<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>APIs &amp; SDKs — The Latent Daily</title><description>Model APIs, SDKs and integration patterns.</description><link>https://thelatentdaily.com/</link><language>en-us</language><atom:link href="https://thelatentdaily.com/rss/apis-sdks.xml" rel="self" type="application/rss+xml"/><item><title>Learning path for developers who want to build with LLMs</title><link>https://thelatentdaily.com/articles/learning-path-for-developers-building-with-llms/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/learning-path-for-developers-building-with-llms/</guid><description>From your first API call to retrieval, tool use, evaluation and deployment: an ordered path for software developers moving into AI engineering.</description><pubDate>Sun, 18 Oct 2026 05:39:00 GMT</pubDate><category>Courses &amp; Learning Paths</category><category>courses</category><category>learning-path</category><category>developers</category><category>llms</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Model deprecations explained: what happens when an AI model is retired</title><link>https://thelatentdaily.com/articles/ai-model-deprecations-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/ai-model-deprecations-explained/</guid><description>AI providers regularly retire older models. How deprecation timelines work, what breaks when a model is shut down and how to plan migrations without surprises.</description><pubDate>Sun, 18 Oct 2026 05:00:00 GMT</pubDate><category>Changelogs &amp; Updates</category><category>changelogs</category><category>deprecations</category><category>apis</category><category>developers</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Model Context Protocol (MCP) explained: the &quot;USB-C port&quot; for AI tools</title><link>https://thelatentdaily.com/guides/model-context-protocol-mcp-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/model-context-protocol-mcp-explained/</guid><description>MCP is an open standard for connecting AI assistants to tools and data. How servers, clients and tools work, how to try it, and the security points to know.</description><pubDate>Sun, 18 Oct 2026 04:54:00 GMT</pubDate><category>Agents &amp; Agentic AI</category><category>mcp</category><category>agents</category><category>tool-use</category><category>open-standards</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Your first LLM API call: a step-by-step guide in Python</title><link>https://thelatentdaily.com/guides/first-llm-api-call-python-guide/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/first-llm-api-call-python-guide/</guid><description>Set up an API key safely, send your first request to a language model in Python, understand messages, tokens and parameters, and handle errors and costs.</description><pubDate>Sun, 18 Oct 2026 04:53:00 GMT</pubDate><category>APIs &amp; SDKs</category><category>apis</category><category>python</category><category>developers</category><category>tutorial</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Structured outputs and function calling: getting reliable data from LLMs</title><link>https://thelatentdaily.com/guides/structured-outputs-and-function-calling-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/structured-outputs-and-function-calling-explained/</guid><description>How to make language models return valid JSON that matches a schema, how function calling works, and how to validate outputs so your application never breaks.</description><pubDate>Sun, 18 Oct 2026 04:52:00 GMT</pubDate><category>APIs &amp; SDKs</category><category>apis</category><category>json</category><category>function-calling</category><category>developers</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How LLM inference serving works: batching, KV cache and vLLM</title><link>https://thelatentdaily.com/guides/how-llm-inference-serving-works-vllm/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/how-llm-inference-serving-works-vllm/</guid><description>What happens when a server answers thousands of LLM requests: prefill and decode, the KV cache, continuous batching, PagedAttention and the metrics that matter.</description><pubDate>Sun, 18 Oct 2026 04:45:00 GMT</pubDate><category>MLOps &amp; Infrastructure</category><category>inference</category><category>vllm</category><category>mlops</category><category>gpus</category><author>dario_admin@resolvia-crm.tech</author></item></channel></rss>