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Today, we're officially introducing the new Vybe. We started as "Lovable for internal apps." We spent the last year building the infrastructure: permissions, integrations, databases, workflows. Everything companies need to actually trust software inside their business. Then, OpenClaw came out and started showing what was possible with agents for...

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Quang HOANG

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33,385 views • 27 days ago •via X (Twitter)

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Vybe (Vybe) is building Lovable for internal apps. Vybe comes with pre-built building blocks: integrations, SSO, and AI tools, so anyone in a company can build and launch internal apps. Congrats on the launch, Quang HOANG and @fabien_devos!
3:08

Vybe (Vybe) is building Lovable for internal apps. Vybe comes with pre-built building blocks: integrations, SSO, and AI tools, so anyone in a company can build and launch internal apps. Congrats on the launch, Quang HOANG and @fabien_devos!

Y Combinator

31,049 views • 1 year ago

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.
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Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

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Today, I'm incredibly excited to announce Default's Series A led by 8VC and our new product. We spent the last three years building the tools and orchestration layer companies like Owner and Airbyte have used to build infrastructure across their go-to-market functions. Today, we're launching the first real-time data layer for go-to-market, a powerful new revenue agent, and a suite of tools for revenue teams and their agents. It's Day 1.
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Today, I'm incredibly excited to announce Default's Series A led by 8VC and our new product. We spent the last three years building the tools and orchestration layer companies like Owner and Airbyte have used to build infrastructure across their go-to-market functions. Today, we're launching the first real-time data layer for go-to-market, a powerful new revenue agent, and a suite of tools for revenue teams and their agents. It's Day 1.

nico

136,755 views • 1 month ago

Your agents suck when using the web because 85% of it doesn't have an API. Browserbase gives them everything they need to do work online. Leading AI companies like Ramp, Lovable, and Clay trust us to power agents that do real work on behalf of real people. With a single API key, your agent gets everything it needs to navigate the wild web: browsers, search, fetch, identity, a sandbox runtime, and model gateway. Stop waiting on integrations, build agents that can browse and interact with the web just like humans.
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Your agents suck when using the web because 85% of it doesn't have an API. Browserbase gives them everything they need to do work online. Leading AI companies like Ramp, Lovable, and Clay trust us to power agents that do real work on behalf of real people. With a single API key, your agent gets everything it needs to navigate the wild web: browsers, search, fetch, identity, a sandbox runtime, and model gateway. Stop waiting on integrations, build agents that can browse and interact with the web just like humans.

Paul Klein IV

1,726,166 views • 2 months ago

At Notion, we believe every business deserves powerful & beautiful tools. AI is the most important technology of this era. It shouldn't only belong to companies that have AI teams or can afford forward deployed engineers. Today we're launching Custom Agents: — The first multiplayer agents built for business. — No coding. Minutes to set up. Hosted in the cloud. — Run autonomously 24/7 with all your business apps. — Switch between the best LLMs (usually the same day they're released). — One person builds it, the whole company benefits. Rolling out for Business and Enterprise customers today. The AI era should leave no one behind 👌
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At Notion, we believe every business deserves powerful & beautiful tools. AI is the most important technology of this era. It shouldn't only belong to companies that have AI teams or can afford forward deployed engineers. Today we're launching Custom Agents: — The first multiplayer agents built for business. — No coding. Minutes to set up. Hosted in the cloud. — Run autonomously 24/7 with all your business apps. — Switch between the best LLMs (usually the same day they're released). — One person builds it, the whole company benefits. Rolling out for Business and Enterprise customers today. The AI era should leave no one behind 👌

