# Slack Evolves Into Agentic Work Operating System

**Podcast:** Dev Interrupted
**Published:** 2026-02-10

## Transcript

Today I am thrilled to welcome our guest, Curtis Kemple, the senior director of DevRel at Slack.
Curtis, welcome to Dev Interrupted.
Thank you so much for having me.
It is a pleasure to be here.
We're really excited to have you here.
Uh, you and I we met at Dream Force last year.
And when we met, I knew I had to have you on the show to pick your brain because we chatted for a while about some pretty cool concepts.
One of them that really stuck with me around the future of work.
And I really want to dive into that with you today.
Because when when we chatted at Dream Force, you you shared this idea that really stuck with me about how Slack is evolving from a place where work is discussed to where the work is actually done, as if like those words are starting to move into action.
And I think that's really interesting to explore.
It makes me think of like supporting practices in the code world, like DevOps.
You know, maybe we're entering a world where you get something like chat ops.
And so this is kind of part of the future of work that Slack is taking us and everyone who uses Slack, which is a lot of folks, uh, into the future.
And I want to dive into that vision with you and talk about how those core problems have evolved.
So, you know, what do you think about that premise?
Do you want to dive into that today?
I absolutely do.
I absolutely do.
And you know, before we hop directly into that feature, I just want to take one second to talk about the past and how we got here because you know, Salesforce and uh has really created the the push for agent force and agent interaction into Slack.
That was our real first approach, right?
Like we dropped it in there, we learned a lot, and through that process, we started to understand and develop like what does it take to support like that type of experience, getting agents directly in, first through there, but now through anywhere, right?
Like third party directly into the Slack platform, uh, or first party customers building their own agents and integrating.
And so we just hit like kind of that that you know perfect storm or shelling point, if you will, right?
Yeah, and essentially uh, you know, it made us really just stop for a second and put on a beginner's mindset and say, like, what is a platform that supports like any kind of agentic workflow, but does it in a way that is like structured, consistent, grounded, you know, that is a very difficult tension to think through.
And so I just want to preface that.
And we've been working with a lot of customers to figure this story out, right?
Like Anthropic and Vercell have been at the forefront of this.
We've got all kinds of companies really just uh helping us replic another one that stands to mind, just tons of these uh across different industries, all noticing and saying, like, hey, we can deploy AI here because we've got collaborative environments, we've got context, which is what we're gonna talk about here.
Um, and so yeah, so sorry, just the the main intro I just wanted to bring us because that's how we started thinking about the future, right?
Like, look at where all these things are heading.
There are some similarities, some things that are overlapping.
And when we think about truly having humans and agents working together and collaborating, like what does that look like in reality, right?
Not even just at the code level, but literally handing off at the interaction point.
I love I love how you framed it.
I'm really excited to dive into this because you're right.
I mean, Slack becomes the place where all of that context lives, and that context is messy.
It's the real communications between real people getting their work done.
It's not this neat, orderly structured data that can flow in and out of systems.
And so it creates this perfect intersection between the systems we're building to be more productive and how and where the work is getting discussed.
And it's exciting to think out how all these other companies too see the opportunities with their conversations and want to tap into that to make their own work better.
And really it comes down to this context, right?
It's because context has evolved now into being a first class citizen of the AI world.
Before we were all about prompts and prompt engineering, and then it evolved into context and context engineering.
And, you know, I can't think of a better source of context for a lot of the things that happen at work than maybe some Slack channels.
So, you know, can you expand a little bit on this context gap and and how it really is needed to help models perform and meet companies where they want to use it?
Yeah, absolutely.
So I'm gonna uh walk you through super quick something that I refer to as leaky prompts, right?
Uh, when you only own half of the experience, uh, meaning that I can't control what a user prompts, right?
And they might start off with a very perfect prompt with what they're trying to accomplish.
But literally proven through science, like any conversation, whether that's with something digital, another person, a group of people, will actually slip into chaos unless it is actually managed, like triaged, right?
And we see this actually, you do this right now.
When you are interviewing people and you got engaging conversation and we're chatting, that takes effort from you and energy.
You are literally putting in a ton of work to ensure that we have this very good, fruitful conversation that stays on track and has important insights and talking points.
So, you know, that work is also required when you're engaging with an LLM, surprisingly enough, right?
Uh, but the issue is is we can't control how somebody else is doing.
