Tag: llm

Build a working LLM-as-judge eval harness for a coding agent in Python: golden tasks, deterministic checks, a rubric judge on Claude Sonnet 4.6, calibration against human labels, and a CI gate that fails the build when scores regress.

Cursor is the best place to plan a refactor. Aider is the best place to execute it from a terminal with cheap models and atomic git commits. This guide shows the exact pipe: dump the Cursor chat to markdown, hand it to Aider as a read-only context file, and run an architect/editor split that finishes the work.

Wire a Microsoft.SemanticKernel 1.75.0 plugin into a hosted BackgroundService on .NET 11 and invoke its KernelFunctions on a PeriodicTimer schedule. Covers DI scopes, [KernelFunction] resolution, prompt-cache-friendly invocation, cancellation, and the lifetime gotchas that bite when you move a plugin off the request path.

Wire AIFunctionFactory.Create, ChatOptions.Tools, and ChatClientBuilder.UseFunctionInvocation in Microsoft.Extensions.AI 10.5 so an IChatClient can call your .NET methods automatically. Covers OpenAI and Azure OpenAI providers, the FunctionInvokingChatClient knobs that actually matter (iteration limits, concurrent calls, approval prompts, error handling), and streaming responses with tools.

Stream Claude responses from an ASP.NET Core 11 minimal API end-to-end: the official Anthropic .NET SDK, TypedResults.ServerSentEvents, SseItem, IAsyncEnumerable, cancellation flow, and the gotchas that buffer your tokens silently. With Claude Sonnet 4.6 and Opus 4.7 examples.

Add prompt caching to a Python or TypeScript Anthropic SDK app, place cache_control breakpoints correctly, and read cache_read_input_tokens and cache_creation_input_tokens to compute a real hit rate. With pricing math for Claude Sonnet 4.6 and Opus 4.7.

Microsoft's free generative AI course for .NET developers ships Version 2, rebuilt for .NET 10 and migrated from Semantic Kernel to Microsoft.Extensions.AI's IChatClient pattern.