Microsoft Agent Framework: Agents and Deterministic Workflows in One Stack

Evidence check: 25 October 2026. Product details reflect the referenced documentation observed at this cutoff; exact plans, prices, regional eligibility and unverified release dates are not claimed. This is an editorial guide, not a hands-on test.

The architecture distinction

Microsoft’s Agent Framework overview describes individual tool-using agents, workflow graphs and integrations. It positions the framework as a successor joining concepts from AutoGen and Semantic Kernel. This matters for architects who previously designed systems around those projects: migration is not equivalent to replacing a package name. Review state handling, middleware, tool contracts and behavioral changes before moving a live process.

When to use an agent

An agent is appropriate when the sequence is not fully known or user interaction is central. A workflow is appropriate when execution order must be controlled and audited. Framework docs explicitly encourage using regular functions when a function will do the job. That is a strong practical default: do not turn deterministic record validation into a chain of model decisions.

End-to-end control

Define narrow tools, an authenticated context and explicit permissions. Use middleware or a service gateway to inspect actions before execution. Capture model and connector versions. Track the process state separately from the conversation, because the latter can be truncated, summarized or misinterpreted. Ensure long-running approvals can survive restarts and that a resumed node will not repeat a side effect.

Deployment and provider boundaries

The overview documents multiple model-provider integration paths; support is not the same as identical feature coverage, data residency or support commitments. Its provider guide also warns that integrating third-party systems can involve different terms and privacy boundaries. Confirm applicable region, runtime, model, plan and exact package version before procurement.

A migration checklist

Catalog existing Semantic Kernel or AutoGen dependencies, authentication schemes, middleware, telemetry hooks and serialized state. Re-run held-out tasks against old and new flows; compare outputs, permissions, failures and cost. Stage the cutover, preserve rollback and do not claim backward compatibility until integration tests pass.

Editorial version note

The official getting-started material carried an August 2026 update in the checked documentation, but that is not a verified initial GA release date. This page deliberately omits a specific GA claim and any unverified fee or quota.

Migrating without losing control

Inventory each legacy AutoGen or Semantic Kernel component: prompts, tool adapters, state stores, conversation data, identity policies, telemetry and error-handling assumptions. Build a compatibility table mapping old workflow behavior to new Framework behavior. Do not assume similar class names imply equal persistence or callback semantics. Write deterministic tests around approved action sequences before attempting any agent migration.

A reviewable deployment trial

Use a limited scenario such as internal knowledge search and draft creation. Pin package versions, model endpoints and authorization paths. Log when the flow pauses, who can resume it and whether interrupted operations replay. Keep a fallback system until the new workflow matches the established baseline on correctness, data isolation, trace coverage and operational failures. Microsoft’s documentation establishes available framework concepts; it does not prove a new stack is cheaper or safer in every enterprise. Regional service support must be verified for the actual tenant and destination.