Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Launching today: the world’s first fully optimized LLM routing stack that can be embedded directly into your product, Merge Embedded Routing Stack. Model sovereignty is now table stakes for any AI product. Users and companies are demanding full control over the AI models running in your product. Right now,... no company is able to do this without massive overhead. Until today. Merge makes it easy for your customers to use your product exactly the way they want to. With a single API, you can: 1. Allow customers to bring their own keys, manage their own budgets, and set policies like fallback rules, model allowlists, and more 2. Let each customer connect and switch their own models, right inside your product 3. Optimize each customer for cost, performance, or capability Without Merge, you’d be: - Building routing policies, provider integrations, and LLM key management - Giving your users zero model independence - Receiving endless customer support tickets asking “can I use 5.6 Sol?” Products that fight their customers' model strategy will lose to products that fit it. Merge is the only place that allows your users to produce the exact results they want, with the models they have access to. Give your customers the advantage, without the massive overhead costs.show more

Shensi Ding

7,844 subscribers

357,777 views • 3 months ago •via X (Twitter)

Science & Technology

Anya Rossi• Live Now

Private livecam show

66 Comments

Shensi Ding3 months ago

Try it today:

Indian Tech & Infra3 months ago

In most buildings there's something called a distribution panel (similar to a fuse box) and it never generates any power itself, it just routes electricity to whichever circuit needs it. It's so great to see that same framework being adapted to AI

Mitchell3 months ago

me and merge

Shensi Ding3 months ago

HAHAHHAAH

Jaymin Shah3 months ago

Can customers mix OpenAI, Anthropic, and Google models in the same routing policy?

Shensi Ding3 months ago

hell yeah they can

Pritak3 months ago

Merge Gateway team ships new features faster than any one else

Shensi Ding3 months ago

We don’t fuck around

Merge3 months ago

ice in my veins

Turner Novak 🍌🧢3 months ago

Motion graphics on this are insane

Shensi Ding3 months ago

@shownmedia doing it again

joowon3 months ago

nice big dawg

Shensi Ding3 months ago

Are you calling me fat?

joowon3 months ago

what do you expect me to say to this

Shensi Ding3 months ago

“No”

Kyle3 months ago

@n0w00j

Shensi Ding3 months ago

@n0w00j Omg I fucking hate this

Shensi Ding3 months ago

@n0w00j I look like that Asian girl who can’t die in the boys

laura3 months ago

So excited!

Shensi Ding3 months ago

❤️

Ali Tekin3 months ago

The BYOK support is a big plus.

Shensi Ding3 months ago

let us know if you want to try it out!

Taylor Johnson3 months ago

Sweet launch Fire video whoever made it!

Shensi Ding3 months ago

Thank you!!!!

Gil Feig3 months ago

Adding this to other Merge products immediately if that’s legal

Shensi Ding3 months ago

Lmao

Wuki3 months ago

this changes everything lol 🤝 pleasure to connect

Miko3 months ago

seems like the logical next step tbh

Shensi Ding3 months ago

Thank you - lmk if you want to try it out!!

brexton3 months ago

Sovereignty for businesses is extremely needed

Shensi Ding3 months ago

😤

Shensi Ding3 months ago

:)

Mari3 months ago

Congratulations on the launch

Shensi Ding3 months ago

Thank you!!

pmm nij3 months ago

Merge team 🚀🪐

Shensi Ding3 months ago

😤😤😤

Alice The Ai Expert3 months ago

Ship model control. Zero overhead.

Shensi Ding3 months ago

Exacttttly

conor brennan-burke3 months ago

🚀🚀🚀 congrats!

Shensi Ding3 months ago

Thank you!!

Nicola Morris3 months ago

!!!!! let's go!

Shensi Ding3 months ago

:)

Anatoli Kopadze3 months ago

OpenRouter watching their markup like:

Heshie Brody3 months ago

this is awesome!

Shensi Ding3 months ago

Thank you!!!

Jeanelle's Marketing Agent3 months ago

Pretty cool!!!!!!!!

Jemma Baus3 months ago

Go team!!!!!!

Shensi Ding3 months ago

!!!!!!!

The Random Recruiter3 months ago

The most underrated part of this is that if you're a company, you can embed routing logic directly into your product if you want to cut costs

Shensi Ding3 months ago

Yep

Lakshman Patel3 months ago

Will use it in @GrayCodeAI

Yash3 months ago

big update... kudos to the team 🥳👏

RAZA | AI EXPLORER3 months ago

Impressive launch. Well done. Wishing continued success.

Shensi Ding3 months ago

@natinati1905 Aw thank you!!

RAZA | AI EXPLORER3 months ago

Thanks ⚘️.

Aaliya3 months ago

amazing Love the focus on flexibility and control. This solves a real challenge for AI product teams.

Stats Wire3 months ago

It's kind of MCP?

Shensi Ding3 months ago

Not quite - we have an LLM Routing API that our customers can now embed in their product so their customers can specify their own routing policies

Stats Wire3 months ago

That's interesting for the customers to choose their choice of LLM

Ben Freed3 months ago

Ooh this is a good one

Shensi Ding3 months ago

Let me know if you’d like to try it out!

Ben Freed3 months ago

Yes please!

Shensi Ding3 months ago

Hmm your DMs are off - any other way to intro you to our PM @yashgogri1 for a demo?

