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Kraftful Inbox dropped on Launch Y Combinator🧡 Gathering user feedback used to be chaos. Now it’s automatic. Support tix, sales calls, surveys, reviews, Slack, Discord, Reddit → instant Jira tickets Loved by 50K+ teams. Check out why 👇

11,804 views • 1 year ago •via X (Twitter)

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Today, the future of IT support 𝘴𝘱𝘦𝘢𝘬𝘴 for itself! We’ve just launched Atomicwork’s Universal Agent, now available right from your browser with built-in Voice, Vision, Chat and Work AI capabilities! This isn’t just another update; it’s a revolutionary leap toward contextual, intelligent, real-time support. Atom understands what’s on your screen, listens to what you need, and guides you through tasks step by step. For years, IT support has meant navigating portals, raising tickets, and just waiting for help. @ Atom, the Universal Agent, changes that. It works where you work—in your browser, inside business apps you use at work like Salesforce or Jira to offer proactive and intuitive support with zero context-switching. 🗣️ Talks to you in natural language using Voice AI - Whether it’s fixing an access issue or fetching a sales report, just say it. Atom listens, responds, and walks you through the next-best actions in real time. 👁️ Sees what you can see using Vision AI – Finding it tough to explain what’s broken? Atom sees your screen, understands the issue you're facing and steps in to guide you. 💻 Works where you work using Work AI. The browser extension ensures that it’s available wherever you are and get help in whatever mode you prefer. This launch is just the beginning of a smarter, more seamless way to support employees and service teams alike. Support now can truly be accessed from anywhere, anytime! 💪 We can't wait for you to try out our Universal Agent for your varied enterprise support use cases 🚀 Sign up now to see it in action 🔗 🎦 Watch our team, Denin Siby, Bhavya Vats, Arkajit Datta, and Aishwarya 👾 Hariharan, take you through the core capabilities of the Universal Agent: . . . Vijay Rayapati Parsuram Vijayasankar Aparna Chugh Denin Siby Arkajit Datta

Atomicwork

15,053 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 🔜.

Pasha Rayan

53,998 views • 1 year ago

Another blow to Anthropic! They spent months building what's now fully open-source. Anthropic recently put Claude inside Slack, where you can tag it in a channel. It reads the thread, breaks the task into steps, and posts the result back. The problem is that it only runs Claude and only in the channels Anthropic supports. Running your own agent there is harder. The reasoning, tool calls, and state management are mostly handled by the framework. Connecting that agent to a messaging platform is not. Moreover, each platform has a different integration: - Slack renders messages with Block Kit - Teams uses Adaptive Cards - and each has its own SDK, auth flow, and delivery model. If an agent needs to run on three platforms, one must write three separate integrations against the same agent logic. That overhead explains why most custom agents never get deployed to Slack, and why the ones that do are usually a single vendor's hosted assistant. The alternative is to keep the agent in one place and add a per-platform adapter that translates its output into each platform's native format. The agent is written once, and each channel requires just another output target instead of a separate build. CopilotKit open-sourced this full implementation in the Channels SDK. Essentially, any agent that implements AG-UI can run in a messaging platform in a few lines of code, like Slack, Teams, Discord, WhatsApp, and many more. Because the agent runs inside the thread, it has that conversation's context, so it can summarize the discussion, open a ticket, or route to the right person. It works with any backend, so LangGraph, CrewAI, Mastra, Google ADK, or a plain HTTP agent can connect through an existing endpoint. The same message can render as a Block Kit in Slack and as Adaptive Cards in Teams. In practice, the model and orchestration stay the same; it requires no migration or rewrite. It also handles human-in-the-loop approvals, persistence, and transcripts that carry state across platforms, so a thread started in Teams can continue in Slack. CopilotKit is open-source, and AG-UI is supported across every major agent framework, including LangGraph, CrewAI, Mastra, and Google ADK. Here's the repo: (don't forget to star it ⭐) The agent running in Slack no longer has to be a vendor's. It can be the one you already built. The video below shows this in action. Thanks to CopilotKit for working with me on this launch.