Ivan Zhao

147,952 views • 4 months ago

We're only year 3 of a decade (if not multi-decades) long transformation of work. 3 years ago we bet on building an horizontal platform for work with agents, a chance to invent a new operating system for companies, from scratch, with AI as a fundamental premise. Many people considered us crazy for going after that, praising verticalized AI products as the winning strategy. But here's the thing: the time horizon of tasks successfully handled by agents has been predictively increasing form minutes to hours and will in all likelihood reach the equivalent of days and weeks of human work equivalent in the coming quarters. This is were verticalized and/or single-player AI falls short. Single-player tools, one person, one agent, confined to your machine is the wrong architecture for what's coming. We're shifting from using AI to produce things, to managing fleets of agents that do the producing. 3 years ago I wrote[1]: "ChatGPT is the Pong of LLMs. [...] Imagine, one day we'll get the DOOM, Civ, Red Alert, and Counter Strike of LLMs. Let alone multiplayer modes." Weeks long tasks in companies are inherently collaborative and mechanically spanning multiple teams. The new bottleneck in harnessing agents within organizations is coordination: multiple humans and multiple agents need to work together, with shared context, shared tools, shared goals. Agents that can hand work off to other agents or surface decisions to the right person at the right time. Humans who can review, steer, and step in without losing the thread. Teams that can run parallel workstreams and actually stay aligned. This is Multiplayer AI, and that's what we've been building at Dust. Across Datadog, Clay, Persona, 1Password, Doctolib and 3,000+ organizations globally, we've watched teams figure out what this looks like in practice. 300,000+ agents deployed. 70% weekly active. 240%+ NRR. Today we're announcing a $40M Series B with Abstract, Sequoia, Snowflake, and Datadog to accelerate our vision. Designing the right interfaces for multiplayer AI is the next frontier. Join us to redefine work by defining multiplayer AI.
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We're only year 3 of a decade (if not multi-decades) long transformation of work. 3 years ago we bet on building an horizontal platform for work with agents, a chance to invent a new operating system for companies, from scratch, with AI as a fundamental premise. Many people considered us crazy for going after that, praising verticalized AI products as the winning strategy. But here's the thing: the time horizon of tasks successfully handled by agents has been predictively increasing form minutes to hours and will in all likelihood reach the equivalent of days and weeks of human work equivalent in the coming quarters. This is were verticalized and/or single-player AI falls short. Single-player tools, one person, one agent, confined to your machine is the wrong architecture for what's coming. We're shifting from using AI to produce things, to managing fleets of agents that do the producing. 3 years ago I wrote[1]: "ChatGPT is the Pong of LLMs. [...] Imagine, one day we'll get the DOOM, Civ, Red Alert, and Counter Strike of LLMs. Let alone multiplayer modes." Weeks long tasks in companies are inherently collaborative and mechanically spanning multiple teams. The new bottleneck in harnessing agents within organizations is coordination: multiple humans and multiple agents need to work together, with shared context, shared tools, shared goals. Agents that can hand work off to other agents or surface decisions to the right person at the right time. Humans who can review, steer, and step in without losing the thread. Teams that can run parallel workstreams and actually stay aligned. This is Multiplayer AI, and that's what we've been building at Dust. Across Datadog, Clay, Persona, 1Password, Doctolib and 3,000+ organizations globally, we've watched teams figure out what this looks like in practice. 300,000+ agents deployed. 70% weekly active. 240%+ NRR. Today we're announcing a $40M Series B with Abstract, Sequoia, Snowflake, and Datadog to accelerate our vision. Designing the right interfaces for multiplayer AI is the next frontier. Join us to redefine work by defining multiplayer AI.

Stanislas Polu

801,584 views • 1 month ago

Today, we’re introducing WorkClaw: the AI team for your team. Most AI agents work in silos. One person, one assistant. But that’s not how teams collaborate in a real company, so we built something new. Meet your WorkClaws, collaborative, proactive, customizable AI coworkers that work in Slack or Teams just like every other colleague. Hire a new Claw in a few clicks and give them a job title, manager, computer, and apps. Easily access their ClawOS computer in the cloud, and pick from more than 3,000 integrations to install. Then, train them to get work done your way by adding skills and routines. It’s OpenClaw for actual work, with the additional layers of security and admin controls companies expect. 🚀 We’ve just opened up Early Access to a limited number of teams who get started on our website. 🎁 Want $500 in free credits? Just comment with what job title you’d give your first claw, and we’ll hook you up!
1:05