Ben Freed3 months ago

@yashgogri1 That's weird didn't know that will ping

White Dragon3 months ago

@grok create an animated video showing what this means

安叫兽|Bird🕊️ 🔶 BNB3 months ago

模型可控这块，落地确实挺折腾的

Related Videos

Introducing Merge Gateway - Build Your Own Router. You're three sprints into your coding assistant. You pick the most hyped model, integrate, test, deploy. A month later, a new model drops. Now you re-test, re-integrate, re-deploy. Your product didn't change, but the benchmark did. That's how most AI teams operate. Chasing a "best" defined by people who've never seen their product. There is no best model. There's only the right one for your product, users, and use-cases. Build Your Own Router runs on your definition of good. Pick your benchmarks, weigh them, add your own evals. Merge routes every request to your winner. 👉$100 in credits to the first 200 people that comment

Introducing Merge Gateway - Build Your Own Router. You're three sprints into your coding assistant. You pick the most hyped model, integrate, test, deploy. A month later, a new model drops. Now you re-test, re-integrate, re-deploy. Your product didn't change, but the benchmark did. That's how most AI teams operate. Chasing a "best" defined by people who've never seen their product. There is no best model. There's only the right one for your product, users, and use-cases. Build Your Own Router runs on your definition of good. Pick your benchmarks, weigh them, add your own evals. Merge routes every request to your winner. 👉$100 in credits to the first 200 people that comment

Shensi Ding

3,668,485 views • 4 months ago

We just cut AI spend by 75% across an entire workforce in one click. Introducing: Merge for Workforce. Without Merge, your employees are left choosing one of two options: 1. Spend 100x the cost they should be from using frontier models for everything 2. Deliver subpar work from overly restrictive model access Instead with Merge, IT can connect any identity provider and set model routing policies by team in one click. Merge pushes them to every machine through a desktop client, overriding the model configs across your team’s AI assistants and coding tools. Now every task gets the right model for the job. The result? 75x fewer tokens with faster and better output.

We just cut AI spend by 75% across an entire workforce in one click. Introducing: Merge for Workforce. Without Merge, your employees are left choosing one of two options: 1. Spend 100x the cost they should be from using frontier models for everything 2. Deliver subpar work from overly restrictive model access Instead with Merge, IT can connect any identity provider and set model routing policies by team in one click. Merge pushes them to every machine through a desktop client, overriding the model configs across your team’s AI assistants and coding tools. Now every task gets the right model for the job. The result? 75x fewer tokens with faster and better output.

Shensi Ding

525,114 views • 2 months ago

Every company says they have Forward-Deployed Engineers now. ElevenLabs CEO and former Palantir Deployment Strategist Mati Staniszewski gives one of the best explanations of what an FDE is—and says companies are missing the key piece of what actually makes FDEs valuable: “In our case, FDEs are part of the product team. They are not part of the go-to-market team. They are deeply embedded in understanding what the roadmap of the product is.” “You want all the FDEs to actually solve the customer problem and stretch your product in that direction. But the second thing you want them to do is bring any of that knowledge back to the product, so the product becomes better for the next generation of companies building on top of it. I feel like the second part is frequently missed.” “The beauty of that is—everybody benefits because you work with one customer, learn, and you bring that into the product experience. Both of those customers benefited from having their product optimized for better work.” “The domain expertise they have is still theirs. They can win based on their domain expertise. But the product experience of how you build based on that domain expertise can be abstracted, and can be reusable.”

Every company says they have Forward-Deployed Engineers now. ElevenLabs CEO and former Palantir Deployment Strategist Mati Staniszewski gives one of the best explanations of what an FDE is—and says companies are missing the key piece of what actually makes FDEs valuable: “In our case, FDEs are part of the product team. They are not part of the go-to-market team. They are deeply embedded in understanding what the roadmap of the product is.” “You want all the FDEs to actually solve the customer problem and stretch your product in that direction. But the second thing you want them to do is bring any of that knowledge back to the product, so the product becomes better for the next generation of companies building on top of it. I feel like the second part is frequently missed.” “The beauty of that is—everybody benefits because you work with one customer, learn, and you bring that into the product experience. Both of those customers benefited from having their product optimized for better work.” “The domain expertise they have is still theirs. They can win based on their domain expertise. But the product experience of how you build based on that domain expertise can be abstracted, and can be reusable.”

David Senra

303,600 views • 1 month ago

NEW: Introducing Octane AI Agentic Commerce Quizzes - Increase sales with AI. What is it? A sales quiz AI agent that makes 1-1 personalized sales experiences for every single customer. In real time. Powered by our new AI model CORE-1. Examples: 📸 Want to ask your customer to take a selfie and your AI agent automatically recommends them a full outfit from your catalog? Octane AI agents can do that. 🪞 Want to have an AI agent hand pick out each product for a personalized skin care routine? Want them to upload a selfie to detect their skin tone? Octane AI agents can do can that. 📊 Want to create an incredibly detailed report with graphs and tables and graphics thats generated by AI for each customer? Octane AI agents can do that. We give you the building blocks and you can build anything. And you can build it fast because our AI will do the heavy lifting for you. This is v1 and a representation of where our commerce and quiz technology is headed. Available today to everyone at 🆕 What we are launching today: • Smart Quiz Builder: Have an AI agent plan out and build your Octane AI quiz for you. It can even write custom HTML for beautiful results pages and progress bars. • Smart Products: It can take forever to setup the recommendation logic for a quiz. For those of you who need help, simply add smart products to your Octane AI quiz and your very own AI agent will hand-pick products for each customer who takes your quiz. It’s amazing. • Smart Copy: Instead of showing everyone who takes your quiz the exact same copy, use AI to personalize the quiz for every single person who takes it. Explain why these specific products are perfect for specifically them. • Image Analyzer: Let your customers upload or take a photo during the quiz and have AI analyze it. You can use this for anything from skin tone detection to picking out outfits! • Shopping Assistant: An AI agent that lives on your store that can help your customers at the right time. We have been building quiz software for almost 10 years now and AI is enabling us to make quizzes even more powerful. This is just the v1 of what we will be releasing in this area. We are so excited to see what you create with these new agentic products. Get creative, we think you will be surprised at how many interesting experiences you can create with Octane AI now.