Akshay 🚀

244,298 views • 1 month ago

✨"Cubism Editor 5.4.00 alpha1" limited release until September 14, 2026✨ We are also releasing Cubism 5 SDK for Unity R7 alpha1, which supports these new features, at the same time. Check out the accompanying digest video to learn about the main new features. 🔥[New Features] ✏️ [Parameter Controller SDK Support] Parameter controllers (IK) are now supported in the SDK. You can configure them directly on the model and export them as runtime files. Additionally, a new "target-only" controller can be defined to allow the controller to follow a path. ✏️ [Model State Set] A new model state set feature has been added. You can register working states in a dedicated palette, enabling you to recall specific states of visibility, lock, and parameter values with a single click. This helps you work more efficiently by allowing you to switch between states tailored to different tasks. ✏️[Expanded Editing Support for External Application Integration API ] The external application integration API has been expanded to include object editing and more. You can now integrate an API to directly add and edit parts, deformers, and parameters on models in the editor. ✏️[Enhanced automatic layout for texture atlases] The automatic layout algorithm for texture atlas editing has been completely redesigned. This enables more efficient packing with less unused space. You can configure the layout settings individually for each texture, allowing for flexible layouts. [How to use Cubism 5.4 alpha] Please see the announcement page for details on downloading and feedback. ⚠Notes on using the alpha version - The alpha version is provided for the purpose of gathering feedback on the usability and performance of new features. - Usage Period: Until September 14, 2026. - Please be sure to create a backup, as there is a possibility of data corruption. - Alpha version data and SDK outputs are not guaranteed to function properly and we do not provide support for it. #Live2D #cubism54_alpha

Live2D

103,790 views • 2 months 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!

Quang HOANG

108,724 views • 9 months ago

The moral obligation of great design: A call to arms by @ThisIsBobBaxley Bob has designed products used by billions of people over his 35-year career at Apple, Pinterest, Yahoo, and ThoughtSpot. During his eight years at Apple, he led design for the online store and the App Store, and witnessed the iPhone’s transformative launch while working under Steve Jobs. Bob champions the obligation designers have to reduce frustration in people’s daily lives. "I don't think many people working in the industry understand the scale of what they're doing. Software, both for the audience and for the creators, is an anonymous medium. The products we're building are just these crazy, faceless things created by a bunch of people, you know, who knows where. We never see anybody on the other side of the glass. It's very hard to really understand that we're creating something in Figma on their computer that's going to be interacted with by billions of people, thousands and thousands of times. People don't want to try to figure out how to navigate our login screens or go through our onboarding process. They just wanna get home and spend time with their families and pet their dogs and have a nice dinner." Bob also has some other spicy takes: 🔸 Why design should report to engineering, not product 🔸 The “Beatles principle”—why the best products come from teams of 4 to 6, not 40 to 60 🔸 Why you need design tenets, not principles (with real examples) 🔸 Why you should delay sketching and prototyping as long as possible 🔸 Why software is fundamentally a medium, like film or music 🔸 Much more Listen now 👇 • YouTube: • Spotify: • Apple: 🏆 This entire episode is brought to you by Stripe—helping companies of all sizes grow revenue:

Lenny Rachitsky

83,728 views • 1 year ago

I’m giving away $15,050 today to my top supporters from the Avantis and Boundless drops! Why am I doing this? Easy: I wouldn’t be here without your support these last 2 months. I started this infofi journey on 06/25/2025, and I’m proud of what we’ve built together. Time to give back. If you liked, commented, or reposted my content about them, you might be eligible to get between $50 and $1,000. Check the leaderboards 👇 👉 100 winners for Avantis: 👉 15 winners for Boundless: 💡 If you’re on the list, reply in the comments with: ▫ Wallet ▫ Your ranking position + which drop (Avantis and/or Boundless) ⚡ Payments go out today in USDC on Base. Send an EVM-compatible address (Rabby, Metamask, etc.) or an exchange wallet that supports Base. ━━━━━━━━━ Making these sheets was CRAZY, almost all manual, post by post, to keep it fair. From now on, you can engage directly on my Discord in the post-twitter channel (see the video below for a step-by-step guide). This way I can build leaderboards faster and reward the community every drop. 👉 Join my Discord: Leaderboards reset monthly, so there are always fresh chances. ━━━━━━━━━ Looking ahead: for every drop I get here on X (Wallchain, Kaito, or any other), 30% always goes back to the community: • 10% for top engagers • 20% for top engagers who are also part of my private community (currently limited to Brazilians, but we may expand to English speakers in the future if it makes sense, and if I can deliver real value and support, not just rewards). Thanks a lot for the support, I’m hyped to share this with you all. God bless!

