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Next.js installs will soon include version-matched docs, giving agents context on new and recently updated APIs. In our evals, this improved success rates by ~20%. Try it out: 𝚗𝚙𝚡 𝚌𝚛𝚎𝚊𝚝𝚎-𝚗𝚎𝚡𝚝-𝚊𝚙𝚙@𝚌𝚊𝚗𝚊𝚛𝚢

Next.js

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125,435 views • 7 months ago •via X (Twitter)

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Also coming up next: s402 SDK To bring on new developers and servers to our platform we will be making a boilerplate/SDK for the ease of integrating s402 payments to their applications. Plus, should be updated and all new bugs are fixed. Feel free to try out an Agent! In our example below we query our BNB Chain memecoin insights tool with our agent. Agents have multi-tool capabilities by the way! Proof it works 👇

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Sora 🔶

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Klaus Schwab's mentor Henry Kissinger actually said this out loud in 1992: "A New World Order will emerge. The only question is whether it will arise out of intellectual and moral insight, and by design, or whether it will be forced on mankind by a series of catastrophes." "That's the challenge of our period, and it makes it—to my mind—one of the most exciting periods in which anybody can live."

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Red Pill Dispenser

195,052 views • 9 months ago

🚨Don't ignore this. Here's how SpaceX will play out $SPCX already dropped 50%. I called that move in advance. Now I'm giving you my new predictions. How it will go: IPO → the top → 10 days → $160 → 20 days → $140 NOW → $110 → 60 days → $90 → 80 days → $70 (bottom) 100 days → $110 → 120 days → $200 → 140 days → $300 (new ATH) I believe $80 to $70 will be our bottom. Only after that will we see the real rally begin. As soon as I start buying $SPCX, I'll post it HERE. Follow and turn on notifications so you don't miss it.

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winkle.

51,092 views • 1 month ago

"AI evals force you into the shoes of your user." I love this clip from (Director at Arize) on why evaluations are the top AI skill to build in 2025. In my new interview, Aman breaks down: - How to write evals like a pro - 5 AI product principles he swears by - How to start practicing evals now Some quotes from Aman: "All PMs will be AI PMs. You'll either build on top of LLM APIs, use models in your backend, or use AI tools to solve problems in your daily work." "The waterfall process of writing a PRD and handing it to designers and engineers is dead. Your dev cycle needs to be much shorter." "Imagine showing up to a meeting with a prototype instead of a PRD. That's the shift PMs will need to make to communicate better in this new AI world." 📌 Watch now:

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Peter Yang

15,973 views • 1 year ago

The new company brain. Context is the soul of your company, I learned today. Since I wrote a book, “Age of Context,” years ago I see that context is what we now call our private data. That data should be stored in a way to let AI agents and humans get more and more use out of it. This is precisely what PromptQL does and here Tanmai Gopal goes deep on how it now is a company brain, or, rather, a wiki that everyone updates and uses.

The new company brain. Context is the soul of your company, I learned today. Since I wrote a book, “Age of Context,” years ago I see that context is what we now call our private data. That data should be stored in a way to let AI agents and humans get more and more use out of it. This is precisely what PromptQL does and here Tanmai Gopal goes deep on how it now is a company brain, or, rather, a wiki that everyone updates and uses.

Robert Scoble

18,341 views • 2 months ago

The ROOTS festival was created by Mahindra Group in Mumbai in 2023 It’s goal was help preserve our cultural heritage by celebrating traditional art forms In particular we wanted to engage young people by re-framing heritage in contemporary formats. After its resounding success we are now giving the festival a new & permanent home at Mahindra University in Hyderabad. It will now be the signature, student run festival of Mahindra University Yesterday was the curtain raiser for its first edition which will take place on November 22nd this year. And the excitement was palpable….!

