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Prompt Caching: How to Cut AI API Costs by 80% (Anthropic + OpenAI)
Article

Prompt Caching: How to Cut AI API Costs by 80% (Anthropic + OpenAI)

A practical guide to prompt caching on Anthropic and OpenAI APIs — how it works, what it saves, and the patterns that maximize cache hit rates in production.

#prompt-caching#anthropic#openai
10 min read
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Function Calling Explained: How AI Models Use Tools (With Real Examples)
Article

Function Calling Explained: How AI Models Use Tools (With Real Examples)

Function calling lets LLMs request specific tool actions rather than just generating text. Here's how it works, when to use it, and practical examples in Python.

#function calling#tool use#agents
6 min read
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Structured Outputs and JSON Mode: Getting Reliable Data From AI
Article

Structured Outputs and JSON Mode: Getting Reliable Data From AI

Asking for JSON in your prompt isn't reliable. Structured outputs with schema enforcement is. Here's how JSON mode and structured outputs work across OpenAI, Anthropic, and Google's APIs.

#structured outputs#JSON mode#API
6 min read
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Model Guide

How to Prompt Mistral: Instruct Format, Efficiency, and API Tips

Mistral's model family balances strong performance with exceptional efficiency. Learn the instruct format, how to use the Mistral API, and when each model in the family fits best.

5 min read
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Agents

Function Calling: Giving LLMs Tools

Function calling is the technical mechanism that lets an LLM invoke external tools. Learn how to define tools, how models decide when to call them, and how to structure results so agents act reliably.

6 min read
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Intermediate

Constrained Generation: Force Structured Output

Learn how to make AI models reliably output JSON, XML, CSV, and other structured formats — essential for integrating AI into real applications and workflows.

4 min read
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