Topic
Cost
3 guides on Cost.
What a completed task costs, rather than what a token costs. Caching, counting, and the input-side growth that nobody notices until it arrives on an invoice several weeks later.
Caching LLM Responses in .NET
LLM calls are slow and cost money. Add caching to your .NET AI app — response caching and prompt caching — to cut latency and spend without losing quality.
How to Count Tokens in C#
Tokens drive LLM cost and context limits. How to count tokens in C# with a tokenizer, estimate cost before a call, and keep prompts under the model's limit.
Cost Control for Production AI Agents in .NET
AI agent bills scale with usage and can surprise you. Practical techniques for controlling token spend in .NET agents: right-sizing, caching, context trimming, and budgets.