AI Workflows & Agentic Architecture Directory

Training custom AI models used to cost $100K+ in GPU compute. Prime Intellect's integrated stack — Verifiers, 2,500+ community environments, and hosted training — brings that to $120. Here's how Ramp trained a subagent that beats GPT-5.6 Sol.

Agents don't share context. You copy a brief into Claude, paste it into ChatGPT, drop the same .md into Cursor — and watch them drift. OzBrain solves this with a shared brain that every agent reads and writes. Build a workflow that keeps all your agents synchronized.

The MCP community just published the 2026 roadmap with 192 Hacker News points: stateless architecture, OAuth 2.1, MCP Apps, and the path to becoming the universal agent tool standard. Here's what's coming.

Anthropic closes a $10B Series E at $150B valuation — the largest AI funding round of 2026. The capital fuels Claude AgentOS (an enterprise multi-agent platform), a $5B compute expansion across 6 data centers, and the Decart AI acquisition for world-model capabilities.

Agents need custom models trained on their specific tasks. This FastMCP server exposes Prime Intellect's full RL training pipeline — environment creation, hosted training, evaluation, and 1-click deployment — to any MCP-compatible agent.

Munder Difflin wraps your existing CLI agents into an autonomous office of clones that share context, hand off tasks, and work around the clock. Build a production workflow that turns Claude Code, Codex, and Copilot into a coordinated team.

OpenAI launches GPT-5.6 Max with a 10M token context window — 10x larger than GPT-5.6 Sol. The new model targets enterprise agent workloads requiring entire codebase comprehension, with $0.50/M input tokens and native tool-calling support.

Frontier models are generic. Your agents need domain-specific intelligence. Prime Intellect's RL training stack lets you turn any task into a reinforcement learning environment, train custom models on 2,500+ community environments, and deploy with 1-click inference.

Multi-agent systems fail in predictable, expensive ways. We analyzed $2.3M in production failures across 42 enterprise deployments to identify the 7 anti-patterns that burn through token budgets and break systems.

The EU AI Act Phase 2 enforcement begins today: 40% of enterprise AI agents are now classified as high-risk, requiring audit trails, human oversight gates, and real-time monitoring. Non-compliance fines reach 7% of global revenue.

SOC analysts face 10,000+ alerts daily with 94% false positive rates. Autonomous correlation agents map alerts to MITRE ATT&CK techniques in real-time, cluster related events into incidents, and reduce analyst workload by 89% while catching genuine threats 3.2x faster.

Agents need structured data access to manage projects, track tasks, and coordinate workflows. This FastMCP Python server exposes Airtable's full CRUD API to Claude and Cursor, enabling agents to read, create, update, and search records autonomously through the Model Context Protocol.