The ROOTS festival was created by Mahindra Group in Mumbai in 2023 It’s goal was help preserve our cultural heritage by celebrating traditional art forms In particular we wanted to engage young people by re-framing heritage in contemporary formats. After its resounding success we are now giving the festival a new & permanent home at Mahindra University in Hyderabad. It will now be the signature, student run festival of Mahindra University Yesterday was the curtain raiser for its first edition which will take place on November 22nd this year. And the excitement was palpable….!

anand mahindra

39,839 views • 1 year ago

We’re officially a YOUnicorn! 🦄 Excited to share that You.com just raised $100M Series C at a $1.5B valuation, led by Cox Enterprises. We’ve been heads down building the search infrastructure for the AI and agent future. Soon there will be more AI agents using the web than humans, but today's search wasn't built for this. Agents need deep, contextual information from both public web and internal private data to make real decisions. Our web search API delivers the most up-to-date, accurate, and fastest search results for LLMs and agents. Real benchmarks show we consistently outperform the competition on accuracy and speed while staying cost-effective. Today, we’re answering over 1 billion queries every month across enterprises like DuckDuckGo, Windsurf, Harvey, and many others. There is no other startup of recent years at this scale. Grateful to our wonderful employees, customers, partners, and investors who believe in our vision. The agentic era is here - let's build it together. Try our LLM search APIs.

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Richard Socher

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805,542 views • 3 months ago

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Path of Titans

16,422 views • 5 months ago

Today we're introducing Postman Fabric Gateway—an AI-native agent gateway. Here's why it matters: agents will consume APIs at several orders of magnitude beyond traditional apps. Traditional API Gateways are not designed for AI agents. While many legacy vendors have tried to support agentic workloads, Postman customers have been asking us about something that is AI-native and doesn’t have the baggage of pre-AI architecture. Postman Fabric has been designed from the ground-up for agents with support for MCPs, CLIs, as well as APIs - both AI and deterministic APIs. We are building this with a modular architecture as we are still in the early innings of AI and there are many new patterns that are likely to emerge. One thing is certain though, agents are driven by APIs, and you can’t have agent-ready APIs without a purpose-built gateway. Through Postman Fabric, customers will be able to: 1️⃣ Have a single plane to manage all MCP servers - public or private 2️⃣ Expose internal APIs as MCP tools 3️⃣ Centralize SaaS credentials 4️⃣ Govern agent traffic and run policies at a consumer, route, or service level 5️⃣ Deploy on cloud or in a hybrid model We are opening up early access soon - let me know if you are interested in the comments or a DM!

Today we're introducing Postman Fabric Gateway—an AI-native agent gateway. Here's why it matters: agents will consume APIs at several orders of magnitude beyond traditional apps. Traditional API Gateways are not designed for AI agents. While many legacy vendors have tried to support agentic workloads, Postman customers have been asking us about something that is AI-native and doesn’t have the baggage of pre-AI architecture. Postman Fabric has been designed from the ground-up for agents with support for MCPs, CLIs, as well as APIs - both AI and deterministic APIs. We are building this with a modular architecture as we are still in the early innings of AI and there are many new patterns that are likely to emerge. One thing is certain though, agents are driven by APIs, and you can’t have agent-ready APIs without a purpose-built gateway. Through Postman Fabric, customers will be able to: 1️⃣ Have a single plane to manage all MCP servers - public or private 2️⃣ Expose internal APIs as MCP tools 3️⃣ Centralize SaaS credentials 4️⃣ Govern agent traffic and run policies at a consumer, route, or service level 5️⃣ Deploy on cloud or in a hybrid model We are opening up early access soon - let me know if you are interested in the comments or a DM!

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18,188 views • 4 months ago

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Punishing: Gray Raven

255,477 views • 1 month ago

The highest leverage thing you have to optimize for AI agents is their context. If you’re not getting enough out of AI agents, you probably have a context problem. By default the AI model knows absolutely nothing relevant to perform the task successfully. The whole job of context engineering is to prioritize what the model has as information to work with. Small deviations in the goals, instructions, domain understanding, or underlying data you supply the model will lead to wildly different outcomes. This is where you should spend almost all your time and energy in a workflow. We will start to religiously document more of our workflows and business processes, create clearer goals for people and agents, and ensure our tech infra is setup to get AI agents the right information. The lessons are currently being learned the fastest with coding agents, but the same lessons will apply to every field of knowledge work going forward. dex has a great talk on this that’s absolutely worth your time to watch.

