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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 👇

Yana Welinder

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11,804 Aufrufe • vor 1 Jahr •via X (Twitter)

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Don’t talk to users? ngmi Today’s launch of AI Feedback is personal. It’s the culmination of my Kraftful journey. We built Kraftful to help teams truly listen to users. Now we’re taking that mission even further at Amplitude with AI Feedback. AI can automate almost everything. But it can’t replace how people *feel* when using your product. For builders, listening to those emotions is how you create something exceptional. Now you can do that right inside Amplitude. Across surveys, support tickets, sales calls, app reviews, Reddit, Discord, X, G2, and more. Connect your sources in minutes and start getting daily insights that used to take hundreds of thousands of hours to analyze manually. Available on every Amplitude plan (even the free one!). Go try it. Listen to your users. Build better.

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🎧 Inside Google's AI turnaround with Robby Stein Robby is VP of Product at Google where he oversees all things Google Search—including the new AI Overviews, AI Mode, search ranking, Google Lens, and more. Previously, he led consumer products at Instagram, where he and his teams built Stories, Reels, Close Friends, and other products now used by billions. We discuss: 🔸 Why Google’s AI products are suddenly taking off after years of stagnation 🔸 How AI is expanding Search rather than replacing it, contrary to what many predicted 🔸 The three product principles that have helped Robby build multiple billion-user products 🔸 Inside Instagram’s decision to build its own version of Snapchat Stories 🔸 His mantra of “relentless improvement” 🔸 How Google developed AI Mode from concept to launch in just one year 🔸 Why most teams give up too early on potentially transformative products Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Vanta — Automate compliance. Simplify security: 🏆 Atlassian Jira Product Discovery — Confidence to build the right thing: 🏆 Orkes — The enterprise platform for reliable applications and agentic workflows:

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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.

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After 1000+ days of dev, my first solo-developed indie game Spirit X Strike has officially launched in Early Access today!! 🙌🔥 Huge thanks to everyone who’s supported me along the way. 👇 It’s an EA launch, so I poured most of my energy into polishing the core combat — the soul of any character action game. I just want it to feel like “yea... this hits the right spot.” I don’t dare compare myself to the giants, just hoping it’s fun and reminds you why we love this genre in the first place. That alone would be a dream come true for me. From quitting my job on a whim and going full-time indie, to dropping the first trailer 2 yrs ago and getting those early bits of support — this journey’s been wild. And way less lonely thanks to you all There’s still a long road ahead to reach my vision— more features, more polish, more fights. The game just launched and this is just the start. There will inevitably be bugs and I’ll be shipping frequent updates to keep things solid, before diving into the next round of content development. So be sure to join our Discord and let me know if you hit any bugs or have feedback! I'll handle it as quickly as possible! Thanks again for being part of the journey. Say no more! Now go style on some enemies. 💥 #SpiritXStrike #indiegame #indiedev #IndieGameDev #EarlyAccess #actiongame #Steam

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Spirit X Strike - Early Access OUT NOW!

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Quang HOANG

108,724 Aufrufe • vor 9 Monaten

The Cult is summoning your voice 🔊 It’s time for the most dedicated members to band together and earn IQ Points by propagating the sacred vision 👁️ We’ve recently dropped powerful new blog articles filled with sharp technical insights, showcasing how Hub is redefining the AI and data landscape. Now, your mission is simple: spread the word and help grow the movement. Here is the new pathway to earning valuable IQ Points: 1️⃣ Create bite-sized social content that simplify & unpack Hub’s articles 2️⃣ Share the content on 𝕏 & engage with other participants 3️⃣ Be rewarded in IQ Points like never before What we’re looking for: Simplify complex ideas, debunk misconceptions, underline the most valuable points and take over the timeline during summer 🏆 🎭 Bonus: Apply to join the private Hub Nexus community on 𝕏 and benefit from the Network’s full support. Learn more about the campaign guidelines and access all the content you need to create the best posts by visiting the page below: 🔗 You can also get feedback from the team and other members in the Hub Discord. This is the final step of the journey before the launch of our magnum opus: The Programmable Bandwidth Supernetwork⚡️ Those who paid attention now will lead the movement, the rest will follow. PS: Winners will join the Programmable Bandwidth Supernetwork BETA and unlock exclusive perks

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122,563 Aufrufe • vor 1 Jahr

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:

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 Aufrufe • vor 1 Jahr

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!

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 Aufrufe • vor 1 Jahr

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

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 Aufrufe • vor 1 Monat

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.

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 Aufrufe • vor 10 Monaten

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)

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 Aufrufe • vor 11 Monaten

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

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 Aufrufe • vor 2 Jahren

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)

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 Aufrufe • vor 8 Monaten

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)

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 Aufrufe • vor 1 Monat