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Public posts from the accounts Tech Twitter monitors, in the selected window. Findings need three supporting authors and a published source. Announcements can cite one known-affiliated account. This is a sample of the conversation, not a survey or a measure of adoption.
The posts behind the picture
Public source posts
@aakashgupta
I wrote a PRD with ChatGPT and handed it to the CEO of Zapier to grade on camera.
Wade Foster's first move was to separate two things I had merged. Part of the question was AI fluency. The other part was just whether the product thinking was any good, and he graded that first.
The idea held up. Zapier's connector library wired into Claude Code, running deterministically on Zapier so you get better cost and accuracy. He said the intuition was savvy.
Then he named the two gaps, and both are about where a PM now stops rather than what they wrote.
Why stop at the PRD. Fire up a coding agent and prototype it. His framing is that a picture is worth a thousand words and a prototype is that times ten. The point is not that PMs should write production code.
It is that seeing is believing, and building the thing is no longer an excuse anyone accepts.
Then, where is the customer evidence. Gong recordings, Zendesk tickets, subreddits, LinkedIn, X. Sift all of it and find where people are already complaining about this, then check whether you have the shape of the product right.
Neither gap is about AI. They are both about what you did before you asked for someone's time.
A document that stops at the document now reads as the work you did not do.
SITUATION EXPLAINED: Four of the five authors on the scaling laws paper went on to found Anthropic.
• Dario, Jared Kaplan, Tom Brown, and Sam McCandlish all co-wrote the January 2020 paper, alongside Alec Radford
• Dario leads research direction and strategic vision, and spends his time writing. Daniela is chair and president, and runs the company day to day
• Tom Brown led GPT-3 engineering at OpenAI and is now Anthropic's unofficial face to government, including the Fable negotiations
• Jack Clark runs the Anthropic Institute and Mission Labs, which built Claude Code, MCP, Skills, and Cowork. He was a technical journalist before this
• Jared Kaplan is chief science officer and responsible scaling officer, and helped pioneer constitutional AI
• Sam McCandlish runs large-scale training and is the least famous of the seven. Chris Olah heads interpretability
@theojaffee: "Dario has, like, the most enviable job in the world. You get to be a multi-billionaire and the CEO of the world's most important company, arguably, and you get to spend your day just thinking and writing and blogging all the time."
Holy shit, Claude Opus 5.5 is now up to 40% cheaper than Opus 5.
Same tasks. Same quality. Way less cost.
Breakdown:
Input tokens: $4/M (down 20%)
Output tokens: $20/M (down 20%)
Cache reads: $0.20/M (down 60%)
Most of a coding session's cost comes from cache reads, so this alone can cut your bill by more than half.
AI is slowly getting cheaper.
Introducing Agent Tincan. Let your AI agents ask each other for help.
Your agents each have a superpower. Grok Bot is always on in the cloud. Muse makes phone calls and has access to Meta. Instinct runs in iMessage. Codex and Claude Code have your code. ChatGPT and Claude have your chats.
But they can't talk to each other, so you're the copy-paste. Now they can, all securely over Tailscale.
📞 Ask Grok Bot to have Muse call the restaurant
🖼 Get an image from ChatGPT, from any agent
🔎 Pull a detail out of an old Claude chat
🛠 Talk to Codex on your primary development machine
Runs on your own private Tailscale network. No open ports, nothing leaves it. Open source.
Setup is agent-first: paste one message into your always-on agent and it sets up the rest.
9 Claude Code tips most people don't know
I've been using Claude Code every day, and most people only scratch the surface.
Here are 9 features that changed how I work. None of them are "write better prompts."
Here's Rhys' practical guide to shipping an MCP your users want:
- Your MCP should be able to do everything your dashboard can
Yes including things like deleting resources. The way to make this practical inside of an agent while not having things be unsafe is to deep link them into your product from inside the MCP
- Do not ship lazy loading / codemode inside of your MCP
CodeMode is a harness detail. Most harnesses (Claude / Codex / OpenCode) support codemode now, the problem is if you have two codemode MCPs they don't compose nicely (Executor v2 will still support CodeMode, but, will start to default to a transparent tool proxy for better clients)
- Ship a search docs / skills tool
Agents love these and it helps give them more understanding of your product
MCP is getting skills over mcp which will help here in the future
- Have a deep link into product tool
Let the agent generate a URL that brings them into your product, people still want to use your dashboard and data visualization! They just don't want to click through things
- Customization
I think this matters less over time, but, you can allow people to select 'toolsets' of things to connect with to clients. Some clients don't support customizing tool selections and then it's also nice to have tool permissions set to the auth token
- Let people OAuth from whatever client they want
Please stop putting restrictions on which clients can authenticate to MCP servers, your users hate it, it doesn't improve security, all it does is add more friction
PostHog and Sentry are my two 'AI native' companies to look at today, they both have an excellent onboarding, MCP / CLI experience, if you need a place to learn from look at them
To be honest though, while all the above is helpful just shipping your API spec + CIMD OAuth to it is enough for 99% of agents to have a good experience
It's insane how much better the $200 Claude Code plan is compared to Codex right now.
