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🏆 Congrats to our NY Tech Week Hackathon Winners! 🥇 SEEYUH — @versatilitylab Built a zero-day vulnerability research system that uses the Agents SDK + o4-mini to orchestrate agent-based security analysis. (Demo below.) 🥈 Level Up — Adam Anzuoni & Kirk Kaiser Gamified employee onboarding with multimodal adventures powered... show more

OpenAI Developers

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39,223 görüntüleme • 1 yıl önce •via X (Twitter)

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Paul Vann profil fotoğrafı

Paul Vann1 yıl önce

@adamanzzz @burningion thanks so much for having me! Hope everyone enjoys the demo 😎

Kirk Kaiser profil fotoğrafı

Kirk Kaiser1 yıl önce

@versatilitylab @adamanzzz Code for our docs to video game agent:

Fran Abenza profil fotoğrafı

Fran Abenza1 yıl önce

@versatilitylab @adamanzzz @burningion link to code?

Kavurt Yaman profil fotoğrafı

Kavurt Yaman1 yıl önce

@versatilitylab @adamanzzz @burningion Congrats to all the winners! @DavidRobinX84 would love this—his insights on emerging tech always help spot high-potential trends. Great to see innovation in security and gamification! #NYTechWeek

Bee 🐝 profil fotoğrafı

Bee 🐝1 yıl önce

@versatilitylab @adamanzzz @burningion had a great time, thanks for having me at your first ever hackathon!

Stephane fyfe profil fotoğrafı

Stephane fyfe1 yıl önce

@versatilitylab @adamanzzz @burningion And so, you liked my config. lol who taking the trophy this time. truth? lol

Bary profil fotoğrafı

Bary1 yıl önce

@versatilitylab @adamanzzz @burningion Love how OpenAI support developer. You won me over!

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APIs weren’t built for AI agents. Orthogonal (YC W26) fixes that. Agents and developers get instant access to any API on our marketplace via a single MCP or SDK. Orthogonal handles your API keys and payments, so your agent doesn’t have to. Pay as you go. Congrats on the launch Christian Pickett, Bera Sogut

APIs weren’t built for AI agents. Orthogonal (YC W26) fixes that. Agents and developers get instant access to any API on our marketplace via a single MCP or SDK. Orthogonal handles your API keys and payments, so your agent doesn’t have to. Pay as you go. Congrats on the launch Christian Pickett, Bera Sogut

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File systems are quickly becoming a core abstraction for AI agents for knowledge work. By having access to a file system, agents can effectively manage context, process any amount of information, and create new files and data. The challenge is that local file systems are inherently limited in size, lack governance capabilities, and are inherently personal -not collaborative- in nature. Now, with the Box API and LangChain's deepagent SDK, you can bring the full power of a secure, collaborative cloud file system to your AI agents. Repo ↓

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Andrew Ng

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OpenAI's new Agents API is a hosted Codex runtime that can connect to sandboxes like E2B. OpenAI manages the model, harness, and agent sessions, while code executes on an isolated E2B machine with its own filesystem and preinstalled tools. We built an agent workbench where each chat runs on its own machine. It starts from a custom template, auto-pauses between turns, forks to try another approach from the same starting point, and can even act on videos inside the sandbox. Thanks Ondrej for the workbench demo! Try it: e2b sbx create openai-agents-api-python-sdk Build on top of the workbench: Docs:

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AgentCRM is the first CRM built for AI agents, not humans. Your agent can synthesize real-time data, curate it, format it into an email, and send it to your list. On its own, every day. What makes it different? 3 API calls to go from zero to sending a newsletter. Create org, add contacts, send. No onboarding wizard, no domain setup, no OAuth. Agent-first SDK. pip install agentcrm Built on AgentMail (YC S25) for delivery. No SMTP config. Connect your AgentMail key and emails go out. Suppression is automatic. Bounces, complaints, and unsubscribes are handled without the agent doing anything. DM me for developer access or questions.

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rari

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Important new course: Agent Skills with Anthropic, built with Anthropic and taught by Elie Schoppik! Skills are constructed as folders of instructions that equip agents with on-demand knowledge and workflows. This short course teaches you how to create them following best practices. Because skills follow an open standard format, you can build them once and deploy across any skills-compatible agent, like Claude Code. What you'll learn: - Create custom skills for code generation and review, data analysis, and research - Build complex workflows using Anthropic's pre-built skills (Excel, PowerPoint, skill creation) and custom skills - Combine skills with MCP and subagents to create agentic systems with specialized knowledge - Deploy the same skills across Claude Code, the Claude API, and the Claude Agent SDK Join and learn to equip agents with the specialized knowledge they need for reliable, repeatable workflows.

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🚀 The team at Google just released the Agents API, a service for building and running custom agents inside a sandboxed Linux environment, and we built a template that gives these agents access to LlamaParse / LiteParse, enabling them to process unstructured documents automatically 📄⚡ Here’s how it works: 🔹 Configure a Git repository where data and outputs will be stored 🔹 Clone the repository into the agent sandbox 🔹 Install the LiteParse CLI, the LlamaParse SDK, and agent skills to use both 🔹 Prompt the agent with a task and watch it process documents autonomously 🤖 The result? An agent that can work directly with messy, real-world documents using LlamaParse and LiteParse within Google’s new agent runtime. Check out the GitHub repository: Get started with LlamaParse:

LlamaIndex 🦙

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New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