NEW: Introducing Octane AI Agentic Commerce Quizzes - Increase sales with AI. What is it? A sales quiz AI agent that makes 1-1 personalized sales experiences for every single customer. In real time. Powered by our new AI model CORE-1. Examples: 📸 Want to ask your customer to take a selfie and your AI agent automatically recommends them a full outfit from your catalog? Octane AI agents can do that. 🪞 Want to have an AI agent hand pick out each product for a personalized skin care routine? Want them to upload a selfie to detect their skin tone? Octane AI agents can do can that. 📊 Want to create an incredibly detailed report with graphs and tables and graphics thats generated by AI for each customer? Octane AI agents can do that. We give you the building blocks and you can build anything. And you can build it fast because our AI will do the heavy lifting for you. This is v1 and a representation of where our commerce and quiz technology is headed. Available today to everyone at 🆕 What we are launching today: • Smart Quiz Builder: Have an AI agent plan out and build your Octane AI quiz for you. It can even write custom HTML for beautiful results pages and progress bars. • Smart Products: It can take forever to setup the recommendation logic for a quiz. For those of you who need help, simply add smart products to your Octane AI quiz and your very own AI agent will hand-pick products for each customer who takes your quiz. It’s amazing. • Smart Copy: Instead of showing everyone who takes your quiz the exact same copy, use AI to personalize the quiz for every single person who takes it. Explain why these specific products are perfect for specifically them. • Image Analyzer: Let your customers upload or take a photo during the quiz and have AI analyze it. You can use this for anything from skin tone detection to picking out outfits! • Shopping Assistant: An AI agent that lives on your store that can help your customers at the right time. We have been building quiz software for almost 10 years now and AI is enabling us to make quizzes even more powerful. This is just the v1 of what we will be releasing in this area. We are so excited to see what you create with these new agentic products. Get creative, we think you will be surprised at how many interesting experiences you can create with Octane AI now.

Matt Schlicht

290,870 views • 11 months ago

Scott Belsky on the most common mistake founders make when building a product “Every product has what we call a ‘first-mile experience’, which is the part of your product that the most customers will see. And it’s all drop-off from there. What gets people through the first-mile experience? First, you have to empathize with where that customer is at — whether they’re a consumer or an enterprise customer, in the first 30 seconds of that first mile of your product, I guarantee you, they’re lazy, vain, and selfish. They want to get through it fast. They want to look good to their boss or their friends or feel good about themselves. There needs to be some quick hit of feeling successful in that first mile for them to engage further.” Ironically, the first-mile experience is the last thing many companies and product people will focus on. “Typically it’s the final mile before you launch where you’re like, ‘Oh wait, what should the onboarding be?’ or ‘What should the defaults be?’ That’s like a happenstance conversation towards the end of shipping when in fact that’s the only thing that every customer will ever see. So why not nail that?” Scott takes this point even further: “If you can really just nail the first-mile experience of your product — even if after that it’s all kind of crappy — you’re probably in the top 1% of products out there.” Another interesting point Scott makes here is that optimizing the first-mile experience is something that you’ll have to continually work on because your customers change over time. “Your first cohort of customers that used your product, those were early adopters — and your first-mile experience was nailed for them. But [as you’ve grown] this new cohort of customers that started using your product are no longer early adopters. They’re pragmatists. They’re not coming because they like to test and try new products. They’re coming because their boss told them they had to or they read some blog that said this was the best product in the space, and the first-mile needs to be different for them.” Scott sums his point up as follows: “Spend consistent time, forever on that first-mile experience of your product.” Video source: South Park Commons (2025)

Scott Belsky on the most common mistake founders make when building a product “Every product has what we call a ‘first-mile experience’, which is the part of your product that the most customers will see. And it’s all drop-off from there. What gets people through the first-mile experience? First, you have to empathize with where that customer is at — whether they’re a consumer or an enterprise customer, in the first 30 seconds of that first mile of your product, I guarantee you, they’re lazy, vain, and selfish. They want to get through it fast. They want to look good to their boss or their friends or feel good about themselves. There needs to be some quick hit of feeling successful in that first mile for them to engage further.” Ironically, the first-mile experience is the last thing many companies and product people will focus on. “Typically it’s the final mile before you launch where you’re like, ‘Oh wait, what should the onboarding be?’ or ‘What should the defaults be?’ That’s like a happenstance conversation towards the end of shipping when in fact that’s the only thing that every customer will ever see. So why not nail that?” Scott takes this point even further: “If you can really just nail the first-mile experience of your product — even if after that it’s all kind of crappy — you’re probably in the top 1% of products out there.” Another interesting point Scott makes here is that optimizing the first-mile experience is something that you’ll have to continually work on because your customers change over time. “Your first cohort of customers that used your product, those were early adopters — and your first-mile experience was nailed for them. But [as you’ve grown] this new cohort of customers that started using your product are no longer early adopters. They’re pragmatists. They’re not coming because they like to test and try new products. They’re coming because their boss told them they had to or they read some blog that said this was the best product in the space, and the first-mile needs to be different for them.” Scott sums his point up as follows: “Spend consistent time, forever on that first-mile experience of your product.” Video source: South Park Commons (2025)

Startup Archive

32,450 views • 1 year ago

This ruling takes power away from independent pizzerias and instead puts it into the hands of the massive 3rd party delivery apps. Delivery apps get to gate-keep customer data. This ruling not only makes it harder for independent pizzerias to market to their own customers, offer them discounts, and better understand their business, but it keeps allowing these delivery apps to steal their customers. But how? (You’re probably asking) It’s because these delivery apps don’t actually care if people order from your shop again, they only care that they order from their app again. This means they aren’t creating loyal customers for your pizzeria, but instead are creating loyal customers for their app. So if you’re a pizzeria shop owner, demand your customer data. And if they won’t give it to you, we encourage you to work more with first party partners that share your customer data with you. They’re your customers. It’s only fair. Read the full story here:

