01 Should a team start a new agent workflow with Semantic Kernel or Microsoft Agent Framework?
Microsoft describes Agent Framework as the direct successor to Semantic Kernel's agent framework and AutoGen, with explicit workflows and state management for new agent applications. MetaCTO therefore evaluates Agent Framework first for a greenfield agent or graph workflow. Semantic Kernel can remain the pragmatic choice when an existing .NET, Python, or Java service already relies on its lightweight kernel, plugins, prompts, and function-calling abstractions and the value of migrating does not outweigh the operating risk. The decision should be made against one representative workflow, including approval, recovery, telemetry, and long-term ownership, not from an SDK feature checklist alone.
02 Does Semantic Kernel function calling authorize a model to change a business system?
No. Semantic Kernel can describe plugin functions to a model, marshal selected arguments, and automatically invoke functions, but model selection is not business authorization. MetaCTO registers only the functions needed for the current case, separates reads from writes, validates typed arguments, and rechecks the actor, record version, policy, and approval in trusted application code before any external side effect. A write-capable plugin should also use an idempotency key and return a destination receipt so retries can be reconciled instead of blindly repeated.
03 Which Semantic Kernel filters matter for production controls, and what can they not replace?
Microsoft documents function-invocation, prompt-render, and automatic-function-invocation filters. They can inspect or stop execution, redact or revise a rendered prompt, handle function exceptions, override results, and terminate an automatic function-calling loop. They are useful enforcement and evidence points, but they do not replace destination authorization, durable workflow state, or human approval for consequential actions. MetaCTO keeps each filter focused, tests the complete pipeline, and avoids depending on implicit filter order because Microsoft notes that dependency-injected filter ordering is not guaranteed.
04 Can Semantic Kernel own a multi-day process, human approval, and failure recovery by itself?
It should not be the only durable owner for a critical operational process. Microsoft's Semantic Kernel Process Framework documentation still labels that framework experimental, while the kernel itself is a lightweight service-and-plugin container whose plugin collection is mutable. MetaCTO stores the case state, deadlines, approval decisions, action keys, and reconciliation status in an application database or proven durable orchestrator. The kernel can be created per use with the approved plugin set, then safely reconstructed after a timeout or deployment without losing the authoritative process record.
05 How should a team observe Semantic Kernel without leaking operational data?
Semantic Kernel emits OpenTelemetry-compatible logs, metrics, and distributed traces in supported SDKs; Microsoft currently documents this observability for .NET and Python, not Java, and notes that function arguments and results can appear at debug level. MetaCTO correlates model and function spans to a non-sensitive case ID, disables sensitive payload capture by default, and applies explicit access, redaction, sampling, and retention rules before enabling deeper traces. Runtime telemetry is then paired with business signals such as approval rate, exception reason, destination receipt, and final case outcome so a technically successful call is not mistaken for a successful operation.