Just a few weeks ago, it was the other way around. Excited to see how OpenAI fights back.
The product manager role is 3 jobs. Most people want 1.
Here's how to hold them all:
It's still the classic job that we saw when Martin Eriksson (@bfgmartin) drew it in 2011. You have to be at the intersection of what customers want, what will move the business forward, and what's just become recently possible.
But with AI the PM has moved closer to everything.
Customer
What is worth solving?
You want to get as close to the customer as possible. We used to be gated by UXR with access to our customers, with analysts with access to our data. All those barriers have dissolved, and with MCP or CLI connections, PMs are put right into the center of their most important customer data. And with AI automations, PMs can get more time to spend with actual customers.
Tools: @hidovetail @pendoio @intercom @Zendesk @hotjar @Qualtrics
Engineering
What is possible?
You still don't want to build THE thing (usually), but we're getting closer. We're building prototypes on the real code base and design system. We're skipping the old wireframe stage with Balsamiq and going straight into clickable, full-data prototypes to drive better discovery.
Tools: @boltdotnew @lovable_dev @Replit @figma @github @vercel
Business
What is worth funding?
You don't need to become the analyst, but you can't wait on one anymore. We used to file a ticket with the data team and wait a week for a dashboard. Now PMs query the warehouse directly, pull revenue by segment, and walk into planning with the business case already built. The number that decides the roadmap is one prompt away.
Tools: @stripe @HubSpot @mixpanel @googleanalytics Looker @Snowflake
The Product Manager
Which one ships?
You still make the call, but now everything is connected in one place. With agentic harnesses like Claude Code and Codex, you can set up an operating system at the center of everything. And with newer tools like Herdr and pi, you can really take the agentic part of that to a whole new level. You still make the call, but you have an AI employee helping you alongside everything.
Tools: Claude Code (@claudeai), Codex (@OpenAI), @cursor_ai, @herdrdev, @pidotdev, Instinct (@noahrshinn)
It's amazing how nothing changed.
And everything changed.
Using managed agents is perfect for running coding agents anywhere in the world.
The beauty of this:
• You can resume a session from anywhere
• You can fork a session into multiple agents
• You can run parallel agents
• You can reuse environments
Here is how you can do this with Claude Code, Codex, OpenCode, or Hermes.
Anthropic has no image or video model, yet Opus 5.5 just made me this 30 second animated film using nothing but 2,800 lines of code
(yes, this is 100% Claude Code with no other AI tools, connectors, or reference images)
i gave it one prompt: 4 seasons passing outside a train window, a cozy carriage, a cup of coffee on the table, Grand Budapest Hotel style
and it literally came back with the finished .mp4 file ready in the chat
so i asked it... how did you achieve this result when you have no image model??
here's what Claude actually does behind the scenes:
1. sets up free drawing software on your computer, the kind that turns written instructions into pixels
2. writes ~2,800 lines of code describing every object as shapes with exact coordinates: a tree is a brown trunk plus ~6 overlapping green circles, the coffee cup is a few ovals and curves
3. layers the scenery at different speeds, so telegraph poles whip past 140x faster than the mountains (which is what gives it depth)
4. renders a still of each season, looks at them, then fixes what looks off
5. animates it like a flipbook: it calculates where every object should be at each moment, then redraws the whole scene 900 times
6. builds the soundtrack the same way, as equations. a plucked string is a stack of sound waves that fade out. each rail click lands on the exact frame where the coffee ripples
7. stitches it all into the final video
it even invented its own season transitions: a passing train sweeps spring into summer, tunnel turns autumn into winter, etc
the creativity and attention to detail is getting pretty ridiculous
Opus-5.5 is the model I have liked most since Opus-4.6.
It’s the type of model that only comes out once a year or so: a clear leap above what was possible before, really great to talk to, and all around banger.
A lot of people have been upset with how Anthropic is watermarking text, or pacing the frontier, or being all doom and gloom. But what they have built over there has been working.
As someone who follows every new model release from every lab closely, I can confidently say they have had the best frontier model for most of the last 2 years. That’s an insane feat in such a competitive market.
Dario is cooking. The team is cooking. And the revenue shows it. Another year of 10x, when they themselves thought they couldn’t do it. I firmly believe they could do $1T revenue next year and 10x again. The funny thing is I think the team at Anthropic may not know it.
The only company who has briefly taken the #1 spot is OpenAI. I think they still have the power to take it longer-term. But they need to learn more from Anthropic. They need to release more and only announce when they can release to everyone. They need to reach parity with Claude Code’s harness. They need to actually focus on AI writing because Anthropic went the watermarking route so they have clear counter positioning.
