AI Agent
From tool calling, MCP, memory and RAG to workflows and production deployment.
Why Production Agents Often Look Like State Machines
A reliable workflow can be explicit without being less intelligent.
AGENTMulti-Agent Teams: When Parallelism Actually Helps
A decision framework for deciding whether to split work across agents or keep one controlled workflow.
AGENTBackground Agents Need Human Approval Boundaries
A practical permission model for agents that continue working after the user leaves.
AGENTAgent Evaluation: Task Success Is Only the First Metric
How to evaluate quality, cost, latency, safety and recovery instead of relying on a single pass rate.
AGENTAgent Memory: What Should Be Stored and What Should Expire?
A practical distinction between durable user preferences, business facts and temporary task state.
AGENTGitHub Copilot Coding Agent: The Review Loop Is the Product
Model choice, self-review and security scanning point to a new standard for delegated coding.
AGENTMCP 2026.07: Tasks, Routing and the Next Agent Infrastructure
Why long-running tasks and routable tool connections matter for enterprise agents.
AGENTManaged Agents and Remote MCP: The Integration Layer Gets Serious
A practical look at background execution, remote tools and credential refresh for agent products.
AGENTWhat the Agents API Changes for Production Builders
The practical building blocks behind longer-running, tool-using agents.
AGENTAI Agent Learning Guide: From Tool Calling to MCP
A structured path for learning modern AI agents without getting lost in frameworks.