And so it puts us in a place where the only way that we can have the best chance of ensuring that that intent is in alignment, we're staying on task to their goal, is that the context, the representation of what we give to the LLM on the user's behalf, is as best a representation of what we can think they're trying to do.
You're almost adding like a second-order need of understanding, all right?
It's like you have to understand how the user is going to interact with the LLM and ensure that you can just provide the right context.
I like to think of it more as information architecture at this point.
And if you can do it well enough, it makes it a lot harder to have those conversations get off track and that misalignment on a tent.
Uh it makes a difference.
And like you said, Slack is a wonderful home for that context.
We've got threads and channels and messages.
And that's where the I see the secret sauce at.
Totally.
And so when you're talking about like basically this triage, this harness to keep the conversational rails.
We we're at this point where we all acknowledge that AI is very powerful, but it's a force multiplier.
It multiplies the good and the bad.
And it's going to make bad situations worse in terms of not having the right kind of prompt, you know, leaky prompts as you described it.
Also not doing that your own kind of like data hygiene on what you provide and what you're asking for.
Also having clarity on what you're even trying to achieve when you ask it.
All of these things are powerful things that the user brings to influence the outcomes and the experience of using the tool.
But context, as you say, becomes this experience that the producer of the experience, the provider, the one that's trying to give the end-to-end service, can actually use to keep on rails.
And I'm kind of curious to know from you how does Slack turn the messy reality of all of those conversations into that context harness that keeps users from hurting themselves with their own agentic conversations?
So we're approaching it in a couple different ways.
And I think number one first is like understanding the needs of app developers, right?
And people who want to integrate into the Slack platform because uh that's actually going to largely inform what type of context we should be exposing to them and at what degree, right?
And uh helping them understand how best to use it through SDKs or APIs.
And so tactically, how that actually manifests is something like okay, very common uh need is to uh do some sort of deep research or deep synthesis of context, right?
And that will be broader than a specific channel or thread or something like that.
So how do we accommodate that?
We build a like a real-time search API that is purpose-built to interact with LLMs as opposed to end users, right?
And so then you can build these, you know, better search integrations, your perplexities or other things.
I'm working on an app right now called Trendy that we might talk about a little bit um that does deep research, right?
And so, you know, these things uh you know require one specific type of context.
Uh, but then we've got where maybe you're a design team and you're working with your uh uh uh marketing team and you've got a design for a new landing page.
So you pull up the Versell B Zero agent and you're working back and forth, and it's able to take the context from that thread level and actually go off and generate something for you based off of that, and that's great.
But then also what about the scenario where uh you've got generally most Slack workspaces have some sort of knowledge or answer, you know, or QA channels, right?
Where you go to look things up.
So you probably want to be able to have an agentic experience at that channel level that's able to tie into related, you know, canvases or lists and the messages within there and help answer questions faster.
I can think of about 15 different, you know, verticals or or use cases where that becomes immediately applicable.
And so, you know, last time when we talked, I'll pause right after this, but it's you know, I it's about having the micro uh microscopic and macroscopic and just like finding those right integration points at the platform to enable what it is AI app developers and these AI platforms are wanting to you know bring to their users, and so it's a lot, but yes, it's all context.
Everything I said is about like data management or context.
And in this world where you're managing and creating this context that produces these more deterministic outcomes, you're you're ultimately rendering a conversation into a tool somewhere and allowing it to apply actions.
Like the Vercel, the V0 one is a really powerful example.
People could be having a conversation or dropping a Figma link or cross-linking things in Jira, right?
Because these are also places where context lives.
And so when you talk about tools being able to grab and use and interact with that data just like we as humans can, you start talking about a new kind of uh it's like an integration layer where human intent and machine ability can meet.
And that's an exciting opportunity for for Slack.
I think Slack is uniquely positioned to tackle that problem.
It sounds like from the way that you frame it, y'all already are, you know, really like headfirst tackling this problem.
I I'm wondering how y'all think about it too, because Slack is notoriously a multiplayer experience.
No one uses Slack by themselves.
But AI is relatively single player in terms of how we think about it and use it, right?
We maintain our own context windows, our own chats, we have our own silos, we go to chat GPT, whatnot.
But you know, I I want to know from your perspective, how does that change and evolve when you start getting multiple people interacting with these bots in a shared communication environment?
Yeah, yeah, you know, I really wanted to experience that.