Rodrigo Moura Crypto

17,498 views • 1 year ago

Fewer than five people on Earth have built two open-source JavaScript framework companies. Sam Bhagwat is one of them. The book that made him known is now one of the go-to texts for building agents. You’ve seen it: Principles of Building AI Agents. But the part that’s important to his story is the low point before Mastra. When Gatsby faded, the acquisition went sideways. They went off to build sales AI and failed for months, then came back to open-source dev tools and instantly felt like they were back on track. His word for it: the "unknown knowns." The things you know so well you forget you know them. They'd forgotten they were world-class at the exact thing they walked away from. I sat down with him at Y Combinator, where Mastra went through the Winter 2025 batch. We got into: •Why "that's interesting" is the most dangerous thing a user can tell you •Why planning in quarters is dead, it's actions-per-minute now •Why it's okay to quit your idea •Writing a print book in an era that moves too fast to print •The loneliness nobody talks about: teams stopped pair programming because everyone's driving their own agent His rule, from a YC partner: generosity breeds luck. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Intro — Y Combinator (01:30) What Mastra Is (03:00) Content Wants to Be Frequent (05:00) Shipping a Tier-One Feature Every Day (07:00) The $13M Seed and $22M Series A (09:00) Turn-Based vs. Real-Time Strategy (12:00) Why Experience Beats Fresh Eyes (15:00) "That's Interesting" Means They're Not Interested (18:00) It's Okay to Quit Your Idea (21:00) The Book That Started as a Joke (25:00) From Journalism to Open Source (28:00) The Netlify Acquisition, and What It Cost (32:00) The Unknown Knowns (36:00) The YC Winter '25 Takeoff Story (40:00) Remote Work Is Underrated in the Age of AI (44:00) The New Loneliness of Building With Agents (47:00) What He Still Can't Figure Out About Agents

Julia Fedorin

35,776 views • 1 month ago

The Agentic Literature Review is Now a Reality. 🚀 I watched a student from King’s College London dismantle a task that used to take weeks. His mission? Deconstruct 47 complex academic papers for his dissertation. The old way: ❌ Endless skimming & highlighting ❌ Messy, unsearchable notes ❌ Citation chaos across 5 different tools The new way? He used a single platform and finished the core analysis in an afternoon. This isn't just another "AI summarizer." ResearchCollab is an AI co-pilot for research. I tested it against the standard "academic grind." The difference was staggering: 🔴 Traditional Workflow: Scattered PDFs, chaotic notes, mental burnout. 🟢 ResearchCollab Workflow: • AI instantly surfaces key insights from 250M+ papers without manual prompting. • Auto-organizes and relates everything personalized to the user. • Generates perfect citations (APA, MLA) in one click. • Brainstorms new research directions you might have missed. 👇 See how it works (No Credit Card Needed): Start your free trial → Why this is a silent revolution for knowledge workers: 1️⃣ Students are cutting literature review time by up to 80%. 2️⃣ Research teams are collaborating in real-time, killing version control nightmares. 3️⃣ The "blank page syndrome" is solved. AI helps you generate outlines and spark unique ideas instantly. The most compelling part? It’s not just about speed. It’s about clarity. ✔️ Finds connections between papers you'd never see. ✔️ Keeps your entire research universe in one searchable place. ✔️ Works 24/7 for less than the cost of your monthly coffee budget. This is the "Copilot" moment for academia and R&D. The barrier to high-quality, organized research has just collapsed. 👉 Support ResearchCollab Product Hunt launch : PS: I've compiled a short guide on "The 5-Day Research Sprint" methodology that this enables. Like 👍 and Comment "Research" and I'll DM you the link.

Anuj

10,780 views • 10 months ago

Brian Armstrong shares the Y Combinator advice that helped Coinbase find product/market fit “The first version of a product you put out doesn’t work. In fact, that’s the only thing I’ve ever seen happen in startups. I’ve never seen a startup where the first version of their product actually worked. Sometimes in hindsight people like to tell that story, but I think in reality it’s very rare.” The first version of Coinbase was a hosted Bitcoin wallet. Brian posted it to Reddit and a few people signed up but nobody stuck around. Rather than get discouraged though, he recalled the advice he got at Y Combinator: “Don’t spend your time going to conferences and trying to raise money. If you don’t have product/market fit yet, talk to your customers and improve the product based on their feedback… There’s really only two things you should be doing in the early stage - talking to your customers and improving the product. It sounds like simple advice, but people spend so much time doing other stuff that’s not actually real work.” Following that advice, Brian emailed 10 of the people who had signed up for Coinbase and asked if they’d be open to a quick phone call. One of the users liked the wallet but didn’t have any Bitcoin. Brian asked him: “If there was an easy way to get Bitcoin into your wallet - like a buy button or something - would you have stuck around and used it?” “Yeah, probably” replied the user. So Brian spent the next few months securing bank partnerships and money transmission licenses so he could build a simple buy button into the app. Then he launched it. “The minute we launched that buy button, it started to grow every day organically with no marketing or anything. And that was the minute I felt like we finally had product/market fit.” Video source: Steven Bartlett (2022)

