<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>AI &amp; LLM Engineering - Penluma</title><description>Building, evaluating, and shipping with large language models.</description><link>https://penluma.com/</link><item><title>How LLMs Actually Work (And Why It Still Matters)</title><link>https://penluma.com/blog/ai-llm-engineering/01-foundations-how-llms-work-why-these-skills-endure/</link><guid isPermaLink="true">https://penluma.com/blog/ai-llm-engineering/01-foundations-how-llms-work-why-these-skills-endure/</guid><description>Learn how LLMs actually work in plain English - tokens, context windows, temperature, and the durable engineering skills that outlast every model release.</description><pubDate>Sun, 21 Jun 2026 00:00:00 GMT</pubDate><category>AI &amp; LLM Engineering</category></item><item><title>AI Evals: How to Know Your LLM App Actually Works</title><link>https://penluma.com/blog/ai-llm-engineering/02-evaluation-measurement/</link><guid isPermaLink="true">https://penluma.com/blog/ai-llm-engineering/02-evaluation-measurement/</guid><description>Learn how AI evals replace guesswork with repeatable measurement. A plain-language guide to LLM evaluation, graders, LLM-as-a-judge, RAG, and agents.</description><pubDate>Sun, 21 Jun 2026 00:00:00 GMT</pubDate><category>AI &amp; LLM Engineering</category></item><item><title>Context Engineering: How to Feed an LLM the Right Facts</title><link>https://penluma.com/blog/ai-llm-engineering/03-context-engineering-retrieval/</link><guid isPermaLink="true">https://penluma.com/blog/ai-llm-engineering/03-context-engineering-retrieval/</guid><description>Learn context engineering and RAG: why more context hurts, how retrieval works, and the proven stack that makes AI answers accurate and grounded.</description><pubDate>Sun, 21 Jun 2026 00:00:00 GMT</pubDate><category>AI &amp; LLM Engineering</category></item><item><title>AI Agents Explained: From One LLM Call to Multi-Agent Systems</title><link>https://penluma.com/blog/ai-llm-engineering/04-agent-architecture-orchestration/</link><guid isPermaLink="true">https://penluma.com/blog/ai-llm-engineering/04-agent-architecture-orchestration/</guid><description>Learn how AI agents really work: the ReAct loop, tools, workflow patterns, and when to go multi-agent. A clear, practical guide to agent architecture.</description><pubDate>Sun, 21 Jun 2026 00:00:00 GMT</pubDate><category>AI &amp; LLM Engineering</category></item><item><title>When to Use AI (and When Plain Code Wins)</title><link>https://penluma.com/blog/ai-llm-engineering/05-ai-product-judgment/</link><guid isPermaLink="true">https://penluma.com/blog/ai-llm-engineering/05-ai-product-judgment/</guid><description>Most AI products fail before the model is even chosen. Learn when to use AI, when plain code wins, and how to climb the ladder of escalation wisely.</description><pubDate>Sun, 21 Jun 2026 00:00:00 GMT</pubDate><category>AI &amp; LLM Engineering</category></item><item><title>LLM Engineering FAQ: RAG, Agents, Evals, and More</title><link>https://penluma.com/blog/ai-llm-engineering/06-frequently-asked-questions/</link><guid isPermaLink="true">https://penluma.com/blog/ai-llm-engineering/06-frequently-asked-questions/</guid><description>Clear answers to the questions every LLM engineer asks: RAG vs fine-tuning, agents vs workflows, evals, hallucinations, tokens, context windows, and more.</description><pubDate>Sun, 21 Jun 2026 00:00:00 GMT</pubDate><category>AI &amp; LLM Engineering</category></item><item><title>LLM Engineering Cheat Sheet: The Whole Field on One Page</title><link>https://penluma.com/blog/ai-llm-engineering/07-revision-cheat-sheet/</link><guid isPermaLink="true">https://penluma.com/blog/ai-llm-engineering/07-revision-cheat-sheet/</guid><description>A fast, plain-English LLM engineering cheat sheet covering evals, RAG, agents, and judgment - plus a decision table for picking the right technique every time.</description><pubDate>Sun, 21 Jun 2026 00:00:00 GMT</pubDate><category>AI &amp; LLM Engineering</category></item></channel></rss>