The highest leverage thing you have to optimize for AI agents is their context. If you’re not getting enough out of AI agents, you probably have a context problem. By default the AI model knows absolutely nothing relevant to perform the task successfully. The whole job of context engineering is to prioritize what the model has as information to work with. Small deviations in the goals, instructions, domain understanding, or underlying data you supply the model will lead to wildly different outcomes. This is where you should spend almost all your time and energy in a workflow. We will start to religiously document more of our workflows and business processes, create clearer goals for people and agents, and ensure our tech infra is setup to get AI agents the right information. The lessons are currently being learned the fastest with coding agents, but the same lessons will apply to every field of knowledge work going forward. dex has a great talk on this that’s absolutely worth your time to watch.

Aaron Levie

87,086 views • 1 year ago

"I like to move extremely fast, but in order to move fast, you need to have brakes." Up to 200,000 AI agents wake up at Kavak every day. CPO & AI Officer Alejandro Maza says eval quality is what sets the ceiling on speed at that scale: "So to give you a sense of the scale, 96% of all interactions are handled by agents. No humans there. 95% of all transactions are completely handled by agents." "AI is super powerful, and I've seen many companies get this wrong because they try to go slow because they don't have the right brakes. So I thought about it the other way around: how fast can we go? Well, it depends on the quality of our evals." "A good rule of thumb here is we spend about the same amount of engineer time, tokens, and money on building the evals as building the agents." Alejandro Maza

"I like to move extremely fast, but in order to move fast, you need to have brakes." Up to 200,000 AI agents wake up at Kavak every day. CPO & AI Officer Alejandro Maza says eval quality is what sets the ceiling on speed at that scale: "So to give you a sense of the scale, 96% of all interactions are handled by agents. No humans there. 95% of all transactions are completely handled by agents." "AI is super powerful, and I've seen many companies get this wrong because they try to go slow because they don't have the right brakes. So I thought about it the other way around: how fast can we go? Well, it depends on the quality of our evals." "A good rule of thumb here is we spend about the same amount of engineer time, tokens, and money on building the evals as building the agents." Alejandro Maza

a16z

41,467 views • 1 month ago

clickup just mass-obsoleted every AI agent platform here's the thing nobody's talking about: AI doesn't fail because the models are bad. it fails because it has no context. you paste in a prompt. it hallucinates. you blame the tool. but the tool was never the problem. the CONTEXT was. clickup just solved this. their new "super agents" live INSIDE your workspace. they see everything: - your tasks - your docs - your meetings - your conversations - your decisions 100% context. always on. always scraping. this isn't bolted-on AI calling APIs. this is AI that already knows your business. i've been running an AI backend for my agency. the architecture works - but you have to BUILD the context layer. clickup just made that automatic. i already use it. have tons of data there. this is about to be unbelievable. if you're building automations and you're not paying attention to this— you're about to get lapped. playing with it hard over the next 2 days. full deep dive coming. drop "SUPER" and i'll send you the breakdown when it's ready.

clickup just mass-obsoleted every AI agent platform here's the thing nobody's talking about: AI doesn't fail because the models are bad. it fails because it has no context. you paste in a prompt. it hallucinates. you blame the tool. but the tool was never the problem. the CONTEXT was. clickup just solved this. their new "super agents" live INSIDE your workspace. they see everything: - your tasks - your docs - your meetings - your conversations - your decisions 100% context. always on. always scraping. this isn't bolted-on AI calling APIs. this is AI that already knows your business. i've been running an AI backend for my agency. the architecture works - but you have to BUILD the context layer. clickup just made that automatic. i already use it. have tons of data there. this is about to be unbelievable. if you're building automations and you're not paying attention to this— you're about to get lapped. playing with it hard over the next 2 days. full deep dive coming. drop "SUPER" and i'll send you the breakdown when it's ready.

