<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Sudharsan Balaji Vijayakumar — Field Notes</title><description>Technical Program Manager with a decade across solution, project, and product delivery — PLM is my domain, not my ceiling.</description><link>https://sudharsanbalaji.com/</link><language>en</language><item><title>Think in Systems. Transform with Purpose</title><link>https://sudharsanbalaji.com/blog/think-in-systems-transform-with-purpose/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/think-in-systems-transform-with-purpose/</guid><description>Many digital transformations stall before a single tool is bought, and not because of the technology. Six steps for thinking in systems and bringing people along, plus what a transformation really needs.</description><pubDate>Sat, 03 Oct 2026 00:00:00 GMT</pubDate><category>Business</category><category>digital transformation</category><category>systems thinking</category><category>change management</category><category>strategy</category></item><item><title>Measuring an AI System, Stage by Stage</title><link>https://sudharsanbalaji.com/blog/evaluation-metrics-by-stage/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/evaluation-metrics-by-stage/</guid><description>There is no single score for an AI system. What you measure changes four times between choosing a model and running one in production — what an eval actually is, which metrics earn their place at each stage, and why the governance ones belong on the same schedule.</description><pubDate>Sat, 05 Sep 2026 00:00:00 GMT</pubDate><category>AI</category><category>evals</category><category>metrics</category><category>responsible AI</category><category>learning notes</category></item><item><title>From an Open-Ended Problem to a Shipped Solution</title><link>https://sudharsanbalaji.com/blog/from-open-ended-problem-to-production/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/from-open-ended-problem-to-production/</guid><description>Building an agent is the easy half. The hard half is choosing what to build and closing a vague business problem into a bounded one — with TOSCAR — before a single prompt gets written. Then the four stages that follow.</description><pubDate>Sat, 05 Sep 2026 00:00:00 GMT</pubDate><category>Business</category><category>agents</category><category>product management</category><category>problem framing</category><category>learning notes</category></item><item><title>RAG Isn&apos;t Training — It&apos;s What You Put In Front of the Model</title><link>https://sudharsanbalaji.com/blog/how-rag-works-with-an-example/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/how-rag-works-with-an-example/</guid><description>Retrieval-augmented generation changes nothing about the model — it changes what the model is looking at when it answers. The mechanism, worked end to end on one real question.</description><pubDate>Sat, 05 Sep 2026 00:00:00 GMT</pubDate><category>AI</category><category>RAG</category><category>retrieval</category><category>agents</category><category>learning notes</category></item><item><title>A Framework for Building Agents That Don&apos;t Fall Over</title><link>https://sudharsanbalaji.com/blog/a-framework-for-building-agents/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/a-framework-for-building-agents/</guid><description>Six parts every working agent has, whether or not the team building it named them. A practical structure for scoping, building, and containing an agent — before the demo becomes a product.</description><pubDate>Thu, 03 Sep 2026 00:00:00 GMT</pubDate><category>AI</category><category>agents</category><category>frameworks</category><category>product</category><category>learning notes</category></item><item><title>MCP: The Boring Standard That Makes AI Tool Use Maintainable</title><link>https://sudharsanbalaji.com/blog/model-context-protocol-explained-with-an-example/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/model-context-protocol-explained-with-an-example/</guid><description>Every AI product used to write its own tool-calling glue. Here is what the Model Context Protocol actually is, what a server exposes, and one small server walked through end to end.</description><pubDate>Tue, 01 Sep 2026 00:00:00 GMT</pubDate><category>AI</category><category>MCP</category><category>agents</category><category>tools</category><category>learning notes</category></item><item><title>Workflows, Agentic AI, and Autonomous Agents — and Why RAG Exists</title><link>https://sudharsanbalaji.com/blog/agentic-ai-autonomous-agents-and-rag/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/agentic-ai-autonomous-agents-and-rag/</guid><description>Three terms get used almost interchangeably in AI conversations, and they mean genuinely different things. Here&apos;s the actual distinction, plus why retrieval-augmented generation matters underneath all of them.</description><pubDate>Mon, 31 Aug 2026 00:00:00 GMT</pubDate><category>AI</category><category>agents</category><category>RAG</category><category>fundamentals</category><category>learning notes</category></item><item><title>A Simple n8n Workflow: Form Submission, Logged and Actioned</title><link>https://sudharsanbalaji.com/blog/n8n-workflow-form-to-sheet-to-email/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/n8n-workflow-form-to-sheet-to-email/</guid><description>Not every automation needs a model. A small, real workflow — three fixed steps in n8n — that turns a form submission into a logged record and a sent email, automatically.</description><pubDate>Mon, 31 Aug 2026 00:00:00 GMT</pubDate><category>Business</category><category>automation</category><category>n8n</category><category>workflow</category><category>learning notes</category></item><item><title>What Business and AI Together Look Like: The Value vs. Effort Matrix I Actually Use</title><link>https://sudharsanbalaji.com/blog/pm-discipline-when-ai-is-the-deliverable/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/pm-discipline-when-ai-is-the-deliverable/</guid><description>Most &apos;AI and business&apos; conversations skip the part where you decide what to build first. Here&apos;s a simple value-vs-effort framework for sorting real initiatives from expensive demos.</description><pubDate>Mon, 10 Aug 2026 00:00:00 GMT</pubDate><category>Business</category><category>AI strategy</category><category>prioritization</category><category>product management</category></item><item><title>How Large Language Models Actually Work, for Non-ML People</title><link>https://sudharsanbalaji.com/blog/how-large-language-models-actually-work/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/how-large-language-models-actually-work/</guid><description>A mental model of what&apos;s happening inside an LLM, written for someone who needs a clear picture without an ML background — not a machine learning course.</description><pubDate>Wed, 15 Jul 2026 00:00:00 GMT</pubDate><category>AI</category><category>fundamentals</category><category>LLMs</category><category>learning notes</category></item><item><title>Prompting Techniques That Actually Move the Needle</title><link>https://sudharsanbalaji.com/blog/prompting-techniques-that-actually-help/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/prompting-techniques-that-actually-help/</guid><description>Not a list of magic words. A short, practical set of prompting patterns that consistently produce better output, and why each one works the way it does.</description><pubDate>Sun, 28 Jun 2026 00:00:00 GMT</pubDate><category>AI</category><category>prompting</category><category>practical</category><category>learning notes</category></item><item><title>A Short History of AI, for People Who Skipped the Hype Cycles</title><link>https://sudharsanbalaji.com/blog/a-short-history-of-ai/</link><guid isPermaLink="true">https://sudharsanbalaji.com/blog/a-short-history-of-ai/</guid><description>What the word &apos;AI&apos; actually contains — machine learning, deep learning, generative AI and LLMs are nested, not synonyms — and the short version of how the field moved from the outer ring to the inner one.</description><pubDate>Fri, 05 Jun 2026 00:00:00 GMT</pubDate><category>AI</category><category>fundamentals</category><category>history</category><category>machine learning</category><category>learning notes</category></item></channel></rss>