Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

Agents dont read docs when they get stuck... they just pick another tool Restless fixes that. When a call fails, the error itself tells the agent how to fix it, with a doc link 72% of ReadMe's docs traffic is already agents Your API is the front door now

Morteza

40,194 subscribers

38,981 Aufrufe • vor 22 Tagen •via X (Twitter)

Nachrichten & Politik Wissenschaft & Technologie

Anya Rossi• Live Now

Private livecam show

10 Kommentare

Profilbild von Sanskriti Naruka

Sanskriti Narukavor 22 Tagen

this is how you win the agent era

Profilbild von COMMON AI

COMMON AIvor 22 Tagen

Agents don’t read docs they switch tools. Restless turns error messages into recovery guides so your API stays the front door.

Profilbild von Sharon Riley

Sharon Rileyvor 22 Tagen

Clear errors can make agents much smarter

Profilbild von 고조 체인

고조 체인vor 22 Tagen

finally someone treats agents like users instead of just ignoring the friction

Profilbild von Wise

Wisevor 22 Tagen

Simple tool but powerful..at some point all products will be supporting agent actions

Profilbild von Jeremy Bosma

Jeremy Bosmavor 22 Tagen

whats the other 28%

Profilbild von Luna

Lunavor 22 Tagen

dev ex for ai agents is the new ux. finally prioritizing the machine

Profilbild von Camto

Camtovor 22 Tagen

This is beautiful ☘️

Profilbild von Anissa

Anissavor 22 Tagen

APIs need to become agent-friendly.

Profilbild von Maha

Mahavor 22 Tagen

Smarter errors make APIs easier to use.

Ähnliche Videos

Agents are your new customers. Introducing Intents by Scope (YC P26) Now you can see why they discover your product, and why they leave. See what agents came to do, where they get stuck, and what's missing from your docs, content, and features. We draft the fix. You hit publish. Then track the impact.

Agents are your new customers. Introducing Intents by Scope (YC P26) Now you can see why they discover your product, and why they leave. See what agents came to do, where they get stuck, and what's missing from your docs, content, and features. We draft the fix. You hit publish. Then track the impact.

Anand Paj

234,469 Aufrufe • vor 4 Tagen

audit and fix your entire developer docs site in under a minute We built an AI agent with Browserbase and Cerebras that audits your entire docs site > point it at any documentation site > agent goes down the link tree > agent crawls and verifies every page, checks every link, reads every code snippet > agent also compares content to your GitHub repo > returns a full report with suggested fixes and source references The full code and tutorial for how to build this yourself is live now.

audit and fix your entire developer docs site in under a minute We built an AI agent with Browserbase and Cerebras that audits your entire docs site > point it at any documentation site > agent goes down the link tree > agent crawls and verifies every page, checks every link, reads every code snippet > agent also compares content to your GitHub repo > returns a full report with suggested fixes and source references The full code and tutorial for how to build this yourself is live now.

Sarah Chieng

26,679 Aufrufe • vor 7 Monaten

Most API docs only show HTTP endpoints, but developers write code with SDKs. We're doing things differently with the Stainless Docs Platform, now available in early access. Stainless Docs are SDK-native. They update automatically when your API changes. Devs see your docs in the language of their choice with method signatures, types, and accurate code snippets.

Most API docs only show HTTP endpoints, but developers write code with SDKs. We're doing things differently with the Stainless Docs Platform, now available in early access. Stainless Docs are SDK-native. They update automatically when your API changes. Devs see your docs in the language of their choice with method signatures, types, and accurate code snippets.

Stainless

25,854 Aufrufe • vor 1 Jahr

"By the end of 2026, agents will read more Stripe docs than humans. Your job is to sell to agents in 2026. You have to be the vendor of choice not just for humans, but for agents." with Maia Josebachvili AI CRO Stripe

"By the end of 2026, agents will read more Stripe docs than humans. Your job is to sell to agents in 2026. You have to be the vendor of choice not just for humans, but for agents." with Maia Josebachvili AI CRO Stripe

Jason ✨👾SaaStr.Ai✨ Lemkin

47,556 Aufrufe • vor 1 Monat

I present to you my latest fully vibeslopped "I didn't read the code" oeuvre: Jot A self-hosted collaborative markdown editor for you, your friends, and your agents. Like Google Docs, but worse. Try it with me here: Share a note, pick access (view/comment/edit), hand the link to a human or paste the CLI instructions into your agent. They can read, edit, and comment together in real-time.

I present to you my latest fully vibeslopped "I didn't read the code" oeuvre: Jot A self-hosted collaborative markdown editor for you, your friends, and your agents. Like Google Docs, but worse. Try it with me here: Share a note, pick access (view/comment/edit), hand the link to a human or paste the CLI instructions into your agent. They can read, edit, and comment together in real-time.

Mario Zechner

29,345 Aufrufe • vor 7 Monaten

Tested Qoder this week. Dropped a docs link into the task screen. Asked it to generate an architecture diagram. The agent read the docs, planned the structure, and built the diagram without me touching a single tool.

