Adapt

Your company brain + the universal AI agent that runs on it.

Ready to join your team in Slack 🚀

[Adapt @Adapt]

All teams who try to build their own company brain will discover the same thing: it's complicated.

We hear from companies that they're building a company brain themselves. Then they come back and become customers.

Why? Because few teams have the resources to solve the ongoing challenges involved. Most need to spend their eng resources on innovating on core product instead.

That's why we're building Adapt.

[David Cramer @zeeg]

this Slack agent is certainly the most difficult engineering project I have touched in a long, long time

on the surface its somewhat straight forward, but the amount of moving parts and complexity combined with the fact that much of its not determnistic makes it very difficult

[Jim Benton @jim_benton]

Join us tonight. Everyone is welcome.

An easy 3 mile run from our porch at 103 Montgomery St in the Presidio (right next to the Disney Museum), out to the Golden Gate and back.

Come around 6:15pm, we leave at 6:30pm sharp, and we'll hang out on the porch with refreshments after. All speeds welcome, no one gets left behind, bring a friend, bring a lot of friends. There is a bathroom upstairs if anyone needs a changing room. If you have a favorite post-run drink beyond water, drop it in the comments and I'll grab a bunch ahead of time.

Credit to @Adapt for taking an idea I shared in our team Slack channel and turning it into a killer flyer. Ping me if you need anything! Email in the flyer.

[Adapt @Adapt]

Adapt has become meaningfully more capable over the last few months, and we're passing that on to our users.

Every $0.01 credit now does more work - more questions answered, more scheduled tasks run, more apps built.

New users who sign up with their work email start with $100 free credits and can earn up to $200 more by connecting your tools.

And when you're ready to top up, plans now start at just $50/month.

[Adapt @Adapt]

Our favorite of @danshipper's predictions for the future:

"Every company will have one super-agent inside their Slack that every employee will use."

Built for that future now. https://t.co/L4gTE273Au

[Lenny Rachitsky @lennysan]

My biggest takeaways from @danshipper:

1. The future of work will happen inside Codex or Claude Code. Instead of putting AI into your SaaS tool, you’ll use your SaaS tools inside your favorite AI agents' in-app browser. Dan spends all his time in Codex now—writing documents, managing email, doing research, everything. He's using Google Docs, PostHog, and everything he needs within the agent's in-app browser. The agent can see what he’s doing, and has all of his context, so he and his agent collaborate quickly and super effectively.

2. Automation is a lie—every automation needs a human. Dan's company doubled in size this year despite being incredibly AI-forward. Why? Because in order to make automation work well, you need humans making sure everything keeps working. This is why benchmarks are misleading—they measure AI on problems we’ve already framed and can score, but there’s always a higher frame.

3. PMs will win the AI era. Marcus, a former PM who previously ran Axios’s writing product, joined Every after getting super AI-pilled. Now he runs their product Spiral, and ships faster than anyone on the team. He pairs technical knowledge with spiky product sense, deep user empathy, and an eye for what matters. Dan thinks any PM who gets really AI-native will be incredibly dangerous because the building is done for you—what matters is figuring out what to build and if it’s great.

4. Full-stack designers are becoming superheroes. Designers used to make beautiful interactions that engineers didn’t want to build or couldn’t execute properly. Now designers don’t need to hand things off; they can build it themselves. Designers are naturally creative people, and AI is the perfect tool for them because it lets them bring their vision to life without the traditional bottlenecks.

5. SaaS is not dead. In fact, Dan is bullish on SaaS stocks. When users bring their own AI (via Codex or Claude Code) to use SaaS products, the user—not the SaaS company—pays for tokens. This saves SaaS company’s margins. Since the agents need their own seats, Dan predicts that agents will create massive new demand for SaaS because there will be tons of agents using these products at high volume.

6. Every company will have one “super-agent” inside their Slack that every employee will use. Dan initially thought every employee would have their personal work agent, like a shadow AI org chart, but he’s completely flipped his view. He realized agents need humans who care about them. When someone gets tired of maintaining their personal agent, it becomes useless. The winning model is one forward-deployed engineer or AI-savvy person who maintains a company-wide agent (like Shopify’s River or Viktor), and then it trickles down to more specialized team agents as models improve and become less fiddly.

