Production AI Workflows & Multi-Agent Blueprints

Headroomlabs' Headroom compresses tool outputs, logs, files, and RAG chunks before they reach the LLM — achieving 20% fewer tokens for coding agents and 60-95% fewer for structured data. Build a LangGraph workflow that wraps any agent pipeline with Headroom compression for instant cost and latency savings.

WebLLM by mlc-ai runs 27B parameter models entirely in-browser via WebGPU. Build a LangGraph agent workflow that processes sensitive data clientside with zero server costs and zero data egress.

Google's Gemini 3.8 Flash Cyber scored 863 points on Hacker News with its cyber-security-first architecture. Build a LangGraph workflow that autonomously scans codebases, enriches CVE data, and generates verified patches.

Meta's Muse Spark 1.3 hit 429 HN points with real-time text-to-image at 512x512 in 0.8 seconds. Build a LangGraph workflow for prompt engineering, iterative refinement, and production visual asset validation.

Agentic web research is replacing manual search-and-copy workflows in enterprises. This workflow builds a production pipeline using Firecrawl for reliable web scraping, LangGraph for multi-stage orchestration, and structured synthesis with source verification. Results: 71 percent faster research cycles with citation-verified outputs.

Most agent architectures are request-response and synchronous. This workflow builds a streaming agent architecture using WebSockets for real-time client push and Kafka for event-driven agent-to-agent communication. Achieves sub-100ms end-to-end latency for real-time agent applications.

Single-vector RAG hits a ceiling at approximately 72 percent answer accuracy. This multi-agent pipeline combines three retrieval agents — vector search, Cross-Encoder reranking, and knowledge graph traversal — with a judge agent that selects the best answer. Achieves 52 percent higher accuracy than single-vector RAG in production benchmarks.

OpenCode, the open-source AI coding agent that exploded on Hacker News with 1274 points, redefines agentic coding workflows. This production playbook covers multi-file task orchestration, sandboxed execution via Docker Sandboxes, token-efficient prompt engineering, and agent monitoring - with complete runnable code.

Head-to-head benchmark: OpenCode sends 7,000 system tokens vs Claude Code's 33,000 - a 79% reduction. Over 500 SWE-bench tasks, OpenCode delivers 57% lower latency and 53% cost savings with only a 3.6pp SWE-bench score gap.

Docker Sandboxes (GA September 2026) bring Firecracker microVM isolation to AI coding agents with 180ms cold start times. This production playbook builds a connection pool manager, sandbox-aware agent runtime, and CI/CD integration pattern with full runnable TypeScript code.

Anthropic shipped Computer Use, Browser Use, and Tool Search Tool to general availability on August 19-20, 2026. This workflow orchestrates a multi-step browser automation pipeline — form filling, data extraction, screenshot analysis — using Tool Search Tool to reduce context consumption by 85% while maintaining full tool library access.

The EU AI Act, India's DPDP Act, and Saudi Arabia's Sovereign AI regulations now mandate data residency for AI training and inference. This workflow deploys specialized CrewAI agents that classify data by jurisdiction, route processing to compliant regions, and maintain audit trails — all executed by Temporal for crash-proof durability.