights I missed when writing the piece.
It’s a story about the future of software—built to be read with an agent:
every.to/p/how-codex-happene…
Every 📧 retweeted
This is the kind of incredible reporting, writing, and super innovative agent-native storytelling that made me want to work at @every
@danshipper is doing the kinda creative work in a post-AI world that is legit inspiring to me... AND you can come work with us... We're hiring
Codex is one of the most important untold stories in the history of technology.
A year ago, it was a scrappy effort in a quiet corner of @OpenAI. Its cloud product hadn’t found PMF, and the team was starting over from scratch.
Less than 12 months later:
- Codex swallowed the flagship ChatGPT desktop app from the inside (it literally runs as com.openai.codex on your Mac)
- Codex and ChatGPT for Work hit 40M+ weekly users across engineering and knowledge work
- Its leader @thsottiaux was elevated to run all of OpenAI’s core products, including ChatGPT, Codex, and the API
How did they pull it off?
They trained their own dedicated model line, separate from ChatGPT, with researchers and product builders sitting on the same team
They built four different products in a single year (cloud → terminal → IDE sidebar → a desktop app with no code editor at all) as every model leap made a new form factor possible
They used Codex to build Codex—so a handful of people could prove a new product in weeks instead of arguing for it in meetings
I had a front-row seat to the whole arc—from their failed Cloud launch, to OpenAI’s offices the night before GPT-5 dropped, to the day Codex took over ChatGPT.
And I spent months interviewing @gdb, @thsottiaux, @embirico, @mia_glaese, @aambrosino, and @edbayes to get inside how it all went down.
Here is the full, behind-closed-doors story of the team that remade OpenAI:
every.to/p/how-codex-happene…
We’re pushing the boundaries of how stories like this are told.
This piece is completely agent-native—designed to be read alongside your agent inside ChatGPT’s in-app browser:
- Every interview transcript is included in full: Click any quote and you (or your agent) can see the exact conversation it came from.
- Built for your agent to explore: Ask your agent to pull out product lessons for your team, cross-examine the transcripts, or find insights I missed when writing the piece.
It’s a story about the future of software—built to be read with an agent:
every.to/p/how-codex-happene…
Every 📧 retweeted
Codex is the kind of product that deserves a definitive history, and @danshipper's written it!
As someone who was personally Codex-pilled by Dan AND got to tag along with to the OpenAI offices for some of the reporting for this piece, it's so exciting to see this out in the world.
Codex is one of the most important untold stories in the history of technology.
A year ago, it was a scrappy effort in a quiet corner of @OpenAI. Its cloud product hadn’t found PMF, and the team was starting over from scratch.
Less than 12 months later:
- Codex swallowed the flagship ChatGPT desktop app from the inside (it literally runs as com.openai.codex on your Mac)
- Codex and ChatGPT for Work hit 40M+ weekly users across engineering and knowledge work
- Its leader @thsottiaux was elevated to run all of OpenAI’s core products, including ChatGPT, Codex, and the API
How did they pull it off?
They trained their own dedicated model line, separate from ChatGPT, with researchers and product builders sitting on the same team
They built four different products in a single year (cloud → terminal → IDE sidebar → a desktop app with no code editor at all) as every model leap made a new form factor possible
They used Codex to build Codex—so a handful of people could prove a new product in weeks instead of arguing for it in meetings
I had a front-row seat to the whole arc—from their failed Cloud launch, to OpenAI’s offices the night before GPT-5 dropped, to the day Codex took over ChatGPT.
And I spent months interviewing @gdb, @thsottiaux, @embirico, @mia_glaese, @aambrosino, and @edbayes to get inside how it all went down.
Here is the full, behind-closed-doors story of the team that remade OpenAI:
every.to/p/how-codex-happene…
We’re pushing the boundaries of how stories like this are told.
This piece is completely agent-native—designed to be read alongside your agent inside ChatGPT’s in-app browser:
- Every interview transcript is included in full: Click any quote and you (or your agent) can see the exact conversation it came from.
- Built for your agent to explore: Ask your agent to pull out product lessons for your team, cross-examine the transcripts, or find insights I missed when writing the piece.
It’s a story about the future of software—built to be read with an agent:
every.to/p/how-codex-happene…
Every 📧 retweeted
Dan was one of the first ones to keep annoying everyone to say to use Codex. And I use it today.
Codex is one of the most important untold stories in the history of technology.
A year ago, it was a scrappy effort in a quiet corner of @OpenAI. Its cloud product hadn’t found PMF, and the team was starting over from scratch.
Less than 12 months later:
- Codex swallowed the flagship ChatGPT desktop app from the inside (it literally runs as com.openai.codex on your Mac)
- Codex and ChatGPT for Work hit 40M+ weekly users across engineering and knowledge work
- Its leader @thsottiaux was elevated to run all of OpenAI’s core products, including ChatGPT, Codex, and the API
How did they pull it off?