7. The AI job apocalypse is not happening, but you do need to evolve to stay relevant. Models make yesterday’s human competence cheap. But because everyone uses the same models, it all looks the same if you use it the default way; it becomes commoditized slop. Humans then take that frozen competence and use it to make something new and interesting for their specific situation. The key: “ride the models”—use them for everything you do, try new models when they drop, keep turning over rocks.

8. We will read way more AI-generated writing, and we will like it. Human writing is incredibly important for things that matter, but for internal docs, planning, and email, AI-generated is often better because most people are bad at writing strategy documents.

9. Build software for humans and agents to use together. The current model is building a CLI that an agent uses independently. Instead, you and your agent should be using the app together. This creates new design challenges—agents can make a billion requests in three seconds, so you need approval flows, inboxes that summarize what happened, logs, and easy rollback.

10. Forward-deployed engineers are the new most essential role. The big model companies have teams of people managing their internal agents, and those teams aren’t going away. It’s different from traditional software building, and certain engineers love it. As models get better, this role will evolve—you’ll be managing more agents doing more things.

[Adapt @Adapt]

Make this time the last time you prep for a monthly business review.

- Ask for the data you need across systems
- Build an internal dashboard app w/ the data
- Automate next month's updates and delivery

Try it out for May's metrics with $100 free credits at signup.

[Het Trivedi @het_trivedi05]

on nvidia's earnings call yesterday, jensen made the case that neoclouds like $NBIS and CoreWeave are positioned to outgrow the hyperscalers.

used adapt to pull the receipts.

[Adapt @Adapt]

We're honored to play an important role in @wander's growth story, where every department runs on Adapt.

[John Andrew Entwistle @jaentwistle]

@jim_benton @wander wouldn't be possible without such a great company brain from the @adapt team

[John Andrew Entwistle @jaentwistle]

@jim_benton @wander wouldn't be possible without such a great company brain from the @adapt team

[Adapt @Adapt]

Vendor agents optimize for specific job functions.
A universal agent optimizes for the entire company.

[David Cramer @zeeg]

vendor-specific chatbots are broken by design

that means the Sentry agent, the Linear agent, and any others you might have in Slack

they are fine for some point situations, they're nice to get started with, but agents with generalized access outperform them in every single scenario

some weeks ago we built an internal Slackbot, gave it access to a bunch of systems (Sentry, GitHub, Linear, Notion, etc), and its capabilities overnight far exceed these other bots

"Oh cool Linear can now search your code bases" - our bot did that on day one, and then could push that information wherever it needed to go.

Its useful to the point where I now discourage use of things like the Linear bot because it _creates worse outcomes_.

this also goes beyond the simple generalization of access: we can customize it. we throw in skills-as-runbooks, templates, etc and the outcomes once again incrementally improve

if your org hasnt already built a general purpose bot internally you should. if you need inspiration ours is open source on GitHub (albeit fairly unstable still)

https://t.co/4SzdZPIMBP

[Adapt @Adapt]

"Every company will have a company brain. Not a bunch of AI tools. A single AI brain."

[The SAAS Operators @saasoperators]

E54: Become AI Native with @jim_benton from @Adapt

@jackdoesecom @JeremiahPrummer @rishabhmjain
Watch the full episode below 👇

[Adapt @Adapt]

"I was one of those people saying AI agents don't work. Up until Adapt."

4 months later...

RevSend has 21 tools connected, replaced 3 platforms, and automates ~100% of their RevOps with Adapt.

[Adapt @Adapt]

We're not here to replace your human co-workers with AI.

We won't masquerade in your Slack as an "AI co-worker" with a human face and name.

Adapt is the AI computer for your entire company.

It makes everyone feel like they've cloned themselves, hired an intern, and leveled up their skills all at once.

Not a new co-worker. A force multiplier for your team.

[Adapt @Adapt]

@LegitSeanSmith still got it

[Sean Smith @LegitSeanSmith]

o3 not wrong

[Adapt @Adapt]

Scaling products is fun :)

[Adapt @Adapt]

already prepping for the next one 🚀

[Leo Motion @MotionByLeo]

AI Launch videos don't have to be boring✨

[Adapt @Adapt]

Get started with up to $300 in free credits when you sign up with your work email

[Adapt @Adapt]

Introducing Adapt, your company’s AI computer.
Now available to everyone.

→ Ask questions across every system
→ Build internal apps with live data
→ Automate mundane to complex tasks
→ Multi-player by design