<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>ThirdAct Labs Blog</title><description>ThirdAct Labs simplifies and accelerates the transition to the AI era through AI strategy, engineering, and platform solutions.</description><link>https://thirdactlabs.ai/</link><language>en-us</language><ttl>60</ttl><item><title>AI-Native Architecture: An Executive Decision Guide</title><link>https://thirdactlabs.ai/blog/ai-native-architecture-executive-decision-guide/</link><guid isPermaLink="true">https://thirdactlabs.ai/blog/ai-native-architecture-executive-decision-guide/</guid><description>A practical framework for executives on where AI runs, how it accesses enterprise knowledge, when to customize models, and where automation should stop for human review — starting always with the lightest-cost lever that solves the problem.</description><pubDate>Sun, 10 May 2026 00:00:00 GMT</pubDate><category>AI Strategy</category><category>ai architecture</category><category>enterprise ai</category><category>strategy</category><category>rag</category><category>fine-tuning</category><category>agents</category></item><item><title>The Executive&apos;s Guide to RAG for Enterprise AI</title><link>https://thirdactlabs.ai/blog/the-executives-guide-to-rag/</link><guid isPermaLink="true">https://thirdactlabs.ai/blog/the-executives-guide-to-rag/</guid><description>A strategic guide for business leaders on the four evolutionary architectures of RAG — from basic document search to autonomous AI workflows — and how to match the right architecture to the right business problem.</description><pubDate>Wed, 15 Apr 2026 00:00:00 GMT</pubDate><category>AI Engineering</category><category>rag</category></item><item><title>From Heuristics to Abstractions: Toward Structured Prompt Engineering</title><link>https://thirdactlabs.ai/blog/from-heuristics-to-abstractions-towards-structured-prompt-engineering/</link><guid isPermaLink="true">https://thirdactlabs.ai/blog/from-heuristics-to-abstractions-towards-structured-prompt-engineering/</guid><description>Manual prompt engineering doesn&apos;t scale. DSPy offers a structured approach — abstracting prompts into signatures, modularizing LLM behaviors, and optimizing programs with metrics and data rather than intuition.</description><pubDate>Sat, 11 Apr 2026 00:00:00 GMT</pubDate><category>AI Engineering</category><category>prompt-engineering</category><category>dspy</category><category>primer</category><category>ai-frameworks</category></item></channel></rss>