Make AG-UI events drive UI state, not assistant prose
Reduce structured AG-UI events into frontend state instead of parsing generated text to control application components.
Ai-Engineering
Version prompts, models, datasets, and evaluation results together
Keep every evaluation result tied to the exact prompt, model identities, dataset, evaluator, and configuration that produced it.
Provider Independence from Day One
A C# implementation for keeping provider coupling at explicit boundaries while making model capabilities and provider-specific behavior visible.
Retries Are Not a Recovery Strategy
Why bounded retries help with transient faults but cannot resolve unknown outcomes, partial workflows, or duplicated side effects in AI systems.
Separate ingestion health from retrieval readiness
A failed ingestion run should not stop retrieval while an accepted index remains queryable and eligible to serve.
Cap tool-call loops explicitly
Set a hard iteration limit on automatic function invocation and treat hitting it as an explicit application outcome.
Embeddings in .NET
How to generate text embeddings with Microsoft.Extensions.AI and keep the model, dimensions, comparison metric, and indexing behavior compatible.
What Happens When Your AI Feature Fails?
A practical way to identify failure modes, choose explicit application behavior, and test an AI feature before its successful path hides the hard decisions.
Designing an AI Service Layer
How to place model access, prompts, retrieval, tools, and application policy behind a maintainable use-case boundary in a .NET application.
Validate tool arguments at the execution boundary
Treat model-generated tool arguments as untrusted input even when they satisfy the generated schema and bind successfully to the expected C# types.