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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

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Next.js

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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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"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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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….!

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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.

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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.

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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 👇

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425,244 Aufrufe • vor 5 Monaten

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2:20

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:

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22,889 Aufrufe • vor 2 Monaten

Attention all slicers! Not only is MotorSlice out now, a new beta version is available to try out on Steam! This prospective update tweaks the gameplay in order to address some of the main points people struggled with, and to improve game feel overall. Your thoughts on these changes are welcome. Check it out by going to the Steam properties for MotorSlice, the "Game versions & Betas" tab, and selecting the betatest option.
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Attention all slicers! Not only is MotorSlice out now, a new beta version is available to try out on Steam! This prospective update tweaks the gameplay in order to address some of the main points people struggled with, and to improve game feel overall. Your thoughts on these changes are welcome. Check it out by going to the Steam properties for MotorSlice, the "Game versions & Betas" tab, and selecting the betatest option.

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12,087 Aufrufe • vor 1 Monat

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⚠️ PROJECT FOR DREAMERS! The DPR team wants to hear your voices and would like to include fans in an upcoming project! Let's show our appreciation for Christian Yu ❤️‍🩹 "How has DPR IAN helped you through your dark times?" Record your response to this question in a voice message (10-15 secs) and e-mail it to These will be used in future content for DPR. This is not a fan project; it will be coordinated and run by Ian's team. All info will be kept private and any language will be accepted. Please try to submit as soon as possible, especially within the next couple days before Coachella. Thank you!

DPR IAN archive

84,064 Aufrufe • vor 3 Jahren

Today we’re introducing Superhuman Docs, the evolution of Coda (Superhuman Docs) into the best place for teams and AI to work together. I co-founded Coda to reimagine the modern document and enable anyone to make a doc as powerful as an app. Superhuman Docs builds on that mission, and is reimagined for how teams work with AI now. With Superhuman Docs, AI is no longer a solo experience. Docs AI works with you the way a teammate would, with full context of everything your team has built: your data, your briefs, your roadmaps, your connected tools. You can ask it to summarize a sprint, draft a decision record from your meeting notes, or pull a competitor analysis into a new page, and that work stays right where your teammates can pick it up. I’m incredibly proud of the team for bringing Docs to life! There’s so much more we’re launching, including a way to create custom interfaces on top of your data just by describing it. We’re also introducing Superhuman Databases for teams to manage up to 1 million rows, launching Docs MCP to open it up to the AI tools you already use, and debuting a brand new Mac app. We’ve been building toward this moment for a long time, and Docs starts rolling out today. If you’re an existing Coda user, everything you rely on in your docs will remain the same, and if you’re new, now is a great time to jump in.
4:07

Today we’re introducing Superhuman Docs, the evolution of Coda (Superhuman Docs) into the best place for teams and AI to work together. I co-founded Coda to reimagine the modern document and enable anyone to make a doc as powerful as an app. Superhuman Docs builds on that mission, and is reimagined for how teams work with AI now. With Superhuman Docs, AI is no longer a solo experience. Docs AI works with you the way a teammate would, with full context of everything your team has built: your data, your briefs, your roadmaps, your connected tools. You can ask it to summarize a sprint, draft a decision record from your meeting notes, or pull a competitor analysis into a new page, and that work stays right where your teammates can pick it up. I’m incredibly proud of the team for bringing Docs to life! There’s so much more we’re launching, including a way to create custom interfaces on top of your data just by describing it. We’re also introducing Superhuman Databases for teams to manage up to 1 million rows, launching Docs MCP to open it up to the AI tools you already use, and debuting a brand new Mac app. We’ve been building toward this moment for a long time, and Docs starts rolling out today. If you’re an existing Coda user, everything you rely on in your docs will remain the same, and if you’re new, now is a great time to jump in.

Shishir

22,007 Aufrufe • vor 14 Tagen

We've been obsessing a lot about creating the best possible AI support experience Dub.co. And I think we've found the magic formula. The stack: ✦ Mintlify → docs + help articles ✦ Upstash vector → vector search ✦ AI SDK + Claude sonnet → LLM/retrieval ✦ Plain → support infra Here's how it works: We consolidated our docs + help articles on Mintlify (best-in-class docs platform) so all our support content is now in one place. On every push to main, we sync changes to our Upstash Vector DB. We also built a custom chat interface that retrieves content from Upstash Vector and generates responses via AI SDK + Claude sonnet. The best part: The AI agent uses 𝚝𝚘𝚘𝚕() from AI SDK to retrieve the user's workspace / partner data to provide accurate responses. Finally, if the user needs to speak to a human, we generate a 𝚃𝚒𝚌𝚔𝚎𝚝𝚄𝚙𝚕𝚘𝚊𝚍 UI that lets users upload screenshots + add more context, before creating a ticket on Plain. Cherry on top: The chat interface is embeddable, so we're able to embed it both in our Mintlify docs + support portal 👇 Since we launched this, it's been a gamechanger for scaling support – reducing support workload and creating a much better experience for our users. Highly recommend giving this a try!
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We've been obsessing a lot about creating the best possible AI support experience Dub.co. And I think we've found the magic formula. The stack: ✦ Mintlify → docs + help articles ✦ Upstash vector → vector search ✦ AI SDK + Claude sonnet → LLM/retrieval ✦ Plain → support infra Here's how it works: We consolidated our docs + help articles on Mintlify (best-in-class docs platform) so all our support content is now in one place. On every push to main, we sync changes to our Upstash Vector DB. We also built a custom chat interface that retrieves content from Upstash Vector and generates responses via AI SDK + Claude sonnet. The best part: The AI agent uses 𝚝𝚘𝚘𝚕() from AI SDK to retrieve the user's workspace / partner data to provide accurate responses. Finally, if the user needs to speak to a human, we generate a 𝚃𝚒𝚌𝚔𝚎𝚝𝚄𝚙𝚕𝚘𝚊𝚍 UI that lets users upload screenshots + add more context, before creating a ticket on Plain. Cherry on top: The chat interface is embeddable, so we're able to embed it both in our Mintlify docs + support portal 👇 Since we launched this, it's been a gamechanger for scaling support – reducing support workload and creating a much better experience for our users. Highly recommend giving this a try!

Steven Tey

22,654 Aufrufe • vor 4 Monaten

If Trump authorizes the Strategic Crypto Reserve, which it looks like he will… David Sacks ~ the new Ai/Crypto Czar ~ could train these powerful new Ai Agents on the reserve… Which will be mostly XRP, since they want to focus on US based crypto… And these Ai Agents could be commanded to do anything possible to wipe out our $36 trillion dollar national debt… And with the insane new capabilities of these Ai Agents, they can deploy smart contracts, make strategic investments and do all sorts of magic to accomplish what nothing else could match. We have no plan of prayer to get out of this debt by traditional means. The golden age is definitely going to be Ai powered 🔥 🇺🇸 💪
4:54

If Trump authorizes the Strategic Crypto Reserve, which it looks like he will… David Sacks ~ the new Ai/Crypto Czar ~ could train these powerful new Ai Agents on the reserve… Which will be mostly XRP, since they want to focus on US based crypto… And these Ai Agents could be commanded to do anything possible to wipe out our $36 trillion dollar national debt… And with the insane new capabilities of these Ai Agents, they can deploy smart contracts, make strategic investments and do all sorts of magic to accomplish what nothing else could match. We have no plan of prayer to get out of this debt by traditional means. The golden age is definitely going to be Ai powered 🔥 🇺🇸 💪

Jordan Crowder

18,808 Aufrufe • vor 1 Jahr