And so we've been building it, right?
You know, um, and I even built a full-on example of just a little chat app for me and my family that integrates AI just to really experience multi turn, uh, collaborative with AI and the flow of that.
And, you know, I think the only reason we don't see more of it is because I think it's pretty difficult to really build up that user interface, you know.
But we've been doing that for a long time.
Uh, and you know, I think the Salesforce uh to agent force to Slack integration shows up a lot there.
And I bring this up because we see companies who are like saving literally like 4.8 million in annual benefits by offloading stuff that uh yeah, agents that they were able to just click and create to help with deal pipelines to so that it's doing the intermediate toil triaging, not making decisions, bucketing, categorizing, flowing, deciding where it goes, right?
And that is completely different, you know.
And like now we're seeing more and more verticals bringing that, like you can code apps fully through uh open AI codecs or GitHub co-pilot, or do both.
You're an engineering manager, GitHub co-pilot, go dig through all of my top PRs, prioritize them for me.
Oh, code codecs now.
Please go through those, open the top five in a sandbox environment for me so that I can work through them or check them out, right?
And then you close them all up.
And you know, the thing for me too is that I think about Slack like as a uh uh saving youth on the productivity tax, yeah.
And so when you're doing AI well in Slack, it's doing the same thing any other app does.
It it's me when I vibe whatever and I spin that off, and now I'm off doing something only I can do, only me that I need to spend my time on.
And so I've just like got this like a web of agents around me now, you know, that I'm using, and they're doing everything, like I said, from deep research projects, pulling in my calendar and organizing my day, looking at issues and things that I might need to triage and address.
All the stuff that was just like manual labor, nobody else was gonna do, right?
Like it falls to me.
And then my other favorite place is I love to do it to apply AI to where I otherwise wouldn't have time.
I have 20, 30 minutes for AI.
Let me see if I can vibe code up a qu a good enough solution for this.
I end up with nothing.
It was 30 minutes of my time.
I end up with a success.
I now have something that I wouldn't have had anyway because I only had 30 minutes, couldn't have done it alone in 30.
Maybe I'll get a good result if I can sprinkle a little AI in.
So I just, you know, when I talk about integrating AI and the flow of work, I think I'm like at a point where people are like, you know, we're talking about like handing off just a Figma here and there.
I'm talking about like building the Figma and then handing that off to V0, who's generating the page, and Slack bots writing up the canvas for me to go share with the marketing team so we can get ready for the GA and submitting the AI created workflow that some lines all of the social media stuff for us, you know.
You know, it's like wow, that's like a powerful handoff experience.
You you're talking about this world where you're effectively chaining these agentic tools together using Slack as the medium.
Slack becomes the integration layer because it's the means by which you're communicating with the bots.
What do you do when you communicate with any AI tool?
You're providing words that are context.
Slack then just be kind of becomes this place where you're conducting an orchestra basically between all of these agents as the way as the way that you described it, you're orchestrating because you're basically a you're basically a pipeline, you yourself, and you are the uh the human in the loop deciding what's the next stage of the pipeline, but you're effectively handing things between the tools.
And I think that's a powerful way of working.
I also think that opens up a whole new level of uh, you know, even the examples of like using GitHub Copilot to get your ish top issues and feeding it into codex, like that's an immediate powerful atomic example.
And all of this comes down to how easy it is to build and tinker and explore.
You talked about companies deploying their own tools, the reduce a lot of toil and sales pipelines, you know, saving them literally millions of dollars, and those are just easy one-click wins.
So, yeah, I want to dig into think this is a good point to really kind of dig into the how of how Slack is empowering these teams to build these really cool agentic experiences to actually unlock those savings.
And you know, a big vision like that can only work if the platform is easy and delightful to build on.
So, how does Slack achieve that?
How do you educate your devs for all of this complexity?
You know, that was the first thing is like uh we had to reassess our entire platform.
So a couple months ago, we were looking at the direction of where things are going, uh, and where we had spent investment over the last two years.
And a lot of that was into our uh the automation side of the house, which was good.
We needed it.
Workflow builder is amazing.
It gets you so far.
Also, just released a bunch more uh like conditional nested conditional branching to customers.
So go check that out.
If you're not using workflow builder, you should be, but it gets you so far.
But when we think of building these AI um experiences, they're gonna be tying into Slack in all kinds of surfaces, right?