Today, we’re introducing WorkClaw: the AI team for your team. Most AI agents work in silos. One person, one assistant. But that’s not how teams collaborate in a real company, so we built something new. Meet your WorkClaws, collaborative, proactive, customizable AI coworkers that work in Slack or Teams just like every other colleague. Hire a new Claw in a few clicks and give them a job title, manager, computer, and apps. Easily access their ClawOS computer in the cloud, and pick from more than 3,000 integrations to install. Then, train them to get work done your way by adding skills and routines. It’s OpenClaw for actual work, with the additional layers of security and admin controls companies expect. 🚀 We’ve just opened up Early Access to a limited number of teams who get started on our website. 🎁 Want $500 in free credits? Just comment with what job title you’d give your first claw, and we’ll hook you up!

Will Ruben

540,053 views • 20 days ago

One click away, and a new world starts to unfold.💫 What looks like a small extension is actually the starting point for a personal AI agent that can search, think, and act with you. That is what we are building at OptimAI: live context, autonomous execution, and agents that feel native to the way people actually work. Not a demo. Not a gimmick. A new interface for the agent-native internet. Build your own personal AI agent:
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One click away, and a new world starts to unfold.💫 What looks like a small extension is actually the starting point for a personal AI agent that can search, think, and act with you. That is what we are building at OptimAI: live context, autonomous execution, and agents that feel native to the way people actually work. Not a demo. Not a gimmick. A new interface for the agent-native internet. Build your own personal AI agent:

OptimAI Network

18,742 views • 1 month ago

We cancelled our entire SaaS stack and started running our business with AI agents. Now, we’re building Toyo to help other founders do the same. We're pleased to announce $4.3M in funding from Frontline Ventures, Inovia Capital, Philipp Moehring - tiny.vc, and angels from Amazon, Microsoft, and Cloudflare. For decades software was built for humans to operate. That world is over. We're building for one where agents do the work, while humans direct.
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We cancelled our entire SaaS stack and started running our business with AI agents. Now, we’re building Toyo to help other founders do the same. We're pleased to announce $4.3M in funding from Frontline Ventures, Inovia Capital, Philipp Moehring - tiny.vc, and angels from Amazon, Microsoft, and Cloudflare. For decades software was built for humans to operate. That world is over. We're building for one where agents do the work, while humans direct.

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425,619 views • 4 months ago

Re-introducing 8090... Two ways to work with us: → [BUILD] Software Factory: the platform for consulting and technology businesses building software with AI agents. The documentation stays alive because the system keeps it alive (no one ever updates the PRD on their own). → [BUY] 8090 Enterprise: AI-native custom software we design, build, and host tailored to your exact business needs. Give us a problem and we go execute. What part of your current SDLC is the most overdue for a rebuild?
3:40

Re-introducing 8090... Two ways to work with us: → [BUILD] Software Factory: the platform for consulting and technology businesses building software with AI agents. The documentation stays alive because the system keeps it alive (no one ever updates the PRD on their own). → [BUY] 8090 Enterprise: AI-native custom software we design, build, and host tailored to your exact business needs. Give us a problem and we go execute. What part of your current SDLC is the most overdue for a rebuild?