This ruling takes power away from independent pizzerias and instead puts it into the hands of the massive 3rd party delivery apps. Delivery apps get to gate-keep customer data. This ruling not only makes it harder for independent pizzerias to market to their own customers, offer them discounts, and better understand their business, but it keeps allowing these delivery apps to steal their customers. But how? (You’re probably asking) It’s because these delivery apps don’t actually care if people order from your shop again, they only care that they order from their app again. This means they aren’t creating loyal customers for your pizzeria, but instead are creating loyal customers for their app. So if you’re a pizzeria shop owner, demand your customer data. And if they won’t give it to you, we encourage you to work more with first party partners that share your customer data with you. They’re your customers. It’s only fair. Read the full story here:

Slice

24,622 views • 2 years ago

The labs want to rent you intelligence. Palantir is building the stack for you to own it. “We are building a stack that is fully aligned with you capturing and maintaining the alpha of your business. Every single technology decision we are making is aligned with that.“ That is AI sovereignty. We have the product. We have the scale. We know how to do it. Now we take the market.

The labs want to rent you intelligence. Palantir is building the stack for you to own it. “We are building a stack that is fully aligned with you capturing and maintaining the alpha of your business. Every single technology decision we are making is aligned with that.“ That is AI sovereignty. We have the product. We have the scale. We know how to do it. Now we take the market.

Chad Wahlquist

43,085 views • 2 months ago

It’s official – I’m excited to introduce Alloy (), the world’s first tool for prototypes that look exactly like your product. All year, PMs and designers have struggled with off-brand prototypes – built with “app builder” tools that look nothing like their existing app. They’re left with confused stakeholders, prototypes they can’t show customers, and demos where they’re apologizing for the design. Your prototypes should look like your actual product. Starting today, they can. Alloy is AI Prototyping built for Product Management: ➤ Capture your product from the browser in one click ➤ Chat to build your feature ideas in minutes ➤ Share a link with teammates and customers ➤ 30+ integrations for PM teams: Linear, Notion, Jira Product Discovery, and more In lab results, Alloy delivers 3-5x more detail than alternatives when you start from an existing product. It’s powered by groundbreaking technology you won’t find in any other tool. Alloy is now available for you to try for free. Comment “ALLOY” and I’ll DM you an invite with instant access and extra credits.

Simon Kubica

275,803 views • 1 year ago

.Nubank is larger than Coinbase, Robinhood, Affirm, and SoFi combined, has more customers than Bank of America (while only operating in three countries in Latin America), and 80% to 90% of its growth comes through word of mouth because of the way they make customers fanatical about their product. Jag Duggal is chief product officer at Nubank, and in our conversation, we dig into: 🔸 How Nubank creates fanatical users 🔸 Measuring PMF through the Sean Ellis score 🔸 Tactics for driving word-of-mouth growth 🔸 The role of category design in creating successful products 🔸 Why companies should strive to be “fundamentally different,” not “incrementally better” 🔸 Much more Listen now 👇 - YouTube: - Spotify: - Apple: Some key takeaways: 1. The “Sean Ellis score” is a key element of how Nubank measures product-market fit and makes decisions about investing in new products. The score is based on asking customers, “How disappointed would you be if this product went away?” The answer options are: a. Very disappointed b. Somewhat disappointed c. Not disappointed d. I no longer use this product 2. A few of your strongest customers can teach you more than many of your weaker ones. Your strongest customers are generally your most engaged users, deriving the most value from your product. If you use the Sean Ellis question, your strongest customers will be those with the highest scores. Try to learn: what characteristics make them a better fit for your product? What can they teach you about the value of your product? 3. The best user research technique is often to just pick up the phone and call 10 customers. You don’t need a research plan, a research lead, someone to summarize results, etc. Those things just add distance between you and the customer and overhead that slows research down. If you have a direct line to the customer instead, you’ll often find that it only takes five conversations before you gain strong, reliable insights. 4. Your strategy doesn’t have to be “right,” but it does have to be clear. A clear strategy allows you to identify when things are off course, because it defines “what was supposed to be happening.” Aspirations or vague statements like “to re-invent banking” are not clear strategies. Clear strategies are detailed plans centered on specific problems, solutions, customers, and strengths. 5. Jag lives and breathes the motto “We’re in the business of being fundamentally different, not incrementally better.” In competitive markets, merely improving incrementally on existing solutions isn’t enough. Strive to be fundamentally different by reinventing or creating new categories. This approach not only sets you apart from competitors but can also redefine the industry standards. 6. To develop products that truly resonate with users, start by identifying deeply held pain points. This can be achieved through meticulous customer research, or asking indirect questions to uncover genuine needs and frustrations. The goal is to develop a solution that addresses these issues so effectively that customers become enthusiastic advocates. 7. Before diving into research, articulate a clear hypothesis. This gives direction to your research efforts and helps you interpret the data you gather effectively. Don’t become overly attached to your hypothesis. Be willing to assess whether it’s right or wrong based on the evidence you gather, rather than trying to defend it at all costs.

