<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI Orchestration on SoloSoft</title><link>https://www.solosoft.dev/tags/ai-orchestration/</link><description>Recent content in AI Orchestration on SoloSoft</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.solosoft.dev/tags/ai-orchestration/index.xml" rel="self" type="application/rss+xml"/><item><title>DeerFlow: ByteDance's Open-Source LLM Workflow Engine</title><link>https://www.solosoft.dev/post/deer-flow-llm-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/post/deer-flow-llm-2026/</guid><description>&lt;p&gt;Building production LLM applications involves far more than making a single API call. Real-world applications chain multiple LLM calls together, combine them with data processing steps, apply conditional logic, handle errors gracefully, and manage state across the pipeline. &lt;strong&gt;DeerFlow&lt;/strong&gt; by ByteDance provides a comprehensive workflow engine for building these complex LLM applications, with a visual pipeline designer that makes the development process accessible and transparent.&lt;/p&gt;
&lt;p&gt;DeerFlow is built on the observation that most LLM applications follow identifiable patterns: retrieve-then-generate (RAG), multi-step reasoning, LLM-as-judge evaluation, and agent-based tool use. Rather than implementing these patterns from scratch each time, DeerFlow provides reusable pipeline components that can be wired together both visually and programmatically.&lt;/p&gt;</description></item></channel></rss>