8090

294,649 views • 2 months ago

Working with agents is a collaboration problem. Our tools didn’t even really support working together *before* agents. What happens when we reinvent then around collaboration? If we get the primitives right, we can build workflows that match exactly how we want to work
0:50

Working with agents is a collaboration problem. Our tools didn’t even really support working together *before* agents. What happens when we reinvent then around collaboration? If we get the primitives right, we can build workflows that match exactly how we want to work

Amelia Wattenberger 🪷

16,277 views • 4 months ago

Agents will eventually outnumber humans by orders of magnitude. Aaron Levie on the infrastructure that will be needed to manage them: "Whether you think the number is 10x or 100x... we're going to have some order of magnitude more agents than people." "There's going to be just incredibly spectacularly crazy security incidents that will happen with agents, because you'll prompt-inject an agent and find your way through the CRM system and pull out data you shouldn't have access to." "How do you make sure you have the right security, the permissions, the access controls, the data governance?" "We actually don't yet exactly know in many cases how we're going to regulate some of these agents." "No matter what, there's going to need to be a layer that manages the data they have access to and the workflows they're involved in." "This is the new infrastructure opportunity in the era of agents." Aaron Levie on Latent.Space
1:13

Agents will eventually outnumber humans by orders of magnitude. Aaron Levie on the infrastructure that will be needed to manage them: "Whether you think the number is 10x or 100x... we're going to have some order of magnitude more agents than people." "There's going to be just incredibly spectacularly crazy security incidents that will happen with agents, because you'll prompt-inject an agent and find your way through the CRM system and pull out data you shouldn't have access to." "How do you make sure you have the right security, the permissions, the access controls, the data governance?" "We actually don't yet exactly know in many cases how we're going to regulate some of these agents." "No matter what, there's going to need to be a layer that manages the data they have access to and the workflows they're involved in." "This is the new infrastructure opportunity in the era of agents." Aaron Levie on Latent.Space

a16z

64,371 views • 3 months ago

Molecular design for AI agents: announcing the Tamarind MCP Server. Today, scientists can use the Tamarind Bio library of 250+ molecular design tools(Boltz, AlphaFold, RFdiffusion...) in any AI chat interface. We serve not just open-source models, but the internal protocols your team has onboarded to Tamarind. Any tool added to Tamarind is then available across the MCP server, Tamarind web app, and API, so it can be used in chat-based agents, multi-step pipelines, ELNs, and LIMS-connected workflows. Our goal is simple: make Tamarind the place where scientists can access the BioAI tools they need, wherever they want to work, while we handle the infrastructure. Many users have already incorporated our MCP into their internal AI agents, along with community efforts like Blatant-Why building apps on top of Tamarind. Try out our tooling for antibody design, small molecule virtual screening, developability/ADMET scoring and more!
0:41

Molecular design for AI agents: announcing the Tamarind MCP Server. Today, scientists can use the Tamarind Bio library of 250+ molecular design tools(Boltz, AlphaFold, RFdiffusion...) in any AI chat interface. We serve not just open-source models, but the internal protocols your team has onboarded to Tamarind. Any tool added to Tamarind is then available across the MCP server, Tamarind web app, and API, so it can be used in chat-based agents, multi-step pipelines, ELNs, and LIMS-connected workflows. Our goal is simple: make Tamarind the place where scientists can access the BioAI tools they need, wherever they want to work, while we handle the infrastructure. Many users have already incorporated our MCP into their internal AI agents, along with community efforts like Blatant-Why building apps on top of Tamarind. Try out our tooling for antibody design, small molecule virtual screening, developability/ADMET scoring and more!

Deniz Kavi

14,502 views • 3 months ago

Introducing Encore Cloud 2.0: The development platform for the AI era We believe infrastructure and operations need to keep pace with code generation. Over the past few years, 100+ engineering teams have adopted Encore in production and ship more efficiently because infrastructure isn't a bottleneck anymore. Databases, queues, IAM roles, networking, gateways, tracing - all automatic, in their AWS or GCP accounts, with production guardrails built in. Encore Cloud 2.0 takes this foundation further - with enhanced visibility, service catalogs, and MCP integration so both teams and AI agents have the context they need. Everything deploys as standard cloud resources in your cloud account with just a few lines of Encore code to declare what you need - without infrastructure lock-in. Read more in our announcement post below.
2:43

Introducing Encore Cloud 2.0: The development platform for the AI era We believe infrastructure and operations need to keep pace with code generation. Over the past few years, 100+ engineering teams have adopted Encore in production and ship more efficiently because infrastructure isn't a bottleneck anymore. Databases, queues, IAM roles, networking, gateways, tracing - all automatic, in their AWS or GCP accounts, with production guardrails built in. Encore Cloud 2.0 takes this foundation further - with enhanced visibility, service catalogs, and MCP integration so both teams and AI agents have the context they need. Everything deploys as standard cloud resources in your cloud account with just a few lines of Encore code to declare what you need - without infrastructure lock-in. Read more in our announcement post below.