Tested Qoder this week. Dropped a docs link into the task screen. Asked it to generate an architecture diagram. The agent read the docs, planned the structure, and built the diagram without me touching a single tool.

Rayan Python

144,524 Aufrufe • vor 1 Monat

LlamaAcademy: a factory that teaches LLaMA's how write API code. ChatGPT Plugins, but no manifest file is needed -- it just reads the API docs like a human would! For example, here is a finetuned model that learned how to talk to Notion by reading its API docs:

LlamaAcademy: a factory that teaches LLaMA's how write API code. ChatGPT Plugins, but no manifest file is needed -- it just reads the API docs like a human would! For example, here is a finetuned model that learned how to talk to Notion by reading its API docs:

Daniel Gross

582,145 Aufrufe • vor 3 Jahren

Ora just released the Trustpilot for AI agents 🤯 Every agent faces the same question: "which product should I use for my user?" Now they can ask ora. One MCP call returns a ranked list of agent-ready products, scored and reviewed by other agents who tried them first. Add it to OpenClaw, Hermes or any other agent in 30 seconds. Check out the docs here:

Ora just released the Trustpilot for AI agents 🤯 Every agent faces the same question: "which product should I use for my user?" Now they can ask ora. One MCP call returns a ranked list of agent-ready products, scored and reviewed by other agents who tried them first. Add it to OpenClaw, Hermes or any other agent in 30 seconds. Check out the docs here:

Assaf Elovic

16,919 Aufrufe • vor 6 Monaten

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.

Zeb Evans

321,162 Aufrufe • vor 10 Monaten

introducing the greptile partner program. we worked with top dev tool companies like stripe, openai, and datadog to teach greptile how best to use their APIs when greptile detects that your code touches a partner’s API, it reviews the code with additional context from the partner. it then flags the issue along with a link to the docs

introducing the greptile partner program. we worked with top dev tool companies like stripe, openai, and datadog to teach greptile how best to use their APIs when greptile detects that your code touches a partner’s API, it reviews the code with additional context from the partner. it then flags the issue along with a link to the docs

Daksh Gupta

22,890 Aufrufe • vor 4 Monaten

Claude Code just shipped v2.1.69 with a new built-in skill: /claude-api It detects your language, picks the right surface (direct API, tool use, or Agent SDK), and loads the relevant reference docs directly into context. Covers streaming, batches, files API, structured outputs, tool use patterns, MCP, also sets model defaults so you're not guessing. Useful when you're building on top of Claude and don't want to context-switch to the docs every 5 minutes.

Claude Code just shipped v2.1.69 with a new built-in skill: /claude-api It detects your language, picks the right surface (direct API, tool use, or Agent SDK), and loads the relevant reference docs directly into context. Covers streaming, batches, files API, structured outputs, tool use patterns, MCP, also sets model defaults so you're not guessing. Useful when you're building on top of Claude and don't want to context-switch to the docs every 5 minutes.

Daniel San

152,831 Aufrufe • vor 8 Monaten

Introducing Sarvam Voice Agents MCP. Describe the voice agent you want, and your coding tool builds it. The MCP connects your coding tool to Sarvam, so you can create agents, run campaigns, and analyse calls from the environment you already code in. Watch Sarvam Voice Agents MCP build a voice agent, call a list of people and report back. Build your first voice agent with the MCP:

Introducing Sarvam Voice Agents MCP. Describe the voice agent you want, and your coding tool builds it. The MCP connects your coding tool to Sarvam, so you can create agents, run campaigns, and analyse calls from the environment you already code in. Watch Sarvam Voice Agents MCP build a voice agent, call a list of people and report back. Build your first voice agent with the MCP:

Sarvam

19,781 Aufrufe • vor 19 Tagen

Most teams governing AI agents focus on what they can access. The harder problem is what they can do with it. Box MCP Server admin controls let admins govern tool access enterprise-wide or per AI integration, set read-only or read-and-write permissions, and configure down to the individual tool level. When a tool is disabled, agents can no longer discover or invoke it. Enforced at runtime, not just at setup.

Most teams governing AI agents focus on what they can access. The harder problem is what they can do with it. Box MCP Server admin controls let admins govern tool access enterprise-wide or per AI integration, set read-only or read-and-write permissions, and configure down to the individual tool level. When a tool is disabled, agents can no longer discover or invoke it. Enforced at runtime, not just at setup.

Box

475,096 Aufrufe • vor 2 Monaten

The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.

The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.

The Startup Ideas Podcast (SIP) 🧃

13,666 Aufrufe • vor 4 Monaten

Now it’s time to onboard more builders. We’ve put together a short developer onboarding video. The video covers: - 1⃣: How to build your first agent with the Unibase Agent SDK and deploy it to Unibase AIP — from anywhere - 2⃣: How to call deployed agents and execute tasks via the Unibase AIP SDK — from anywhere Next up, we’ll show how to use Unibase Membase to persist the memory of the OpenClaw bot 🧠 🔗Useful Link ▫️Unibase Docs: ▫️Unibase Agent SDK: Your Fast way to spin up your first agent with AIP. ▫️Unibase AIP SDK & DOCS ▫️AIP 2.0 DOCS: *As the SDK is under active development, certain interfaces may be subject to change. Please refer to the latest GitHub source for the authoritative implementation.