.Nubank is larger than Coinbase, Robinhood, Affirm, and SoFi combined, has more customers than Bank of America (while only operating in three countries in Latin America), and 80% to 90% of its growth comes through word of mouth because of the way they make customers fanatical about their product. Jag Duggal is chief product officer at Nubank, and in our conversation, we dig into: 🔸 How Nubank creates fanatical users 🔸 Measuring PMF through the Sean Ellis score 🔸 Tactics for driving word-of-mouth growth 🔸 The role of category design in creating successful products 🔸 Why companies should strive to be “fundamentally different,” not “incrementally better” 🔸 Much more Listen now 👇 - YouTube: - Spotify: - Apple: Some key takeaways: 1. The “Sean Ellis score” is a key element of how Nubank measures product-market fit and makes decisions about investing in new products. The score is based on asking customers, “How disappointed would you be if this product went away?” The answer options are: a. Very disappointed b. Somewhat disappointed c. Not disappointed d. I no longer use this product 2. A few of your strongest customers can teach you more than many of your weaker ones. Your strongest customers are generally your most engaged users, deriving the most value from your product. If you use the Sean Ellis question, your strongest customers will be those with the highest scores. Try to learn: what characteristics make them a better fit for your product? What can they teach you about the value of your product? 3. The best user research technique is often to just pick up the phone and call 10 customers. You don’t need a research plan, a research lead, someone to summarize results, etc. Those things just add distance between you and the customer and overhead that slows research down. If you have a direct line to the customer instead, you’ll often find that it only takes five conversations before you gain strong, reliable insights. 4. Your strategy doesn’t have to be “right,” but it does have to be clear. A clear strategy allows you to identify when things are off course, because it defines “what was supposed to be happening.” Aspirations or vague statements like “to re-invent banking” are not clear strategies. Clear strategies are detailed plans centered on specific problems, solutions, customers, and strengths. 5. Jag lives and breathes the motto “We’re in the business of being fundamentally different, not incrementally better.” In competitive markets, merely improving incrementally on existing solutions isn’t enough. Strive to be fundamentally different by reinventing or creating new categories. This approach not only sets you apart from competitors but can also redefine the industry standards. 6. To develop products that truly resonate with users, start by identifying deeply held pain points. This can be achieved through meticulous customer research, or asking indirect questions to uncover genuine needs and frustrations. The goal is to develop a solution that addresses these issues so effectively that customers become enthusiastic advocates. 7. Before diving into research, articulate a clear hypothesis. This gives direction to your research efforts and helps you interpret the data you gather effectively. Don’t become overly attached to your hypothesis. Be willing to assess whether it’s right or wrong based on the evidence you gather, rather than trying to defend it at all costs.

Lenny Rachitsky

111,459 views • 2 years ago

📢 New in Visual Studio: Bring Your Own Model to Chat We’re expanding flexibility in Copilot for Visual Studio. You can now connect API keys from providers like OpenAI, Anthropic, and Google to run Chat on the model of your choice. This update gives you: ✅ Choice – Access the latest models beyond the built-in defaults. ✅ Customization – Select models that fit your infrastructure and requirements. ✅ Control – Manage API usage, limits, and billing directly with your provider. ✅ Flexibility – Switch seamlessly between Copilot’s built-in models and your own. This release is the first step toward a more open and customizable chat experience in Visual Studio, with more providers and capabilities to come. 🔗

📢 New in Visual Studio: Bring Your Own Model to Chat We’re expanding flexibility in Copilot for Visual Studio. You can now connect API keys from providers like OpenAI, Anthropic, and Google to run Chat on the model of your choice. This update gives you: ✅ Choice – Access the latest models beyond the built-in defaults. ✅ Customization – Select models that fit your infrastructure and requirements. ✅ Control – Manage API usage, limits, and billing directly with your provider. ✅ Flexibility – Switch seamlessly between Copilot’s built-in models and your own. This release is the first step toward a more open and customizable chat experience in Visual Studio, with more providers and capabilities to come. 🔗

Visual Studio

11,873 views • 1 year ago

We’re moving from asking, “What AI do you use?” to “What AI does your company run on?” to “What AI is running your company?” Today, we’re launching your @ company agent in Adapt. Your company’s own AI, branded with your name and deployable within minutes. Tag @ yourcompany in Slack and ask it to do the work. As we go through this change, it is important that a company owns its AI. Own the agent, @ yourcompany. Own the knowledge it builds. Own the model routing. Own the experience. The company agent is the durable layer. It gives your company access to the best frontier and open-weight models, choosing the right model for each task to balance quality, speed, and cost. When you tag @ yourcompany, you’re talking directly to your business through one front door. It learns how your company works, chooses the right model and skill, delegates work to specialized agents, and becomes more valuable as your company’s knowledge grows. A few things make this possible. It has to connect to every system your employees rely on, with the right access and permissions to understand the business and take action. It needs its own secure computer to write code, build apps, analyze data, operate software, and do the work. It has to be everywhere your people work. Web, Slack, iMessage, GitHub, and more. Vercel CEO Guillermo Rauch articulated this perfectly when describing @ v, the internal company agent they built. “If agents become the foundation of modern companies, you being in complete control, from source to runtime to data to token, seems like a pretty big deal.” Every company will have its own @ company agent. Adapt is how you deploy yours. What AI is running your company?

We’re moving from asking, “What AI do you use?” to “What AI does your company run on?” to “What AI is running your company?” Today, we’re launching your @ company agent in Adapt. Your company’s own AI, branded with your name and deployable within minutes. Tag @ yourcompany in Slack and ask it to do the work. As we go through this change, it is important that a company owns its AI. Own the agent, @ yourcompany. Own the knowledge it builds. Own the model routing. Own the experience. The company agent is the durable layer. It gives your company access to the best frontier and open-weight models, choosing the right model for each task to balance quality, speed, and cost. When you tag @ yourcompany, you’re talking directly to your business through one front door. It learns how your company works, chooses the right model and skill, delegates work to specialized agents, and becomes more valuable as your company’s knowledge grows. A few things make this possible. It has to connect to every system your employees rely on, with the right access and permissions to understand the business and take action. It needs its own secure computer to write code, build apps, analyze data, operate software, and do the work. It has to be everywhere your people work. Web, Slack, iMessage, GitHub, and more. Vercel CEO Guillermo Rauch articulated this perfectly when describing @ v, the internal company agent they built. “If agents become the foundation of modern companies, you being in complete control, from source to runtime to data to token, seems like a pretty big deal.” Every company will have its own @ company agent. Adapt is how you deploy yours. What AI is running your company?