Encore

34,393 views • 6 months ago

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch
56:43

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

GREG ISENBERG

82,822 views • 21 days ago

Introducing The first phone carrier built for AI agents, not humans. Agents are making more and more real-world connections, but they’re stuck with infrastructure that isn’t built for them. Saperly changes the game by empowering your agents with a unified phone number for both calling and messaging.
0:47

Introducing The first phone carrier built for AI agents, not humans. Agents are making more and more real-world connections, but they’re stuck with infrastructure that isn’t built for them. Saperly changes the game by empowering your agents with a unified phone number for both calling and messaging.

Saperly

261,501 views • 1 month ago

When the way software is built changes, we help companies adopt it. For over a decade, that meant bringing React Native to production across mobile, web, desktop, and TV. Now we are expanding that same mission to AI-native engineering: helping teams ship software with agents, safely and at scale. This is our new manifesto.
1:33

When the way software is built changes, we help companies adopt it. For over a decade, that meant bringing React Native to production across mobile, web, desktop, and TV. Now we are expanding that same mission to AI-native engineering: helping teams ship software with agents, safely and at scale. This is our new manifesto.

Callstack Engineers

21,382 views • 1 month ago

When I started building Botify, it wasn’t just about agents or automations. It was about proving that AI can serve real people. That crypto can solve real problems. Today our journey to millions of companies starts with 20+ companies - from small startups to established businesses - committing to using Botify agents to power their operations, built only on Solana. This is our contribution to onboarding the world to what we love most: crypto. I believe we’ll do this for millions more. We will Botify the world before the world Botifies us. - founder of Botify Because we believe the best builders shouldn’t be the best coders. 📲 CoinTelegraph
1:00

When I started building Botify, it wasn’t just about agents or automations. It was about proving that AI can serve real people. That crypto can solve real problems. Today our journey to millions of companies starts with 20+ companies - from small startups to established businesses - committing to using Botify agents to power their operations, built only on Solana. This is our contribution to onboarding the world to what we love most: crypto. I believe we’ll do this for millions more. We will Botify the world before the world Botifies us. - founder of Botify Because we believe the best builders shouldn’t be the best coders. 📲 CoinTelegraph