Like this uh app I'm vibe coding now, trendy.
It you can DM it, you can pull it up through the agent sunroof, you can at message it in channel, and no matter what, it's gonna help you build that deep research report, right?
And so, like, you know, we have to think about, and that's still being narrow.
We've got slash commands, message actions, you know, all kinds of events.
There's no reason AI can't sit behind any of those events coming through Slack, you know, and and as a matter of fact, my next uh project app I'm building is called Tidy, and it's gonna go around and help make sure that your workspace is just all tidied up for you and and exactly what you want, giving you reports, what's happening now, these channels might need to be archived.
Uh, you know, they will write up canvases and archive it and clean it up, recommend workflows, and that's just scratching the surface.
Yeah, because all of that context also will need its own kind of agentic janitor to keep it used.
That's it.
That is it.
That is it.
And so, you know, we are also hard at work on making that click to create agent experience, just getting them right in there.
Super simple.
The vibe coding Slack app experience, you'll be able to vibe code uh Slack apps, like with uh Heroku and stuff like that, and just deploy them right into your workspace.
Very seamless, but it all starts with the developer experience, and we've invested a ton over that.
And so we did that by consolidating back onto bolt apps, which is our main framework.
Uh, we consolidate it onto the CLI.
So you CLI, you know, Slack create, pass it a template if you want, or start blank.
It's up to you.
We've got all the options.
You run Slack run, and now you can run it in a workspace and tinker with it and run Slack deploy and deploy it to your platform of choice.
And that's where we are right now in that that second half, um, which I've put under time to value, which is deploying.
Like I've gotten an agent and it needs to be in Slack, and I need to have it production ready.
I want that time like down, like a a week, like two weeks.
Like you should be able to databases, observability fully integrated into surfaces, AI inference happening uh in a matter of a week and be submitting to the Slack marketplace to get your app there.
Uh last note, I'll say I keep telling folks, stop building apps and start building conversations.
Like we already have multi-turn, multi-collaborative UI and AI user experience, purpose built.
Why build your whole own website on an app on top of yours?
Find product market fit right in Slack.
You know, that's what we're building.
The infrastructure to support that.
It becomes the user experience as well.
And I I want to know too, in this world we're describing or we're entering into, you know, doing this this agentic coding, it's relatively approachable.
We talk about the developer experience and how the developers can spin up their sandbox environment on Slack.dev and get started, and they can also use bolts, your SDK, to quickly get an app on online and connect it, right?
So, you know, how do how does Slack also think about enabling people who are not engineers, but who are also using Slack and would benefit from these workflows to be able to maybe build and deploy things?
Is that what the the builder uh workflow builder aims to solve?
Or do you see a world for them where maybe they're using these tools as well?
I think we're gonna see the world.
I think I think any tool that is built to add guardrails, most people uh when they you know become familiar with them enough, hit the rails.
It's almost inevitable.
And it doesn't matter how far you move that guardrail, eventually people who are invested enough and have found enough value will hit those rails because they understand the more they integrate the more value they're receiving right and so they'll find new ways that you never thought of to try to do that.
So I think my point there is that like yes you have to purposefully build uh what I like to call like learning paths that are essentially are persona based and you have to understand that right level of abstraction and so the kind of the way I like to think of it is first I teach them about the platform in a bit of a vacuum not too much of a vacuum so that there's no external context but really first let's familiarize ourselves with the platform its AI offerings why it might matter to you what features are available and how you get started.
That's like clean you know what I mean I can work with that I can get through that pretty quickly and then we want to pull out of that vacuum and now we want ecosystem integration because when I'm building something for production whether I'm a customer or partner, whoever, I'm never building my app like completely in isolation, right?
We have data management, permissions, security, compliance, you know the the the list goes on and on.
And so this is actually where we are now.
We've consolidated our developer experience to make this easier.
We've updated all the initial enablement material for Slack in a vacuum, and where we're pushing with partnerships with Vercell and Replit and Anthropic and OpenAI and uh all these other amazing, you know, AI companies, uh, more and more on the list too.
We're gonna be everywhere.
I'm very excited.
But long story short, is you know, we're really pushing to uh just like enable all of these different types of experiences to be built directly into Slack and through multiple ways.
Like we even have MCP.
If you're working in Anthropic, right?
Or you're working in in Chat GPT, stay there, right?
But now your Slack context again is getting to you where you are.