Whether they can do so remains to be seen. Google, Meta, and X are also horses in the race. But they have yet to come close to a model of Opus-5.5’s particular delightfulness.
It mogs Fable-5.1 in 80% of tasks, and it’s like 20% the cost (all things considered). It’s fucking awesome.
Claude Opus 5.5 animated this in one Claude Code session.
A Series C offer the recruiter calls $370K a year: $200K base, $30K bonus, $40K sign-on, $400K in RSUs.
Say you stay 2 years. Spread the sign-on over those 2 years. Value the stock at 40% odds of an IPO, 5 years out, discounted 15% a year: $400K × 0.4 ÷ 1.15^5 ≈ $80K, half of it vesting while you're there.
That's $270K a year. Do the math before you counter.
Just successfully had Grok Bot ask Muse to make a phone call, all securely over Tailscale.
Would anyone else want this tool I built for myself to let all my different agents talk to each other? Right now have it talking to Grok Bot, Instinct, Muse, Codex, Claude Code, Hermes and OpenClaw.
Muse, Instinct, OpenClaw, Claude Code…
All successful agents have 3 key components:
🧠 Brain → model, harness (logic)
👐 Hands → tools, computer, browser
🗃️ Files → memories, skills, repos
The 'easy' way is to throw all these in 1 stateful computer (a Mac Mini)
Like, you run 𝚌𝚕𝚊𝚞𝚍𝚎 or 𝚏𝚡 in your mac, you keep it running all day with 𝚌𝚊𝚏𝚏𝚎𝚒𝚗𝚊𝚝𝚎, it has storage, and CLIs and apps installed.
But if you want to cost-efficiently run agents in the cloud, you actually start breaking down these parts.
🧠 The harness can run in Fluid compute. To make it reliable across restarts, rollouts, crashes, you make its event log durable using Workflow.
👐 The hands can be a dedicated browser fleet like Browserbase/Kernel, a computer like Sandbox, and even more efficient lightweight tools like just-bash.
🗃️ 🆕 What was missing was a way to also decouple storage. Imagine you want to run a memory consolidation cron job every night ("dreaming"). You can read/write to the files directly without 'booting up' the agent's full computer.
Today we're introducing the perfect companion to Sandbox: Drives. We shipped the computer for agents, now we're giving you the 'external disk' you can attach at will. It's early, and we'll be expanding capabilities here quickly.
Btw, breaking apart the agent into these independent parts not only optimizes costs in a big way, it also *massively* improves security and auditability. I'd argue you can't even run a secure agent otherwise!
we’re thinking of killing plan mode and using the shift+tab hotkey to adjust effort levels
I don’t think the models need plan mode anymore, but if you’re a plan mode diehard would love to get your feedback on why
For the last several years, I have said that OpenAI models are better at ideation, creation, and exploration.
If I had to brainstorm something, I would have picked whatever OpenAI model was best in class.
Yesterday, that changed.
First, Opus 5.5 is the only model to hit (note: hit, not beat) my code-meets-poetry challenge. It is the only time I have shared the test with a lab. I was in shock.
Second, last night when making slides, I prompted both Codex and Claude Code to give me design options for one slide I couldn’t crack. Codex was a mess. Claude Opus 5.5 made 6 versions as pngs using image 2.5 from OAI, labeled them perfectly, saved to computer, opened up finder, and messaged its preference (I agreed with one of its recommendations but not the other).
When I said my two preferences, it immediately created them as editable slides in PPT (like text boxes, shapes, the whole thing). I didn’t ask for that.
In my early testing of Opus 5.5, it had several tool call failures. And it seems they have fixed it.
Opus 5.5 is a tool-wielding machine and feels far more creative than previous Claude models.
Gabe on why he doesn't think Anthropic or OpenAI will own finance:
"The reason people get confused when they look at app layer businesses like mine or Harvey or Legora or Sierra is because there's a spectrum of perpendicularity to what the labs are building.
There's a whole bunch of stuff underneath the surface that the labs are never going to build, that we need to build for finance.
All of finance is a collection of different niches with different data sets, different regulatory requirements.
And we can get to $5 billion in revenue by going deep across those things and creating the systems of record that help manage them.
That for Anthropic would be like stopping on the side of the road to pick up a penny, because they're on the pathway of trying to go from $100 billion in revenue to a trillion in revenue.
Say you are a big public company buying another big public company and you need to send data back and forth.
You actually need some sort of data room, something that is compliant, safe and secure. And I don't think OpenAI or Anthropic will ever want to build a data room business.
If you actually want to be the exchange for all of high finance, you don't just need to own the intelligence, you need to own the transaction venue, the communication venue, the workflows, and all the data inputs that go into it.
Think about the fundamental difference between Claude Code when it came out versus ChatGPT.
The models were actually fairly similar, but the harness and the way that it was presented from Claude was far better.
The way that you harness these models is so, so important."