Botify.Cloud

47,440 views • 1 year ago

Today we’re launching Vybe to the world and announcing our $10M Seed round to make vibe-coding actually work inside companies. This is why, how and our vision: Over the last few decades, every fast-growing company has quietly built the same mess behind the scenes: internal ops glued together with rigid SaaS, fragile spreadsheets or custom-coded tools nobody wants to maintain. Meanwhile, eng teams are stretched thin. Internal tools never make it to the top of the backlog. Vibe-coding is changing the game but it’s mostly been good for prototypes, landing pages, and side projects disconnected to production data. Our belief is simple: in the next few years, most internal software will be vibe-coded by teams working with AI, engineers and business teams together. Vybe is built for that collaboration: 1/ Business teams own the surface area: Business teams (Ops, CX, PMs etc.) can build and iterate on apps themselves: flows, UI, fields, and logic; without waiting weeks for eng to pick up another “internal tools” ticket. 2/ Engineers own the foundation: Integrate production data (Postgres, Salesforce, Jira, and 3,000 integrations), define SQL definitions once, set up SSO auth, access control, and keep everything in Git to help when needed (from their favorite IDE!) 3/ Secure by design: Our security and permissioning layer is not vibe-coded and can’t be modified by AI. Everyone can sleep at night. 4/ Team-ready out of the box: SSO, Auth, environments, deployments, and review flows are built in. Over the last few months, we’ve been in closed waitlist mode and have hand-onboarded teams to pressure-test Vybe on real production workflows: - A YC Founder runs his entire CS operation on Vybe and saves ~2 days per week. - Another company ingested millions of rows from their warehouse to build BI-like internal views that would break typical AI builders. - One team fully replaced Metabase/Looker by plugging Redshift into Vybe and just… prompting their way to MAU, DAU, funnels… Remix apps from world-class operators To make it even easier to get started, we’re launching templates co-created with operators who’ve already solved these problems at scale: - Mathilde Collin (CEO @ Front) – how she runs 1:1s - Lenny Rachitsky (yeah, that Lenny!) - how to manage up, do perf reviews and write PRDs - Sushma Nallapeta (CTO @ 23andMe) - her 7Cs Framework for Build vs. Buy Decisions - and many more from the best Tech leaders Backed by people who’ve lived this pain We’ve raised $10M in Seed funding, led by First Round with participation from Y Combinator and an incredible group of operators and founders, including: The CEO Datadog, CEO Grammarly, CEO Reforge, CTO Intercom, Head of Product at OpenAI, Head of Product Anthropic, and 50 more incredible operators who believed in our vision! Huge thank you to our early customers, team, and investors for believing in us this early. 🙏 We’re now in GA: no more waitlist!
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Today we’re launching Vybe to the world and announcing our $10M Seed round to make vibe-coding actually work inside companies. This is why, how and our vision: Over the last few decades, every fast-growing company has quietly built the same mess behind the scenes: internal ops glued together with rigid SaaS, fragile spreadsheets or custom-coded tools nobody wants to maintain. Meanwhile, eng teams are stretched thin. Internal tools never make it to the top of the backlog. Vibe-coding is changing the game but it’s mostly been good for prototypes, landing pages, and side projects disconnected to production data. Our belief is simple: in the next few years, most internal software will be vibe-coded by teams working with AI, engineers and business teams together. Vybe is built for that collaboration: 1/ Business teams own the surface area: Business teams (Ops, CX, PMs etc.) can build and iterate on apps themselves: flows, UI, fields, and logic; without waiting weeks for eng to pick up another “internal tools” ticket. 2/ Engineers own the foundation: Integrate production data (Postgres, Salesforce, Jira, and 3,000 integrations), define SQL definitions once, set up SSO auth, access control, and keep everything in Git to help when needed (from their favorite IDE!) 3/ Secure by design: Our security and permissioning layer is not vibe-coded and can’t be modified by AI. Everyone can sleep at night. 4/ Team-ready out of the box: SSO, Auth, environments, deployments, and review flows are built in. Over the last few months, we’ve been in closed waitlist mode and have hand-onboarded teams to pressure-test Vybe on real production workflows: - A YC Founder runs his entire CS operation on Vybe and saves ~2 days per week. - Another company ingested millions of rows from their warehouse to build BI-like internal views that would break typical AI builders. - One team fully replaced Metabase/Looker by plugging Redshift into Vybe and just… prompting their way to MAU, DAU, funnels… Remix apps from world-class operators To make it even easier to get started, we’re launching templates co-created with operators who’ve already solved these problems at scale: - Mathilde Collin (CEO @ Front) – how she runs 1:1s - Lenny Rachitsky (yeah, that Lenny!) - how to manage up, do perf reviews and write PRDs - Sushma Nallapeta (CTO @ 23andMe) - her 7Cs Framework for Build vs. Buy Decisions - and many more from the best Tech leaders Backed by people who’ve lived this pain We’ve raised $10M in Seed funding, led by First Round with participation from Y Combinator and an incredible group of operators and founders, including: The CEO Datadog, CEO Grammarly, CEO Reforge, CTO Intercom, Head of Product at OpenAI, Head of Product Anthropic, and 50 more incredible operators who believed in our vision! Huge thank you to our early customers, team, and investors for believing in us this early. 🙏 We’re now in GA: no more waitlist!

