AI Workflows & Agentic Architecture Directory

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.

The EU AI Act enforcement deadline of August 2026 mandates strict data residency for AI training and inference data. This workflow uses Temporal's multi-region orchestration with CrewAI role-based agent isolation to ensure data never leaves jurisdiction boundaries with automated audit trails.

Anthropic shipped Computer Use, Browser Use, and Tool Search to GA on August 19-20, 2026. This workflow orchestrates a multi-step browser automation pipeline using Tool Search to reduce context from 72K to 8.7K tokens — an 85% savings — while maintaining full tool library access.

Gemini 3.7 Flash delivers 340 tok/s at $0.75/1M input tokens — the cost-performance sweet spot for multi-agent coding pipelines. This workflow orchestrates parallel code review, test generation, and security scanning agents using LangGraph state graphs and Google ADK's A2A protocol, delivering 58% latency reduction.

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.

Automate build failure triage, test diagnostic parsing, and deterministic AST patch creation with Microsoft Orchard Recipes and GitHub Actions in 2026.

Route high-throughput enterprise webhooks autonomously using FastMCP tool dispatch and Temporal durable workflows for resilient 2026 event processing.