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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... personal use cases. Everything clicked for us. The infrastructure we'd built wasn't just useful for humans anymore: it was exactly what agents needed to operate inside real companies and teams. What happens when agents can work 24/7, with the right context, the right permissions, and access to your company's tools? A founder becomes a one-person army. A small team operates like a much bigger one. That's the mission we fell in love with at Vybe. Our agents have names and roles. They have their own email, Slack, phone number. They prep meetings, follow up with leads, run ops, update CRMs, build internal tools. Vybe runs on Vybe. We're onboarding 10 teams a week to run AI-native companies.show more

Quang HOANG

1,294 subscribers

35,357 views • 4 months ago •via X (Twitter)

Science & Technology

Anya Rossi• Live Now

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28 Comments

Utpal Nadiger4 months ago

congrats on the launch! would love to give agents built on vybe a computer :)

Quang HOANG4 months ago

link to request access:

Lenny Rachitsky4 months ago

Go Vybe!

Micka4 months ago

Let's go! But also, can I know who said this? "This is the most beautiful UI I've seen in any agent builder" YC Founder

Taro Fukuyama4 months ago

Love Vybe Agent! I've built 15+ agents already and can't live without them. Let's goo!

Human Thomas4 months ago

Congrats!!

Gregor4 months ago

curious if the 'lovable for internal apps' users were the ones asking for the permissions layer or if you basically built a new product and are now going back to them with it

Chief AI Officer4 months ago

time to vybe .now!

Hoan Tran4 months ago

Cool product. Curious how you handle trust, transparency, and auditability. As agents start taking actions across tools, how do users trace why a decision was made, what context was used, and prevent agents from going off the rails vs. just inheriting model behavior?

Vatsalpandya3334 months ago

W

Nico Lecomte4 months ago

Autonomous agents running part of your business is so important! A lot of our ops are now agentic and running on Vybe! Love this new version 🫶

Stefan A.4 months ago

great idea, guys! wish you good luck and looking forward to see where the company goes!

Eli Mernit4 months ago

🔥🔥🔥

Karim TechInnovateur4 months ago

Le vrai moat il est là: permissions, contexte, intégrations, workflows. Pas juste un énième wrapper claqué autour d’un LLM.

Alexander Benz4 months ago

The trust layer is the product here. Agents get interesting when permissions, tools, and company context are explicit enough that a human can inspect why the work happened.

conor brennan-burke4 months ago

congrats on the launch! LFG

Greg Gambatto3 months ago

let’s goooo guys 🫡

sabir hussain4 months ago

Which business function do teams automate first?

Victoria Wu4 months ago

Damn! Who came up with the name? Genius! Vibe coding has evolved into Vybe coding. 🔥

Aaliya4 months ago

Agents with real permissions change how teams operate

Gordon Wintrob3 months ago

Congrats!! Super hard to pull this off. Let's go Vybe.

Linky3 months ago

When agents gain context, permission, and a place inside the workflow, they stop feeling like tools and start feeling like teammates. 🤝

₮Ɽ₳Vł₴4 months ago

Vybe is not a great name for “trust” application lol

Neil Mehta3 months ago

agents with their own email

Nick Venturi4 months ago

dont leave us hanging

Julius Stener4 months ago

Nice launch! You can already do all of this @righthanddotai ! (And you don't need to wait for access!) Join hundreds of people using Righthand every day!

sydney shaw4 months ago

@ycombinator @ariavalidate validate

Guillaume Luccisano4 months ago

Let's go!!!

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iLands

59,049 views • 1 month 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!

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

14,630 views • 6 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.

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

36,359 views • 9 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

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

84,760 views • 3 months 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.

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

24,831 views • 4 months ago