Series · Decision APIs

Decision APIs in .NET

Ten technical investigations of typed decisions, native C# clients, Azure, retrieval, coordination and durable review.

Explore the complete Decision APIs in .NET course, its ten investigations and runnable laboratory source.

  1. Part 1

    Decision APIs in .NET: One Judgment Inside a Working Support Desk

    Give a model one bounded question, which team investigates first, and let C# policy decide the action. A small Agent Framework workflow shows six tickets stopping for six reasons.

    13 min
  2. Part 2

    What a Decision Probability Actually Computes: Logits to Labels

    The same {"department":"technical"} can come from generation, a classifier or label scoring. Work through softmax, candidate sets, multi-token labels and schema masks to see what 0.88 means.

    11 min
  3. Part 3

    Designing a Decision Contract That Preserves Meaning in C#

    Write the rubric first, give choice, predicate and score their own C# types, and reject what a JSON schema cannot see: missing candidates, inconsistent means and duplicate keys.

    14 min
  4. Part 4

    Decision APIs: Derive the Threshold From the Cost of Each Error

    A probability is not an action. Derive automation and review thresholds from error costs, model imperfect reviewers, rank a scarce queue and check what calibration must hold.

    16 min
  5. Part 5

    Native Decision API Clients in C#: Wire Shapes and Stalled Bodies

    Build one C# client for System One and OpenAI Decisions that maps answers by meaning, parses strictly, owns one deadline past the headers and reports every failure as a distinct outcome.

    14 min
  6. Part 6

    Azure Decision APIs: Root, Deployment, Operation and Token Audience

    Microsoft-Decision-1 and Azure OpenAI Decisions use different paths, serializers and token audiences. Bind each to one validated C# profile and keep the token inside the deadline.

    13 min
  7. Part 7

    Local Models and Polish Routing: Evaluate the Errors, Not the Average

    A local model changes where inference runs, not what its scores mean. Evaluate English and Polish pairs, separate agreement from correctness, and see why a margin threshold misleads.

    14 min
  8. Part 8

    RAG That Keeps Its Evidence: Eligibility, Coverage and Licensed Claims

    Filter before Top K, check that the selected set covers every required fact, accept only sentences their citations license, and carry an evidence identity into the next stage.

    12 min
  9. Part 9

    When an Agent Coordinator Has a Real Choice

    Drop selector calls where the dependency graph already decides, keep a checked selector only at a real fork, and charge every attempt so a fluent loop that makes no progress still stops.

    12 min
  10. Part 10

    Human Approval After a Restart: One Reviewed Proposal, One Local Effect

    Bind approval to the exact draft, evidence and policy, resume a pending review from an Agent Framework checkpoint in a new process, and recover a lost receipt without a second effect.

    14 min