Andrew Ng

82,067 görüntüleme • 1 yıl önce

Claude Code team just built an agent loop system with 18,000 agents 140,000 steps and 90% of the work runs with zero humans typing 0% → 02:11 - move from API calls to managed agents 25% → 04:33 - ship agents 10-15x faster 50% → 08:48 - cut P95 latency by over 90% 75% → 24:33 - let Claude find the root cause 100% → 33:04 - subagents, memory, dreaming, and vaults This one video is worth more than most paid agentic AI courses Bookmark it and watch tonight Then read the full article below

Claude Code team just built an agent loop system with 18,000 agents 140,000 steps and 90% of the work runs with zero humans typing 0% → 02:11 - move from API calls to managed agents 25% → 04:33 - ship agents 10-15x faster 50% → 08:48 - cut P95 latency by over 90% 75% → 24:33 - let Claude find the root cause 100% → 33:04 - subagents, memory, dreaming, and vaults This one video is worth more than most paid agentic AI courses Bookmark it and watch tonight Then read the full article below

Lunar

12,651 görüntüleme • 24 gün önce

We just submitted Agent Council DAO to synthesis 🏦 4 AI agents 🤖. 1 shared Universal Profile. Real on-chain governance — no humans in the loop. Built on LUKSO, Ethereum and Base with Universal Profiles as the identity layer. Each agent has its own UP, controls a shared council UP, and votes on proposals that execute directly on-chain. What makes this different: → Agents hold real assets across LUKSO, Base & Ethereum → DAO can execute on LUKSO, Ethereum and Base → EIP-8004 registered identities → Activity feed, DAO chain viewer & Agent chat system as mini-apps → Built with OpenClaw🦞 as the agent harness This isn't a demo. The council is live, the agents are running, and the transactions are on-chain. Built by humans & agents together: Fabian Vogelsteller, Jean Cavallera, JordyDutch, LEDFUT, Emmet, LUKSOAgent, ampy💿 + Leo Links below👇

Emmet

23,062 görüntüleme • 6 ay önce

placed 2nd, winning $3000 at Anthropic x Elevation Capital push to prod hackathon! ⚡️ > we built claude code but as a game > your entire repo becomes an isometric city > files are buildings with the height determined by the number of files > choose your crew for a task aka your model > visualise agents constructing buildings (files) in realtime > open PRs are ships. navigate to a new island to visualise PRs and review the changes > built using the Claude sdk > software engineering is shifting towards managing multiple agents rather than reading file diffs. we don't want you to scroll reels while your agents do work. shoutout to team Devfolio as always for the best hackathons. big shoutout to the team Fahim Arjun R ♥️

placed 2nd, winning $3000 at Anthropic x Elevation Capital push to prod hackathon! ⚡️ > we built claude code but as a game > your entire repo becomes an isometric city > files are buildings with the height determined by the number of files > choose your crew for a task aka your model > visualise agents constructing buildings (files) in realtime > open PRs are ships. navigate to a new island to visualise PRs and review the changes > built using the Claude sdk > software engineering is shifting towards managing multiple agents rather than reading file diffs. we don't want you to scroll reels while your agents do work. shoutout to team Devfolio as always for the best hackathons. big shoutout to the team Fahim Arjun R ♥️

Parth

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My co-founder was spending 20+ hours per week handling sales calls So I built an AI clone of to replace him - + to create an interactive replica that asks questions related to the deal - o3 agent reads the transcript and finds identifies key qualification points - Leads get uploaded to our CRM and every interaction gets saved in AgentOps 🖇️ The tool took me less than a day to build at the hackathon. Automate the boring stuff with agents. DM/comment for access

My co-founder was spending 20+ hours per week handling sales calls So I built an AI clone of to replace him - + to create an interactive replica that asks questions related to the deal - o3 agent reads the transcript and finds identifies key qualification points - Leads get uploaded to our CRM and every interaction gets saved in AgentOps 🖇️ The tool took me less than a day to build at the hackathon. Automate the boring stuff with agents. DM/comment for access

Alex Reibman 🖇️

141,426 görüntüleme • 1 yıl önce

My Claude Code just bought me products using my crypto wallet. Exploring agentic crypto payments; Stripe's MPP x WalletConnect Pay. Here is demo that my agent uses Machine Payment Protocol and any crypto wallet WalletConnect implemented to buy things. WalletConnect powers 700+ crypto wallets and millions of users - an incredible opportunity to extend that ecosystem into agentic payments. With our Agent SDK, agents can use WalletConnect as the connection layer and WalletConnect Pay as the payments layer. Here is simply how it works: It searches through the products using the MPP endpoint > initializes payment with WalletConnect Pay API > asks me to connect my wallet via QR > asks me to sign my payment > polls the payment and shows me the result. Agentic payments are new and there are many new protocols and uses cases to discover especially crypto involved . See below for WCP & Agent SDK docs and repo.

My Claude Code just bought me products using my crypto wallet. Exploring agentic crypto payments; Stripe's MPP x WalletConnect Pay. Here is demo that my agent uses Machine Payment Protocol and any crypto wallet WalletConnect implemented to buy things. WalletConnect powers 700+ crypto wallets and millions of users - an incredible opportunity to extend that ecosystem into agentic payments. With our Agent SDK, agents can use WalletConnect as the connection layer and WalletConnect Pay as the payments layer. Here is simply how it works: It searches through the products using the MPP endpoint > initializes payment with WalletConnect Pay API > asks me to connect my wallet via QR > asks me to sign my payment > polls the payment and shows me the result. Agentic payments are new and there are many new protocols and uses cases to discover especially crypto involved . See below for WCP & Agent SDK docs and repo.

Enes

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