AI Workflows & Agentic Architecture Directory

Tencent just dropped Hy4-preview: a 770B-parameter Mixture-of-Experts model under Apache 2.0 with 1M-token context. Here is how to deploy it locally with vLLM 0.28.0 and orchestrate a multi-agent workflow that routes tasks across 256 expert shards.

Nvidia paused its $36B AI Compute Partnership program after employees warned the arrangement could invite antitrust scrutiny. Build a multi-cloud GPU routing workflow that insulates your agent fleet from single-vendor dependency.

Faro AI's $37.3M Series B funds infrastructure to cut clinical-trial timelines by 50%. Build a multi-agent workflow that automates structured data extraction, patient-protocol matching, and regulatory dossier assembly.

OpenAI's Astra model is approaching critical cyber capability thresholds. Here are 5 production guardrail patterns that autonomous agent deployments must implement to detect and mitigate emerging cyber risks in real-time.

Stanford HAI's 2026 AI Index reveals 88% organizational adoption and 77.3% agent success rates. Build a compliance monitor that benchmarks your production agents against these industry standards in real-time.

SWE-bench Verified hit 96% in 2026 — up from 60% in 2025. Here is the multi-agent orchestration architecture that achieved it using PydanticAI planners, LangGraph 1.x execution graphs, and specialized code-generation workers.

Apple released the Apple Intelligence Enterprise SDK, enabling Fortune 500 companies to deploy on-device AI agents that run entirely on Apple Silicon — zero cloud dependency, zero data leaving the device, and full GDPR compliance.

Anthropic released Claude Agent Guardrails v2 — a 12-point safety framework for enterprise AI agent deployments with real-time monitoring, automatic shutdown triggers, and compliance audit trails.

AI agents need instant access to web analytics. This FastMCP server exposes Vercel Analytics and Edge Config data to Claude and Cursor, querying 50 million page views in under 3 seconds.

The Agent-to-Agent protocol enables AI agents to discover and communicate across frameworks. We benchmark Google ADK A2A against LangGraph cross-agent messaging on latency, throughput, and reliability.

AI agents need project management access. This FastMCP server exposes Linear issue tracking to Claude and Cursor, autonomously triaging 500 issues per hour with 94% accuracy.

AI agents need live database access. This FastMCP server streams Supabase Realtime changes, invokes Edge Functions, and queries pgvector — giving Claude and Cursor instant access to live application data.