And when you jump back over to Slack, you've got the GTP app installed, you're literally picking up, almost having the exact same conversation, right?
So yeah.
So it really fulfills that that that vision of the agentic operating system, right?
It becomes the place where everyone goes to do their work.
I I I want to peel back the curtain a little bit.
I I selfishly want to get a glimpse at what that is like inside of the Slack world.
How much is Slack, you know, dog fooding these principles around you know, making it and just kind of uh applying AI for all of these experimental scenarios?
You just you you've described your you're almost a council of tools that you've been building that you've been advising.
I imagine they live, you know, in in some magical Curtis sandbox somewhere.
So what does that look like inside Slack?
Like how has uh your engineering team really evolved to also get in the trenches and build these things?
Yeah, so first of all, like we bring it in all the time.
So we've got another app called Tiny that's already installed to our workspace that uh is used by uh first it will be used by everyone within the Slack business unit, and then we open it up to the broader Salesforce company, right?
And then I'm working on trendy now, and we'll do the same thing.
We'll open that up and let people test it out and build with it, and then we'll open it up to the entire company.
And I'm gonna do the same thing with tidy when I build that.
And that one's gonna be deeply embedded into the AI ecosystem, like Langchain, like creating embeddings and storing that uh in uh interstitial data for steps for longer jobs when it's doing all these really interesting things, being able to stop and rewind and uh redo stuff.
And we've got like the thinking steps and all the support, like actual native user experience to support this coming as well.
And wildly we're looking at even building like an agent SDK and just saying, like, let's make it even faster than using bolt.
Like, what if what can we streamline more?
We're looking at adding new APIs to make it easier for partners to have the proper permissions to build and deploy these agents and apps on users' behalf of uh behalf, but always, of course, as secure as possible.
We take that very seriously.
I want to know from your perspective because you have your role in your role at Slack, you are very empowered and you're very technical, and you're able to envision and build and deliver these things, which is really exciting because you understand what you're trying to achieve.
And as a as a devrel professional, and like I myself really resonate with that, being one myself, is that you know, our whole role revolve around building the context for engineers to do their best work and bringing it all together.
You know, what would you say to an engineering leader about how your role has evolved and you have picked up these tools and you're seeing all the success in delivering things and maybe they they haven't coded in a while.
They're an engineering manager, they're kind of like dipping their toes back into this world, or they're trying to figure it out.
What would you say to them to really get them on the right track and to be building and showing internals internally in the same kind of way that you are?
I love that.
And I'm gonna give you all my tips and tricks right now.
You know, number one is I'm just gonna start with this again.
I've throw AI at what I call toil and time-dependent tasks that I cannot accomplish otherwise first.
I do find places for it in my workflow, but I think the hardest part is getting started.
And I think it's when we try to invest too much.
Like if I went into a okay, here's a you know, like a seven-step program to have you reviewing your PRs today, right?
It's gonna overwhelm people and it might not match exactly your workflow.
And so I actually say find the most chaotic, annoying part of your day.
Sit to go through a week, maybe two, and really think about what part of your day is bothering you, and invest 30 minutes into researching if there's a way that you can use AI within your system, right?
The tools, what tools are available?
Do any of those uh tools like features align with my problem space?
Yes, let me actually invest 15 minutes in trying it out.
And I think that you'll be surprised when you start saving five minutes here, 15 minutes there, 30 minutes here.
Then you'll start investing a little bit more.
I've got a couple of fun little scripts and prompts that I reuse.
Like one of my favorites is it's a strict kind of outline that I give to AI on planning mode when I want to like familiarize myself with a new project.
What dependencies are in use?
What patterns are you recognizing?
Where are you seeing like overlap?
I'm focused on this area.
What part of the project should I dive into first?
You know, a lot of these type of things that can just source information for you quick and you can verify, I find to be so useful.
It's why I'm building trendy, doing one-shot deep research projects on a topic, and I can just put it to the side and come back to it later, saves me literal hours, hours a day.
Deep research is probably one of my most used AI features.
Uh, in Debrell, I'm gonna roll where I need to understand what's happening in them.
Right, right?
You know, and so that's constantly me out there doing it myself or AI, brave search API, uh, a really good system prompt, and now I can just generate reports on the fly.
I can just start generating all of them, you know.
Uh it's no longer me manually opening 40 tabs, synthesizing, writing up the full canvas.