Nozz

20,313 views • 8 months ago

Huge free update coming soon! -^u^- Our 3D customizable now has a CHIBI SLIDER!! 🩷It's so cute and squishy!! This update will include a lot of bug fixes, optimization + fps improvements, preset saving/loading, autosaves, MMD + vowel shape keys, new expressions, and more! ✨ It will be out soon! I've been dealing with a lot of computer problems and nonstop crashing, so that has caused development to slow. I'm investigating the issue and doing my best to work despite it. This project means so much to me, and I'm not going to let some silly problems stop me from working on it! <3

Huge free update coming soon! -^u^- Our 3D customizable now has a CHIBI SLIDER!! 🩷It's so cute and squishy!! This update will include a lot of bug fixes, optimization + fps improvements, preset saving/loading, autosaves, MMD + vowel shape keys, new expressions, and more! ✨ It will be out soon! I've been dealing with a lot of computer problems and nonstop crashing, so that has caused development to slow. I'm investigating the issue and doing my best to work despite it. This project means so much to me, and I'm not going to let some silly problems stop me from working on it! <3

Pastell & Palette🤍 3D Customizable Model!

20,970 views • 1 month ago

SilkAI is live. Try it now: 🔥 The first version of our intelligent web experience is ready for you to explore, directly in your browser, no downloads needed. You can: • Chat with intelligent AI agents • Create and train your own characters • Explore a new layer of interactive AI Built from scratch with love, obsession, and way too many late nights, this is your moment to dive in. And behind the scenes? We’re already working on something wilder: real-world robotics. Talk. Create. Go deep. Try it free. Let SilkAI surprise you.

SilkAI is live. Try it now: 🔥 The first version of our intelligent web experience is ready for you to explore, directly in your browser, no downloads needed. You can: • Chat with intelligent AI agents • Create and train your own characters • Explore a new layer of interactive AI Built from scratch with love, obsession, and way too many late nights, this is your moment to dive in. And behind the scenes? We’re already working on something wilder: real-world robotics. Talk. Create. Go deep. Try it free. Let SilkAI surprise you.

NetVRk

28,908 views • 1 year ago

How many AI agents work at your company? We now have over 3,258 agents working alongside 1,300 humans. The crazy part is these agents were created by EVERY EMPLOYEE at our company... sales reps, marketers, customer support, product, eng. Literally EVERYONE. BUT I'm most surprised by the adoption and value that MANAGERS are getting from agents. I used to think that every IC would become a manager of agents. Now I think that managers will very likely manage WAY more agents than their ICs combined. And managers' agents will manage their ICs' agents - overseeing them for human-in-the-loop interactions. When creating agents, we use 100% context from all of your activity, files edited, tasks and projects worked on, hierarchy, skills, and role information. We build a user-based context model to make agents as relatable as possible to the specific human that we're building for. This means they truly understand the nuances of the work and what "great" looks like - because great is very much in the eye of the beholder. Great is by definition, subjective. This is also why the human ENGAGEMENT loops are SO vital to agent value. The iteration AFTER the agent is onboarded is where the MAGIC happens. This is just like a manager managing an IC in real life... you're giving feedback. In this case, though, agents learn INSTANTLY, and they retain the knowledge perfectly and indefinitely. Even though I've been pushing AI for years now to everyone in our company, this was the first time we had truly end-to-end AI adoption and retention. This kind of AI adoption is wild. But the value we're realizing is truly INSANE. Super Agents outnumber our humans nearly 3 to 1. What if you could 3X your workforce overnight? Watch this video to see how 👇

How many AI agents work at your company? We now have over 3,258 agents working alongside 1,300 humans. The crazy part is these agents were created by EVERY EMPLOYEE at our company... sales reps, marketers, customer support, product, eng. Literally EVERYONE. BUT I'm most surprised by the adoption and value that MANAGERS are getting from agents. I used to think that every IC would become a manager of agents. Now I think that managers will very likely manage WAY more agents than their ICs combined. And managers' agents will manage their ICs' agents - overseeing them for human-in-the-loop interactions. When creating agents, we use 100% context from all of your activity, files edited, tasks and projects worked on, hierarchy, skills, and role information. We build a user-based context model to make agents as relatable as possible to the specific human that we're building for. This means they truly understand the nuances of the work and what "great" looks like - because great is very much in the eye of the beholder. Great is by definition, subjective. This is also why the human ENGAGEMENT loops are SO vital to agent value. The iteration AFTER the agent is onboarded is where the MAGIC happens. This is just like a manager managing an IC in real life... you're giving feedback. In this case, though, agents learn INSTANTLY, and they retain the knowledge perfectly and indefinitely. Even though I've been pushing AI for years now to everyone in our company, this was the first time we had truly end-to-end AI adoption and retention. This kind of AI adoption is wild. But the value we're realizing is truly INSANE. Super Agents outnumber our humans nearly 3 to 1. What if you could 3X your workforce overnight? Watch this video to see how 👇