Startup Archive

78,532 views • 11 months ago

Brian Armstrong shares the Y Combinator advice that helped Coinbase find product/market fit “The first version of a product you put out doesn’t work. In fact, that’s the only thing I’ve ever seen happen in startups. I’ve never seen a startup where the first version of their product actually worked. Sometimes in hindsight people like to tell that story, but I think in reality it’s very rare.” The first version of Coinbase was a hosted Bitcoin wallet. Brian posted it to Reddit and a few people signed up but nobody stuck around. Rather than get discouraged though, he recalled the advice he got at Y Combinator: “Don’t spend your time going to conferences and trying to raise money. If you don’t have product/market fit yet, talk to your customers and improve the product based on their feedback… There’s really only two things you should be doing in the early stage - talking to your customers and improving the product. It sounds like simple advice, but people spend so much time doing other stuff that’s not actually real work.” Following that advice, Brian emailed 10 of the people who had signed up for Coinbase and asked if they’d be open to a quick phone call. One of the users liked the wallet but didn’t have any Bitcoin. Brian asked him: “If there was an easy way to get Bitcoin into your wallet - like a buy button or something - would you have stuck around and used it?” “Yeah, probably” replied the user. So Brian spent the next few months securing bank partnerships and money transmission licenses so he could build a simple buy button into the app. Then he launched it. “The minute we launched that buy button, it started to grow every day organically with no marketing or anything. And that was the minute I felt like we finally had product/market fit.” Video Source: Steven Bartlett

Startup Archive

151,324 views • 2 years ago

Stripe CEO Patrick Collison shares the tactics he used for finding product/market fit “We tried very hard to understand in granular detail what exactly it was that people were doing, where they were tripping up and so on.” Patrick gives some examples of specific tactics: • A public chat room to provide support to people integrating Stripe • For the first 10 users of Stripe, every API request sent an email to the founders so they could better understand how users were using their product and see if users were doing anything weird • All errors generated a high-priority email to the founders. This created a pleasant user experience where 15 minutes after hitting an error, Patrick could reach out to them and let them know the issue was fixed “These are all kind of examples of a general pattern of trying to be hyper-attentive to all the micro details of what people were doing in the product and iterating rapidly in response to it. Generally speaking, I think pre-product/market fit metrics are actually relatively unhelpful because probably not that many people are using your product. If it’s 20 users, you can in some sense afford to just look at everything they’re doing to understand what’s working and what isn’t.” Another example of this Patrick gives is embedding a text input on each of their web pages with placeholder text prompting users to give them useful feedback(e.g. “The worst thing about Stripe is…”, “The worst thing about this page is…”, or “I really hate the way Stripe does…”). As Patrick explains: “At that stage, you have to be kind of masochistic. We’d always be waking up to all these emails telling us all the terrible things about Stripe. But that was a helpful to-do list for the day ahead. Video source: Y Combinator (2018)

Startup Archive

45,833 views • 8 months ago

Stripe CEO Patrick Collison shares the tactics he used for finding product/market fit “We tried very hard to understand in granular detail what exactly it was that people were doing, where they were tripping up and so on.” Patrick gives some examples of specific tactics: - A public chat room to provide support to people integrating Stripe - For the first 10 users of Stripe, every API request sent an email to the founders so they could better understand how users were using their product and see if users were doing anything weird - All errors generated a high-priority email to the founders. This created a pleasant user experience where 15 minutes after hitting an error, Patrick could reach out to them and let them know the issue was fixed “These are all kind of examples of a general pattern of trying to be hyper-attentive to all the micro details of what people were doing in the product and iterating rapidly in response to it. Generally speaking, I think pre-product/market fit metrics are actually relatively unhelpful because probably not that many people are using your product. If it’s 20 users, you can in some sense afford to just look at everything they’re doing to understand what’s working and what isn’t.” Another example of this Patrick gives is embedding a text input on each of their web pages with placeholder text prompting users to give them useful feedback(e.g. “The worst thing about Stripe is…”, “The worst thing about this page is…”, or “I really hate the way Stripe does…”). As Patrick explains: “At that stage, you have to be kind of masochistic. We’d always be waking up to all these emails telling us all the terrible things about Stripe. But that was a helpful to-do list for the day ahead." Source: Y Combinator (Oct 2018)

Startup Archive

32,192 views • 1 month ago