They trained their own dedicated model line, separate from ChatGPT, with researchers and product builders sitting on the same team
They built four different products in a single year (cloud → terminal → IDE sidebar → a desktop app with no code editor at all) as every model leap made a new form factor possible
They used Codex to build Codex—so a handful of people could prove a new product in weeks instead of arguing for it in meetings
I had a front-row seat to the whole arc—from their failed Cloud launch, to OpenAI’s offices the night before GPT-5 dropped, to the day Codex took over ChatGPT.
And I spent months interviewing @gdb, @thsottiaux, @embirico, @mia_glaese, @aambrosino, and @edbayes to get inside how it all went down.
Here is the full, behind-closed-doors story of the team that remade OpenAI:
every.to/p/how-codex-happene…
We’re pushing the boundaries of how stories like this are told.
This piece is completely agent-native—designed to be read alongside your agent inside ChatGPT’s in-app browser:
- Every interview transcript is included in full: Click any quote and you (or your agent) can see the exact conversation it came from.
- Built for your agent to explore: Ask your agent to pull out product lessons for your team, cross-examine the transcripts, or find insights I missed when writing the piece.
It’s a story about the future of software—built to be read with an agent:
every.to/p/how-codex-happene…
Every 📧 retweeted
this is a great read and a very fun agent-native format
Codex is one of the most important untold stories in the history of technology.
A year ago, it was a scrappy effort in a quiet corner of @OpenAI. Its cloud product hadn’t found PMF, and the team was starting over from scratch.
Less than 12 months later:
- Codex swallowed the flagship ChatGPT desktop app from the inside (it literally runs as com.openai.codex on your Mac)
- Codex and ChatGPT for Work hit 40M+ weekly users across engineering and knowledge work
- Its leader @thsottiaux was elevated to run all of OpenAI’s core products, including ChatGPT, Codex, and the API
How did they pull it off?
They trained their own dedicated model line, separate from ChatGPT, with researchers and product builders sitting on the same team
They built four different products in a single year (cloud → terminal → IDE sidebar → a desktop app with no code editor at all) as every model leap made a new form factor possible
They used Codex to build Codex—so a handful of people could prove a new product in weeks instead of arguing for it in meetings
I had a front-row seat to the whole arc—from their failed Cloud launch, to OpenAI’s offices the night before GPT-5 dropped, to the day Codex took over ChatGPT.
And I spent months interviewing @gdb, @thsottiaux, @embirico, @mia_glaese, @aambrosino, and @edbayes to get inside how it all went down.
Here is the full, behind-closed-doors story of the team that remade OpenAI:
every.to/p/how-codex-happene…
We’re pushing the boundaries of how stories like this are told.
This piece is completely agent-native—designed to be read alongside your agent inside ChatGPT’s in-app browser:
- Every interview transcript is included in full: Click any quote and you (or your agent) can see the exact conversation it came from.
- Built for your agent to explore: Ask your agent to pull out product lessons for your team, cross-examine the transcripts, or find insights I missed when writing the piece.
It’s a story about the future of software—built to be read with an agent:
every.to/p/how-codex-happene…
Every 📧 retweeted
A few months ago I migrated our vibe-coded CRM to @attio betting that they would improve the product in unique and value-add ways. It’s been a good bet so far!
In the age of agents, systems of record have never mattered more. They’ve also never been less prepared for what’s coming.
Today, we’re announcing @attio's hybrid architecture, with the controls of application software at the scale of infrastructure.
To agents, Attio looks like a database, queryable in SQL - a language they're RL’d on. Unlike a database, the business logic, policies, and compliance sit behind the query.
This makes all of Attio’s data accessible by agents in the most powerful and flexible syntax. It gives GTM teams an order of magnitude more value from their time, with the full power of agents working across the entire customer lifecycle.
A new shape of software is here.
attio.ai/architecture
Every 📧 retweeted
“The best people I’ve seen building things are playing” says @MattHartman, who wrote the first check into @huggingface (sold to Nvidia for ~$13B)
His approach is to find the newly technically possible, then find the founders already tinkering there. He's backed @factoryai, @modal & more.
Always a treat to chat & special shoutout to @mignano & @alxai_ referenced on the pod! đź‘‹
.@MattHartman assumes every early-stage startup will pivot. That's why he backs technical founders who can "move with where the world goes." Now founder and managing partner of Factorial Capital, Hartman was part of the Betaworks team that wrote @huggingface's first check in 2016—when it was still a chatbot app for teenagers, before it became the largest community for open-source AI, set to be acquired by @nvidia for $13 billion. On this week's episode of The Every Podcast, he tells @NataliaZarina how he spots new opportunities, what makes a founder's insight worth backing, and why vibe-coding his own app gave him a new respect for SaaS.
Introduction
How Hugging Face went from a teen chatbot to the home of open-source AI
The three decisions that set Hugging Face on its path
Hartman's approach to finding the newly technically possible
Why Hartman backs technical founders
How Factorial’s portfolio founders source its next deals
Why faster iteration makes product insight the most valuable skill
What Hartman learned building Ghost Pepper, an open-source voice-to-text app
Hartman's current theses, from non-language models to full-stack AI apps
Why the best founders right now are experimenting