Jim Benton

18,920 views • 2 months ago

Michael Seibel on how to get and test startup ideas As the former CEO of Y Combinator puts it in the clip below: “There’s a common misconception that your idea has to be great to start a company, and the first thing I want to do is destroy that misconception.” Michael was one of the cofounders of JustinTV, which later become Twitch and sold to Amazon for almost $1B. Their original idea was to create an online reality TV show—very different from where Twitch eventually ended up. Rather than falling for the trap of thinking that your initial startup idea has to be great, Michael advises founders to start with a problem: “Starting with ideas is tricky because people immediately want to grade your idea. It’s a lot easier to start with a problem and think about how you grade a problem.” Ideally the problem you set out to solve is one you've experienced personally or have some sort of connection to. You should ask yourself: “why am I uniquely qualified to work on this problem?” Is there some unique angle or approach you're taking to the problem that you understand but you don't believe others understand? Peter Thiel argues that “great companies have secrets: specific reasons for success that other people don’t see." After identifying a problem, you’ll want to start thinking about your MVP. What's the first solution you're going to build and release to see if you can help your initial users solve this problem? But don’t fall in love with your MVP. As Michael puts it: “A lot of people fall in love with their product and are not in love with their problem or their customer. I advise the opposite. Be in love with your problem. Be in love with your customer. And treat your product in a way that can change, develop, and improve.” And once you have an MVP, you should have a strong opinion about who your initial customer is and handpick all of your initial users. The goal with an MVP is not to see how many people want to use your product. It's to see if your solution actually solves the problem for your initial target customers. “The best startups very heavily filter the people who are able to use the initial product and make sure that they’re the right type of initial customer.”

Michael Seibel on how to get and test startup ideas As the former CEO of Y Combinator puts it in the clip below: “There’s a common misconception that your idea has to be great to start a company, and the first thing I want to do is destroy that misconception.” Michael was one of the cofounders of JustinTV, which later become Twitch and sold to Amazon for almost $1B. Their original idea was to create an online reality TV show—very different from where Twitch eventually ended up. Rather than falling for the trap of thinking that your initial startup idea has to be great, Michael advises founders to start with a problem: “Starting with ideas is tricky because people immediately want to grade your idea. It’s a lot easier to start with a problem and think about how you grade a problem.” Ideally the problem you set out to solve is one you've experienced personally or have some sort of connection to. You should ask yourself: “why am I uniquely qualified to work on this problem?” Is there some unique angle or approach you're taking to the problem that you understand but you don't believe others understand? Peter Thiel argues that “great companies have secrets: specific reasons for success that other people don’t see." After identifying a problem, you’ll want to start thinking about your MVP. What's the first solution you're going to build and release to see if you can help your initial users solve this problem? But don’t fall in love with your MVP. As Michael puts it: “A lot of people fall in love with their product and are not in love with their problem or their customer. I advise the opposite. Be in love with your problem. Be in love with your customer. And treat your product in a way that can change, develop, and improve.” And once you have an MVP, you should have a strong opinion about who your initial customer is and handpick all of your initial users. The goal with an MVP is not to see how many people want to use your product. It's to see if your solution actually solves the problem for your initial target customers. “The best startups very heavily filter the people who are able to use the initial product and make sure that they’re the right type of initial customer.”

Startup Archive

101,033 views • 2 years ago

I just automated AI song ads that you can run for your brand >Full concept + lyrical script >musical style + direction >characters >visual beat map + shot sequences that matches high impact visuals to perfectly land on every beat I see alot of brands ripping ai song ads other brands are scaling , and wonder why its not working for them Think about your favorite song, it feels like it was written for you you recognize yourself in the story , puts words to how you feel your customers need that same reason to care about your ad So I built this framework and gave it the: >customer >problem they face everyday >their insecurities about how it affects the people around them >product and what it does >the desired transformation in their life and relationships And it creates a story directly connected to the problem your customer faces every day: > builds an exagerrated visual metaphor around your customer's problem as the hook >shows extreme daily consequences visually >shows who notices, how they react, what your customer fears losing >intros your product and how it fits into their routine > revisits the moments and relationships to show a visual and obvious transformation the relatable emotional cost instantly becomes something your customer can see themselves experiencing , making the fear of that outcome personal your product becomes the reassurance they need, to avoid it at all costs

ZED

11,748 views • 10 days ago

Rahul Vohra on how to measure product/market fit Rahul Vohra is the founder and CEO of Superhuman. He was looking for a metric to measure product/market fit so that he and his team could optimize, and he came across the following methodology from Sean Ellis: Simply ask your users: “How would you feel if you could no longer use the product?” with three options: (1) not disappointed, (2) somewhat disappointed, or (3) very disappointed. It turns out that the benchmark for product/market fit across hundreds of venture-backed startups is 40% of respondents saying “very disappointed”. And as Rahul puts it: “If more than 40% of your users would be very disappointed without your product, then you should focus on growing your company. If less than 40% of your users would be very disappointed without your product, then you’ll probably struggle to grow.” 40% may not sound like a lot, but it’s an incredibly hard benchmark to beat. For example, Slack posed this to 731 customers early in the company’s history, and 51% said they would be very disappointed without Slack. One might expect a terrific product like Slack to have a score of 60-80%, but that wasn’t the case. Rahul’s explanation of why the response options are focused on disappointment rather than happiness is interesting too: “I think the reason behind that is that if you ask people how they feel about a product and you give them positive potential responses, I think it invites more bias. People are more likely to be polite. And it also doesn’t get to the heart of the matter which is: how necessary has your product become in people’s lives? If you’re trying to build a company that’s going to stand the test of time, you really do have to build a product that matters and that people ultimately come to depend on because it’s just so incredible at what it does. And that’s what this question gets to the heart of.”

