Posts tagged with "AI Agents"

The AI agent SDK landscape in 2026 has narrowed to a handful of serious contenders, each with distinct strengths. A working comparison of Claude Agent SDK, LangGraph, AutoGen, Microsoft Agent Framework, and Mastra, with a decision matrix that lets you pick on the criteria that actually matter for your project.

Standard APM was built for HTTP requests and database queries. Agent runs produce a different signal shape: nested decisions, tool calls, hallucination signals, accumulating context. The observability stack has caught up. Here is the production setup that makes agents debuggable.

Agent loops cost 10x to 50x what a chatbot interaction costs; multi-agent systems add another order of magnitude. The cost compounding is structural, not a bug. The cost reduction is structural too. Decomposing where the tokens go and how to bring agent economics back from runaway to acceptable.

Most multi-agent demos collapse in production. The patterns that survive contact with real workloads are smaller in number and more disciplined than the demos suggest. Planner-worker, supervisor-team, critic-reviser, and hierarchical compositions, with the cost and failure tradeoffs that decide which one to pick when.

Browser-based AI agents moved from labs to early production in 2025 and 2026. Anthropic Computer Use, Microsoft Magentic, and OpenAI Operator each take a distinct architectural bet. This is the working comparison for engineers deciding which to deploy and which workloads they actually fit.

A production-shaped guide to designing AI agent tools that the model can actually use without breaking things. Schema choices, idempotency keys, error responses the model can act on, granularity tradeoffs, versioning, and the patterns that separate demo-quality tools from ones that hold up in real workloads.

A deep dive into Microsoft Entra Agent ID, the control plane for AI agent identity in 2026. Covers identity blueprints, attended and unattended authentication, tool-level RBAC, conditional access, OBO flows across multi-agent systems, and the audit logging that satisfies DORA, NIS2, and AI Act obligations.

The capability spectrum from stateless LLM to multi-agent orchestration is one of the most conflated concepts in the 2026 AI market. The distinctions matter. They change architecture, they change cost by an order of magnitude, and under the EU AI Act they change compliance posture.

Classic RAG hits a ceiling when questions require multi-hop reasoning or query refinement. Agentic RAG — treating retrieval as a tool, decomposing queries, adding self-correction loops — routinely wins where classic RAG plateaus.

One year after MCP shipped, this is what adoption actually looks like — server ecosystems, integration patterns, security concerns like tool poisoning and prompt injection, and the open questions heading into 2026.

A year-end, hype-free review of where agentic AI actually shipped in 2025, which patterns graduated from pilot to production, and which still need work before they are safe to trust with consequential decisions.

Microsoft 365 Copilot unifies Chat, Search, Agents, Notebooks, and Create into one secure workflow. Discover how Work IQ, AI-enhanced search, autonomous agents, and integrated content creation eliminate context switching and boost productivity.

Agents need context. Discover Foundry IQ—the knowledge layer connecting AI agents to enterprise data with multi-source RAG orchestration, retrieval steering, dynamic security controls, and agentic RAG delivering 36% higher accuracy than traditional search.

From scientific research to enterprise AI transformation, discover how Microsoft Foundry unifies models from OpenAI, Anthropic, Cohere, Meta, and more into one secure platform. Learn intelligent model routing, cost optimization, and the game-changing Claude integration.

Microsoft Ignite BRK194: Model Context Protocol (MCP) standardizes agent-tool communication across platforms. Azure API Center integration, federated registries, cross-cloud orchestration, and enterprise governance for scalable agentic ecosystems.

Ride the agent revolution with Microsoft Foundry, the enterprise-ready Agent Factory. Build, test, and launch intelligent agents with 1,400+ tools, 11,000+ models, multi-agent orchestration, and seamless Microsoft 365 integration—all with bulletproof security and governance.

Microsoft Ignite BRK116: Deploy AI agents at scale with Azure App Service, AI Foundry, and MCP tools. Built-in observability, governance, security. Hitachi case study shows 73% downtime reduction and 41% cost savings.

Teams with strong DevOps practices are best positioned to harness AI power. Discover how GitHub Copilot and AI agents bring unprecedented speed, scale, and security across the software development lifecycle—from planning to production.