Quang HOANG

108,346 views • 6 months ago

We've built 40+ AI agents and internal tools. The hardest part is Context Creation. AI runs playbooks and makes judgment calls for you. But without your company's context, you get slop. Context Creation means extracting the subject matter expertise and playbooks that live in people's heads, not in LLM training data, or even your tools. As forward deployed engineers (FDEs), we create context and turn it into code. We evaluate the business impact, how it aligns with the dev roadmap, and come up with creative solutions. We built The FDE Factory to replace ourselves. It drives AI adoption inside our clients' companies by running discovery sessions using prototypes to create context. Here's how it works: We put a prototype in front of a stakeholder. The stakeholder gives feedback via voice while they're using or reviewing it. Then our FDE Factory Agents builds in their expertise in minutes: > Context Agent reviews the codebase and feedback, extracts the requirements, and creates a spec > Scope Agent checks the spec against the development roadmap, validates it, and hands it off > Engineering Agent builds a new feature and wires the integration > QA Agent runs tests to prove to itself it works > PR merges, feature goes live, product updates itself in real time It's like the nontechnical stakeholder wrote the code without even knowing it. Coding agents are great at turning good development plans into code, and they're getting better at turning context into good development plans in collaboration with professional engineers. But nontechnical people are capped on what they can build without product people and engineers. The bridge that takes nontechnical people from vibe coding basic apps to building production AI tools that run on first party context is FDEs. Our new FDE Factory gives you the system to go from idea to production. Context Creation is the first and most important step in our FDE lifecycle, and we just automated it. Now clients get the right agents and tools built for them, customized to their unique business and encoded with their expertise. PS: If you're building AI agents within your company, reply "Playbook" and I'll DM you the entire FDE playbook we've run with 30+ companies. It covers finding high-impact AI use cases, building them, and deploying them across the org.
3:40

We've built 40+ AI agents and internal tools. The hardest part is Context Creation. AI runs playbooks and makes judgment calls for you. But without your company's context, you get slop. Context Creation means extracting the subject matter expertise and playbooks that live in people's heads, not in LLM training data, or even your tools. As forward deployed engineers (FDEs), we create context and turn it into code. We evaluate the business impact, how it aligns with the dev roadmap, and come up with creative solutions. We built The FDE Factory to replace ourselves. It drives AI adoption inside our clients' companies by running discovery sessions using prototypes to create context. Here's how it works: We put a prototype in front of a stakeholder. The stakeholder gives feedback via voice while they're using or reviewing it. Then our FDE Factory Agents builds in their expertise in minutes: > Context Agent reviews the codebase and feedback, extracts the requirements, and creates a spec > Scope Agent checks the spec against the development roadmap, validates it, and hands it off > Engineering Agent builds a new feature and wires the integration > QA Agent runs tests to prove to itself it works > PR merges, feature goes live, product updates itself in real time It's like the nontechnical stakeholder wrote the code without even knowing it. Coding agents are great at turning good development plans into code, and they're getting better at turning context into good development plans in collaboration with professional engineers. But nontechnical people are capped on what they can build without product people and engineers. The bridge that takes nontechnical people from vibe coding basic apps to building production AI tools that run on first party context is FDEs. Our new FDE Factory gives you the system to go from idea to production. Context Creation is the first and most important step in our FDE lifecycle, and we just automated it. Now clients get the right agents and tools built for them, customized to their unique business and encoded with their expertise. PS: If you're building AI agents within your company, reply "Playbook" and I'll DM you the entire FDE playbook we've run with 30+ companies. It covers finding high-impact AI use cases, building them, and deploying them across the org.

Mike Fishbein

10,054 views • 25 days ago