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It's Wednesday, March 25th: This week, builders can orchestrate multi-agent research pipelines with ByteDance's DeerFlow 2.0, simulate an entire trading firm with TradingAgents' seven-role LLM framework, and go fully offline with Project N.O.M.A.D.'s survival computer that bundles local AI, Wikipedia, and Khan Academy with zero internet required.
Head over to our Events Portal to get the latest on upcoming AI Collective events near you. Search by city, date, or event format, and join thousands of builders at events across 100+ chapters on every continent (except Antarctica, for now).
Find an event in your city using the link below.👇
In Today’s Top Tools, we spotlight some of the most innovative, creative AI apps that we recommend adding to your stack.
🧬 DEERFLOW 2.0: ByteDance's Open-Source SuperAgent That Spawns Its Own Sub-Agents
ByteDance's open-source agent harness that decomposes complex tasks into sandboxed sub-agents, each scoped with dedicated tools, context, and a real file system.
Give it a research question, a codebase, or a content brief, and the lead agent builds a plan, spins up sub-agents inside isolated Docker containers, and coordinates execution across workflows that can run for hours without losing track. It's also model-agnostic and works with Claude, GPT, DeepSeek v3.2, Kimi 2.5, or any OpenAI-compatible API. The community has pushed it well past ByteDance's original research use case into automated report generation, full slide decks, data pipelines, and dashboard builds. It's already reached 40K+ GitHub stars, built on LangGraph.
📈 TradingAgents: A Multi-Agent LLM Framework That Simulates an Entire Trading Firm
A multi-agent LLM framework from Tauric Research (UCLA/MIT) that simulates an entire trading desk by assigning seven specialized roles to AI agents and forcing them to debate before any trade decision is made.
The roster mirrors how institutional desks actually work. Fundamentals, sentiment, technical, and news analysts feed findings to bull and bear researchers who argue opposing sides, then a trader synthesizes the debate and a risk manager reviews against portfolio exposure before anything executes. In the team's testing, this multi-agent debate structure outperformed single-model baselines on cumulative returns, Sharpe ratio, and maximum drawdown. It's fully open-source, supports OpenAI, Anthropic, Google, xAI, OpenRouter, and Ollama for local models, and the interactive CLI lets you select tickers, date ranges, and research depth. It's already at 40K+ GitHub stars, built on LangGraph. Worth emphasizing that this is a research framework, not financial advice.
🌍 Project N.O.M.A.D.: The Offline Survival Computer That Bundles AI, Wikipedia, and Khan Academy
Here's a thought experiment that became real software: what if you lost internet access tomorrow and needed AI, an encyclopedia, a full education platform, maps, and encryption tools, all running on a single machine with zero cloud dependencies? Project N.O.M.A.D. ships all of that in one self-contained system, powered by Docker, designed for situations where connectivity is a luxury.
The local AI layer runs through Ollama with document upload and semantic search via Qdrant, so you can chat with and query your own files without anything leaving your machine. The project has zero built-in telemetry by design, which makes it a fit for field researchers in bandwidth-constrained environments, educators with unreliable connectivity, and privacy-focused developers who want local AI they fully control. It runs on any Debian-based machine, though the project recommends GPU-backed hardware if you want local model performance that's actually usable. It's already at 15K GitHub stars and Apache 2.0 licensed, with a community benchmark leaderboard for comparing hardware builds.
In this section, we feature a few standout opportunities leading AI companies, non-profits, and other organizations. Each role is selected for impact and relevance to our community.
🔬 Work at a Lab / AI Safety
Roles at frontier labs, safety organizations, and research institutions
AI SAFETY FELLOW — Anthropic | San Francisco (Competitive Salary + Equity)
RESEARCH ENGINEER, FRONTIER SAFETY RISK ASSESSMENT — Google DeepMind | London, NYC, SF ($136K–$245K)
PRINCIPAL, SPECIAL PROJECTS — Center for AI Safety | San Francisco ($150K–$250K)
DATA ENGINEER, SAFEGUARDS — Anthropic | London (Competitive Salary + Equity)
SECURITY LEAD, AGENTIC RED TEAM — Google DeepMind | London ($248K–$349K)
🚀 Work in Industry
Roles at funded AI startups and private companies
FOUNDING ML ENGINEER — Unsloth AI | San Francisco ($200K–$500K, 0.3–0.7% equity)
FOUNDING AI/ML ENGINEER — Concourse | New York ($150K–$250K, 0.5–1.5% equity)
STAFF ML/AI ENGINEER — Confido | New York ($300K–$350K, 0.4–0.7% equity)
STAFF AI SYSTEMS ENGINEER — Flock Safety | Remote US ($200K–$240K)
SENIOR SOFTWARE ENGINEER, AGENTIC SYSTEMS — Tavus | San Francisco / Remote ($160K–$250K)
🏛️ Work in AI Policy / Governance
Roles in government, think tanks, NGOs, and policy organizations
SENIOR ANALYST / COUNSEL, AI GOVERNANCE — Future of Privacy Forum | Washington, DC ($115K–$140K)
NATIONAL SECURITY POLICY LEAD — Anthropic | San Francisco (Competitive Salary + Equity)
JUNIOR ASSOCIATE — AI Policy Network | Washington, DC ($55K-$75K)
🗒️ Community Notes
🌁 MiniMax AI Founder Day | A Room Full of Builders in SF
What happens when you put 200+ AI builders in a room during GTC week?
Last Saturday, we partnered with MiniMax to host AI Founder Day in San Francisco. The room was packed wall to wall with founders, engineers, and AI leaders who showed up ready to connect, learn, and build.
The event was led by MiniMax’s cofounder, Yeyi Yun, who shared the company’s vision for AGI, along with a deeper look into how MiniMax is building toward real-world, production-ready AI systems. From live demos of their latest model to a founder panel with leaders across Silicon Valley, the conversations were grounded in real-world building. What stood out most was the room with a strong concentration of builders actively shaping the next wave of AI.
MiniMax is quickly emerging as one of the key players in the space, and we’re excited to continue building alongside teams like this.
If you were there… you know. If you weren’t – we’ll see you at the next one.
Follow MiniMax for more updates:
🤝 AIC x Make.com | Saturday Hackathon (3/28)
The AI Collective San Francisco is teaming up with Make.com for a one-day hackathon at Entrepreneurs First on Folsom St. this Saturday, March 28th. Doors open at 10 AM, teams form by 11, and you'll have four hours to build automation workflows on Make's visual platform before demoing to a panel of six judges.
Note: space is limited and registration requires approval, so apply soon if you want in. Pizza, music, experts on hand to troubleshoot, and a room full of SF builders who like making things move on their own.
Grab your laptop and come build with us this weekend.
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About Noah Frank
Noah is a researcher, innovation strategist, and ex-founder thinking and writing about the future of AI. His work and body of research explores the economics of emerging technology and organizational strategy.
About Joy Dong
Joy is a news editor, writer, and entrepreneur at the forefront of the emerging tech landscape. A former educator turned media strategist, she currently writes TEA, where she demystifies complex systems to make AI and blockchain accessible for all.