8 posts about token usage by 6 contributors.
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AI features can be easy to add and surprisingly difficult to debug. A normal API call is fairly simple to follow. A request enters the application, a function runs, and a response comes back. With an AI feature, one user request can involve several model calls, retrieval steps, prompts, tool calls,
Learn how to benchmark AI tool search accuracy across large enterprise tool catalogs by measuring selection accuracy, latency, token usage, and incorrect tool calls.
Compare Claude tool search with static tool loading in Microsoft Foundry and measure tool selection accuracy, latency, token usage, and agent performance.
Benchmark GitHub Copilot agent tool-call retries and measure their impact on compute usage, latency, token consumption, reliability, and overall AI coding performance.
Measure AI agent token waste caused by poor tool descriptions and evaluate tool-selection accuracy, prompt efficiency, latency, token usage, and inference costs.
Learn how to measure and reduce token usage in production LLM applications using prompt optimization, context management, caching, response limits, and monitoring.
In 2025, crypto tokens like Sharp Token are transforming from trading assets to real-use tools powering education, rewards, DAOs, creator economies, and community platforms in the evolving Web3 space.
Learn how to create a .NET console application that streams conversations using the Amazon Bedrock Converse API with the Anthropic Claude 3 Sonnet model. This guide covers setting up your AWS environment, configuring Visual Studio, and using the AWS SDK to handle streaming conversations and model responses.
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