I I guess such a head start.
Um, last thing, yeah.
Zero to 60 is I love AI for things that will take me zero to 60 in a structured way.
Those are really useful like set of tips.
I especially like big plus one to like finding the most annoying or like time-consuming toilsome part of your of your day or your week, like go to your Asana board and find that recurring task that always pops back up as soon as you do it and you dread it when it comes back around the next time and create a way to solve that.
If you don't think it's something that can be solved, I challenge you to really change that assumption because we talked about today how even conversations in Slack can become the workflow through which you solve those things, even just saving a few minutes of your time is gonna be a huge unlock.
And lastly, what I'll end on is, you know, if you're our a manager as well, your engineering manager, you have a team of people who probably experience these toils as well, and you on the aggregate, therefore, experience those toils.
So, really also look to the people that you work with and that report to you, and they're busy, right?
What could you maybe find a way to automate for them to take it off their plate?
Start with simple problems and then work, you know, to more complex ones.
I think that that's like a really great way you've lay uh laid that out.
It's the best way of getting started because once you have that win, um, that's the easiest thing to showcase internally to take and talk about with everybody.
You've saved yourself and other people a whole bunch of time.
Uh and that's immediately going to be like fodder, you know, fuel in the tank for your next uh idea that you want to go innovate.
So one at a time, people.
But really great, really great advice.
And I'll leave you with this.
I literally the last two weeks have been out like sick, like so sick.
I got a stomach bug, and like I deal with like immunity stuff.
So, like, yeah, I was like out.
When I came back, I had a rush of things.
I knew also knew I wanted to be ready for this, and like, you know, so many things happening.
I went into Slack bot uh and I was like, please, here's a couple canvases, look at these channels, look at my calendar, and I need you to help me plan this week, like to a T, please help me best use my time to squeeze in all these things.
And it just did.
And I've just been boop, ba-boop, boop, ba-boop, ba-boop, ba-boop.
And that's what I mean.
Like 15 minutes between this meeting, what we did now, and another 45-minute meeting I had between, I literally went and accomplished three little like micro tasks that were already laid out for me.
See, you're already living the successes of it.
And that's what I love so much.
I I I'm really grateful that that we got to to grab some time on your calendar, especially everything is so chaotic around it right now, and you're playing catch-up.
So I definitely also want to say, you know, uh, as we come to the end of our of our chat, we've covered a lot of amazing things about how Slack is becoming the agentic work operating system.
And we've showed a little bit about how it's fun to tinker and experiment in.
But I really wanted to say, you know, from our conversation, you know, Curtis, thank you so much for coming on Dev Interrupted because it's been really great to pick your brain uh in this environment that I know uh myself and many of our listeners use every day to get their work done.
You've really sold me on these tools.
Um, in fact, I I I would love to kind of jump into maybe even try to look at some of the things you've been building.
Uh, I know we don't typically do this on Dev Interrupted, but I I'm just so tickled by all of these uh product uh you know uh prototypes that you are building on that I would love to go and maybe vibe code some of those together with you.
So, you know, what do you think about doing that together?
Um so excited.
Let's do it.
Amazing.
Well, like I said, I'm full of ideas.
I've tinkered a little bit with Slack, um, but I definitely want to learn from you as we go.
And for those of you listening, you know, this is definitely uh a different pivot from how we normally do it in Dev Interrupted.
But if you want to see what Curtis and I cook up, tomorrow, we're gonna be dropping the vibe coding demo uh within Slack on our DevInterrupted YouTube channel and on LinkedIn as well.
So if you're not following us in either of those places, you're gonna miss it.
Make sure you go and follow us on LinkedIn uh or on YouTube.
You can also reach out to me there as well.
Uh so you're gonna miss out on the fun, otherwise, but it's gonna be a blast, and I'm really excited to pull open Slack uh and see what this SDK can do.
So, you know, Curtis, thank you so much for sitting down with me today.
Let's jump into some code.
Let's go.
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Here's the problem: your review process hasn't sped up.
The queue grows, reviewers get burnt out, cycle time stalls.
Linear B changes that.
Our AI reviews every PR the moment it's created, catching bugs, security gaps, and performance issues before humans get involved.
It even writes the PR description automatically.
Your reviewers spend less time on first pass problems and more time on architecture and business logic.
Break the bottleneck, see how Linear B accelerates your workflow.