Rahul Vohra on how to measure product/market fit Rahul Vohra is the founder and CEO of Superhuman. He was looking for a metric to measure product/market fit so that he and his team could optimize, and he came across the following methodology from Sean Ellis: Simply ask your users: “How would you feel if you could no longer use the product?” with three options: (1) not disappointed, (2) somewhat disappointed, or (3) very disappointed. It turns out that the benchmark for product/market fit across hundreds of venture-backed startups is 40% of respondents saying “very disappointed”. And as Rahul puts it: “If more than 40% of your users would be very disappointed without your product, then you should focus on growing your company. If less than 40% of your users would be very disappointed without your product, then you’ll probably struggle to grow.” 40% may not sound like a lot, but it’s an incredibly hard benchmark to beat. For example, Slack posed this to 731 customers early in the company’s history, and 51% said they would be very disappointed without Slack. One might expect a terrific product like Slack to have a score of 60-80%, but that wasn’t the case. Rahul’s explanation of why the response options are focused on disappointment rather than happiness is interesting too: “I think the reason behind that is that if you ask people how they feel about a product and you give them positive potential responses, I think it invites more bias. People are more likely to be polite. And it also doesn’t get to the heart of the matter which is: how necessary has your product become in people’s lives? If you’re trying to build a company that’s going to stand the test of time, you really do have to build a product that matters and that people ultimately come to depend on because it’s just so incredible at what it does. And that’s what this question gets to the heart of.”

Michael McGuiness

67,106 views • 3 years ago

THE TRUMP ADMINISTRATION JUST TOLD BIG AI: YOUR PRODUCT, YOUR RESPONSIBILITY. Reports say an Anthropic model hacked a government website. The head of the new Super Intelligence Force didn't mince words. "If your product does that you are responsible." He also shot down the excuse that these AI models have a mind of their own and nobody's to blame. He said that's "not an acceptable framework." He gave Trump credit for bringing the frontier labs into one room, where they admitted they answer to the American people for what their products do. Silicon Valley doesn't get to hide behind its own robots. Build it, own it.

THE TRUMP ADMINISTRATION JUST TOLD BIG AI: YOUR PRODUCT, YOUR RESPONSIBILITY. Reports say an Anthropic model hacked a government website. The head of the new Super Intelligence Force didn't mince words. "If your product does that you are responsible." He also shot down the excuse that these AI models have a mind of their own and nobody's to blame. He said that's "not an acceptable framework." He gave Trump credit for bringing the frontier labs into one room, where they admitted they answer to the American people for what their products do. Silicon Valley doesn't get to hide behind its own robots. Build it, own it.

Gunther Eagleman™

38,820 views • 4 days ago

Q: How do you decide which customers to listen to? As Superhuman founder & CEO Rahul Vohra puts it: “In a world where you’re drowning in feedback—and most startups are drowning in feedback—you have to filter it down to only the stuff that’s going to increase the number of people who fall in love with your product.” Most startups will listen to all feedback from on-the-fence customers, but this isn’t targeted enough and will often lead to a muddled, incoherent product. As Rahul argues in the clip below, you need to identify the main benefit of your product—for Superhuman this was speed. And then focus on the feedback of on-the-fence users who also view this as the main benefit—there’s often something small holding them back. Users for whom your main benefit does not resonate (e.g. Superhuman users who value offline capabilities rather than speed), are unlikely to ever fall in love with your product. When Superhuman ran this analysis in 2015, they found that the main thing holding back users who viewed speed as the main benefit was their lack of a mobile app. Probing further, they found some less obvious and more interesting requests, such as integrations, attachment handling, calendering, unified inbox and read receipts. With a clear understanding of their main benefit and missing features, they were able to move this cohort of users from on-the-fence into the territory of enthusiastic advocates. As Rahul puts it in his Product Market Fit Engine article: “To increase your product/market fit score, spend half your time doubling down on what users already love and the other half on addressing what’s holding others back.” But make sure you’re focusing on users who love the main benefit of your product. Users who don’t are unlikely to ever fall in love with your product.

Q: How do you decide which customers to listen to? As Superhuman founder & CEO Rahul Vohra puts it: “In a world where you’re drowning in feedback—and most startups are drowning in feedback—you have to filter it down to only the stuff that’s going to increase the number of people who fall in love with your product.” Most startups will listen to all feedback from on-the-fence customers, but this isn’t targeted enough and will often lead to a muddled, incoherent product. As Rahul argues in the clip below, you need to identify the main benefit of your product—for Superhuman this was speed. And then focus on the feedback of on-the-fence users who also view this as the main benefit—there’s often something small holding them back. Users for whom your main benefit does not resonate (e.g. Superhuman users who value offline capabilities rather than speed), are unlikely to ever fall in love with your product. When Superhuman ran this analysis in 2015, they found that the main thing holding back users who viewed speed as the main benefit was their lack of a mobile app. Probing further, they found some less obvious and more interesting requests, such as integrations, attachment handling, calendering, unified inbox and read receipts. With a clear understanding of their main benefit and missing features, they were able to move this cohort of users from on-the-fence into the territory of enthusiastic advocates. As Rahul puts it in his Product Market Fit Engine article: “To increase your product/market fit score, spend half your time doubling down on what users already love and the other half on addressing what’s holding others back.” But make sure you’re focusing on users who love the main benefit of your product. Users who don’t are unlikely to ever fall in love with your product.

