Agent architecture.
How agentic systems are actually built — loops, gateways, subagents, anatomies. 7 articles total — teasers free, full field guide after a free sign-up.
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Agent-to-Agent Communication
A wire-level field guide to the A2A protocol. Build two Groq-backed agents that have never seen each other's code, plus an orchestrator that resolves their Agent Cards and chains them. Covers JSON-RPC transport, the Task lifecycle, and what v1.0 changes for production.
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Top 5 Agent Architectures You Must Know in 2026
Five control-flow patterns for production agentic systems — from prompt chains to evaluator-optimizer loops. Each as the minimum viable topology of LLM calls, gates, and synthesisers, with trade-offs for when to pick each.
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How to Build an AI Agent
A viral infographic frames agent-building as eight sequential steps. That is a parts list, not an architecture. The defining pattern is a loop — gather context, take action, verify, repeat — wrapped in a workflow-versus-agent decision and disciplined context engineering.
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Agent Stack 2026 v2 — Step-by-step guide
v2 of the Agent Stack guide. In about 4–6 hours, go from an empty folder to a deployed, observable, guarded agent. Eight layers plus danic-ai-os integration, free-tier friendly, usable via MCP in Claude Code and Claude Desktop at the end.
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Which AI architecture should you actually build?
A no-fluff decision tree for Single LLM, Single Agent + Tools, Multi-Agent, Long Context, RAG, and Fine-Tuning — before six months go into the wrong pattern.
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Agentic Workflows in Production: Workflow + Architecture + Non-Negotiables
The 7-step workflow design, the 8 architectural layers, and the 6 non-negotiables for production-grade agentic systems.
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12 Concepts of Agentic AI
The vocabulary every builder, operator, and decision-maker should know — MCP, agent loops, tools, memory, guardrails, and how they fit together.
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