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Dear past Jenna, I know you're used to dealing with large, complex, legacy codebases riddled with technical debt.
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Dear past Jenna, There will come a point when you wonder whether your career — the one you went to school for (twice) and spent decades honing — is going away.
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I've spent my career helping people build software.
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Everyone uses the word "memory" but I feel like they all mean something different by it.
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I see this pattern a lot in n8n: a developer sets out to build a RAG-powered feature and ends up three days deep configuring (and reconfiguring) text splitters, embedding models, rerankers, and debugging — without a working system to show for it.
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I built an n8n workflow that shows a simple way to use multiple, specialized knowledge bases because sometimes you need knowledge isolation between clients, locations, or even products in your RAG workflows.
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You know all that RAG complexity you hate?
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Over the last few weeks, I've been working to build out resources for people to learn more about retrieval-augmented generation (RAG) — and to learn more about it myself.
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Want to prototype and test your Pinecone indexes, right from your IDE?
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Last year, I set a goal for myself to build more demos in Python as a way to learn the language.
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In this video, I show you how to build a python app to chat with your architecture diagrams.
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Over the course of my career I have worked on a number of sprawling software systems.
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This post was inspired by the AWS Game Builder Challenge.
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Have you ever wondered why you can chat with an LLM about how to solve math problems but they struggle with actual mathematical calculations?
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I read to my kid a lot.