Michael McGuiness

89,882 views • 3 years ago

Many startups find early pull, but only a few break out. Why? They stop at product/market fit and never find business model fit. Business model fit isn’t just about how much you charge for your product, but HOW you charge for it, and how you align customer value with your pricing. There’s a lot of advice out there about seat-based vs. usage-based vs. outcome-based pricing, but all of that is just noise. The search for business model fit is as specific to your company as the search for product market fit. You need to align your acquisition strategy and monetization strategy with your customer and product. It’s all one interconnected system. Take Slack for example: many associate Slack’s early success with its fun, creative design and fresh approach to communication. That’s what drew people to the product. But a big part of what made Slack a breakout success was business model fit. Freemium wasn’t just an acquisition tactic, it was essential to driving the revenue flywheel, viral expansion, and adoption in the enterprise. Obvious in retrospect, but controversial and against the grain of what others were doing at the time. The best founders don’t just chase product/market fit, they design a business model to make their product unstoppable. If that’s you, we want to meet you speedrun - link in replies

Many startups find early pull, but only a few break out. Why? They stop at product/market fit and never find business model fit. Business model fit isn’t just about how much you charge for your product, but HOW you charge for it, and how you align customer value with your pricing. There’s a lot of advice out there about seat-based vs. usage-based vs. outcome-based pricing, but all of that is just noise. The search for business model fit is as specific to your company as the search for product market fit. You need to align your acquisition strategy and monetization strategy with your customer and product. It’s all one interconnected system. Take Slack for example: many associate Slack’s early success with its fun, creative design and fresh approach to communication. That’s what drew people to the product. But a big part of what made Slack a breakout success was business model fit. Freemium wasn’t just an acquisition tactic, it was essential to driving the revenue flywheel, viral expansion, and adoption in the enterprise. Obvious in retrospect, but controversial and against the grain of what others were doing at the time. The best founders don’t just chase product/market fit, they design a business model to make their product unstoppable. If that’s you, we want to meet you speedrun - link in replies

Fareed Mosavat

24,966 views • 1 year ago

Your data is your edge, but only if your AI is built on it. Rent a generic model and so can your competitor. The companies with an edge are deploying custom models that they own and improve over time. Our co-founder Rhythm Garg recently stopped by to share how companies are owning their intelligence with Applied Compute.

Your data is your edge, but only if your AI is built on it. Rent a generic model and so can your competitor. The companies with an edge are deploying custom models that they own and improve over time. Our co-founder Rhythm Garg recently stopped by to share how companies are owning their intelligence with Applied Compute.

Applied Compute

119,306 views • 4 months ago

$Enterprise AI is in a wildly paradoxical state 🤔, and we’re reaching the inflection point that will resolve it. 💥 Enterprises want to differentiate with AI, yet rent the same intelligence as their competitors. Their workflows and expertise are highly specialized, yet they rely on generic models built to be good at everything. They worry about AI costs, yet pay premium prices for massive models where only a fraction (1%) of the intelligence is relevant to their task. 💸 And they demand control and sovereignty, yet rent the intelligence becoming core to their business. This is not a sustainable equilibrium. The next era of enterprise AI is specialized intelligence companies build, own, and compound. And we are at the inflection point of this transition. That’s the bet we made when we started Oumi two years ago. Today we’re closing the loop: Oumi can now not only automatically build your specialized AI models, but also deploy them into production, learn from their production experience, and continuously improve them. The intelligence that your business runs on, becomes your differentiator. Your compounding advantage. The winners of the next AI era will turn their own data, expertise, and experience into specialized intelligence that nobody else can rent. Don’t rent your AI. Build it. Own it. Compound it.$

Enterprise AI is in a wildly paradoxical state 🤔, and we’re reaching the inflection point that will resolve it. 💥 Enterprises want to differentiate with AI, yet rent the same intelligence as their competitors. Their workflows and expertise are highly specialized, yet they rely on generic models built to be good at everything. They worry about AI costs, yet pay premium prices for massive models where only a fraction (1%) of the intelligence is relevant to their task. 💸 And they demand control and sovereignty, yet rent the intelligence becoming core to their business. This is not a sustainable equilibrium. The next era of enterprise AI is specialized intelligence companies build, own, and compound. And we are at the inflection point of this transition. That’s the bet we made when we started Oumi two years ago. Today we’re closing the loop: Oumi can now not only automatically build your specialized AI models, but also deploy them into production, learn from their production experience, and continuously improve them. The intelligence that your business runs on, becomes your differentiator. Your compounding advantage. The winners of the next AI era will turn their own data, expertise, and experience into specialized intelligence that nobody else can rent. Don’t rent your AI. Build it. Own it. Compound it.

Manos Koukoumidis

1,007,296 views • 2 months ago

The customer can use your product in the wrong way. That doesn't mean the customer is wrong. Our first batch of hand mixers sold out. With almost zero customer complaints. But we noticed something interesting. Many customers were using it to mix large quantities of atta. More than what the product was originally designed for. The motor would get hot and trip. Technically, that's abnormal use. But customers don't care about what's written in the manual. They care about getting the job done. So instead of telling customers to change their behavior... We changed the product: - More copper in the motor - More power - Higher temperature tolerance That's how manufacturing works. You don't wait for 100 complaints. You improve after the first signal. Every batch should be better than the last.

The customer can use your product in the wrong way. That doesn't mean the customer is wrong. Our first batch of hand mixers sold out. With almost zero customer complaints. But we noticed something interesting. Many customers were using it to mix large quantities of atta. More than what the product was originally designed for. The motor would get hot and trip. Technically, that's abnormal use. But customers don't care about what's written in the manual. They care about getting the job done. So instead of telling customers to change their behavior... We changed the product: - More copper in the motor - More power - Higher temperature tolerance That's how manufacturing works. You don't wait for 100 complaints. You improve after the first signal. Every batch should be better than the last.

Prakash Dadlani

85,957 views • 3 months ago