Zeb Evans

425,244 views • 7 months ago

Alright, this one’s worth your attention if you’re building or deploying agents. Future AGI just open-sourced their entire platform and i don’t mean a trimmed-down version. this is the full stack: UI, backend, simulation engine, evals, optimization loop, observability, guardrails, gateway, docs. all in one repo. Apache 2.0. I’ve been putting it through its paces on production agents, and what stands out isn’t just the breadth it’s the architecture. Most of the current “agent reliability” stack is fragmented. tracing lives in one tool, evals in another, guardrails somewhere else. you end up manually connecting dots, and the agent itself doesn’t really improve you just keep patching prompts and hoping for the best. This flips that model. It’s built as a closed feedback loop: simulate failures → evaluate in real time → detect production issues → learn from them → generate fixes → validate against real traffic → check regressions → redeploy → monitor again And when something new breaks, the loop just runs again. no manual glue. The simulation piece is especially strong. instead of static test cases, it generates adversarial, multi-turn conversations based on how your agent actually behaves basically hunting for the exact scenarios where your system fails confidently. ran a few thousand simulations on our side… caught things we definitely would’ve missed. Evals run fast (sub-50ms) across modalities. not LLM-as-judge trained classifiers. guardrails are built-in, not layered on top. observability gives you step-level visibility into reasoning, cost, latency, quality. But the real shift is the optimization loop. Most tools tell you *what* broke. this system actually fixes it, validates the fix, and ensures nothing else regresses. That’s the missing layer. It’s clearly built with production in mind not a research demo. and the fact that it’s self-hostable makes it even more relevant if you’re running serious workloads. If you’ve been duct-taping together infra around your agents, this is probably the closest thing to a unified system i’ve seen so far. Worth checking out. If you're serious about deploying reliable AI agents, this is worth a look: 👉 You can also try it instantly (no setup) via their cloud version:

Alright, this one’s worth your attention if you’re building or deploying agents. Future AGI just open-sourced their entire platform and i don’t mean a trimmed-down version. this is the full stack: UI, backend, simulation engine, evals, optimization loop, observability, guardrails, gateway, docs. all in one repo. Apache 2.0. I’ve been putting it through its paces on production agents, and what stands out isn’t just the breadth it’s the architecture. Most of the current “agent reliability” stack is fragmented. tracing lives in one tool, evals in another, guardrails somewhere else. you end up manually connecting dots, and the agent itself doesn’t really improve you just keep patching prompts and hoping for the best. This flips that model. It’s built as a closed feedback loop: simulate failures → evaluate in real time → detect production issues → learn from them → generate fixes → validate against real traffic → check regressions → redeploy → monitor again And when something new breaks, the loop just runs again. no manual glue. The simulation piece is especially strong. instead of static test cases, it generates adversarial, multi-turn conversations based on how your agent actually behaves basically hunting for the exact scenarios where your system fails confidently. ran a few thousand simulations on our side… caught things we definitely would’ve missed. Evals run fast (sub-50ms) across modalities. not LLM-as-judge trained classifiers. guardrails are built-in, not layered on top. observability gives you step-level visibility into reasoning, cost, latency, quality. But the real shift is the optimization loop. Most tools tell you what broke. this system actually fixes it, validates the fix, and ensures nothing else regresses. That’s the missing layer. It’s clearly built with production in mind not a research demo. and the fact that it’s self-hostable makes it even more relevant if you’re running serious workloads. If you’ve been duct-taping together infra around your agents, this is probably the closest thing to a unified system i’ve seen so far. Worth checking out. If you're serious about deploying reliable AI agents, this is worth a look: 👉 You can also try it instantly (no setup) via their cloud version:

Aakash Verma

22,915 views • 4 months ago