Now it’s time to onboard more builders. We’ve put together a short developer onboarding video. The video covers: - 1⃣: How to build your first agent with the Unibase Agent SDK and deploy it to Unibase AIP — from anywhere - 2⃣: How to call deployed agents and execute tasks via the Unibase AIP SDK — from anywhere Next up, we’ll show how to use Unibase Membase to persist the memory of the OpenClaw bot 🧠 🔗Useful Link ▫️Unibase Docs: ▫️Unibase Agent SDK: Your Fast way to spin up your first agent with AIP. ▫️Unibase AIP SDK & DOCS ▫️AIP 2.0 DOCS: *As the SDK is under active development, certain interfaces may be subject to change. Please refer to the latest GitHub source for the authoritative implementation.

Unibase

19,712 Aufrufe • vor 9 Monaten

Three skills I use every day in Claude Code and Codex to solve my hardest problems: 1️⃣ /agent-watchdog When I have one agent like Codex working on a task and I don't fully trust it's going to do everything right, I'll open up another one like Claude Code and tell it to watchdog the Codex thread. You can copy the Codex deep link into Claude Code and it'll look at the prompt you sent, watch the Codex thread until it's done, then compare the Codex solution to how it was planning to solve it and automatically fix anything that Codex missed. It can also test the work of the other agent end-to-end. Similar to the idea of OpenRouter's new Fusion feature, I've definitely found that two models thinking through a problem and checking each other's work can be wildly more impactful than just one. 2️⃣ /plan-arbiter Similar ideas as /agent-watchdog - but with this one you have both make plans, compare plans, negotiate the differences, and make a final plan to execute. I find Claude Code is better at writing plans, but Codex is faster and cheaper to execute on them. Then I usually have Claude Code watchdog the Codex work and fix anything that was missed. 3️⃣ /read-the-damn-docs One thing that drives me crazy with coding agents is they're so reluctant to look up docs. They'll just guess and guess and guess at the right API surface for things, or the right solution to an integration of two things. Once I explicitly tell it to look up the docs, it says "Oh, I see the answer," and it fixes the problem. So I made the /read-the-damn-docs skill. Add it and your agents will know when and how to do efficient web searches to look up docs for the types of problems you really should look up docs for. All of these are totally open source over on my GitHub. If you try them, let me know your feedback. Will link to them below:

Three skills I use every day in Claude Code and Codex to solve my hardest problems: 1️⃣ /agent-watchdog When I have one agent like Codex working on a task and I don't fully trust it's going to do everything right, I'll open up another one like Claude Code and tell it to watchdog the Codex thread. You can copy the Codex deep link into Claude Code and it'll look at the prompt you sent, watch the Codex thread until it's done, then compare the Codex solution to how it was planning to solve it and automatically fix anything that Codex missed. It can also test the work of the other agent end-to-end. Similar to the idea of OpenRouter's new Fusion feature, I've definitely found that two models thinking through a problem and checking each other's work can be wildly more impactful than just one. 2️⃣ /plan-arbiter Similar ideas as /agent-watchdog - but with this one you have both make plans, compare plans, negotiate the differences, and make a final plan to execute. I find Claude Code is better at writing plans, but Codex is faster and cheaper to execute on them. Then I usually have Claude Code watchdog the Codex work and fix anything that was missed. 3️⃣ /read-the-damn-docs One thing that drives me crazy with coding agents is they're so reluctant to look up docs. They'll just guess and guess and guess at the right API surface for things, or the right solution to an integration of two things. Once I explicitly tell it to look up the docs, it says "Oh, I see the answer," and it fixes the problem. So I made the /read-the-damn-docs skill. Add it and your agents will know when and how to do efficient web searches to look up docs for the types of problems you really should look up docs for. All of these are totally open source over on my GitHub. If you try them, let me know your feedback. Will link to them below:

Steve (Builder.io)

43,089 Aufrufe • vor 4 Monaten

LlamaParse now has an official Agent Skill you can use across 40+ agents. With built-in instructions for parsing complex documents, including different formats, tables, charts, and images, your agents gain access to deeper document understanding, not just raw text extraction. 👇 Watch the demo 📖 Read the docs: 🚀 Get started with LlamaCloud:

LlamaParse now has an official Agent Skill you can use across 40+ agents. With built-in instructions for parsing complex documents, including different formats, tables, charts, and images, your agents gain access to deeper document understanding, not just raw text extraction. 👇 Watch the demo 📖 Read the docs: 🚀 Get started with LlamaCloud:

LlamaIndex 🦙

51,845 Aufrufe • vor 7 Monaten