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Signal Notes

Signal Notes

By: Nick Creighton
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Dispatches from a 13-site AI empire — what actually works in production, what fails, and what nobody tells you about building with AI.(c) 2026 Aevorn LLC Economics
Episodes
  • Fine-Tune Llama 3 706B Model Locally

    Fine-Tune Llama 3 706B Model Locally
    Jun 15 2026
    The hum of a server. The click of a terminal. Forget the API; this is about running the colossal Llama 3 model yourself. A 706B parameter AI, in-house, offline. Host Nick Creighton maps the frontier of true data privacy, where your internal documents and codebases never leave your control. This is the blueprint for building a private AI data center, covering the hardware reality check and the parallel power of fine-tuning and RAG. Ready to ship it? Listen here. Read the companion post: [Link to blog post]
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    17 mins
  • Fine Tune Llama 3 For Sql Query Generation Tutorial

    Fine Tune Llama 3 For Sql Query Generation Tutorial
    Jun 15 2026
    You trust the AI to write your SQL. It's going to cost you. This week, we fine-tune Llama 3 in an afternoon for under fifty dollars, turning a brittle liability into a precise, private tool. It’s about the gap between a convincing answer and a correct one. The quiet panic when a hallucinated column sends your dashboard off a cliff. We’re moving past generic chatbots and into something that understands your schema, your logic, your stakes. Build the detail-oriented, credible alternative. Full walkthrough in the companion post. The next query it writes could save your morning. Listen.
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    15 mins
  • Llm Evaluation Metrics Explained 2024

    Llm Evaluation Metrics Explained 2024
    Jun 8 2026
    Build Log, with Nick Creighton. This week, the models went quiet. The outputs, once reliable, turned bland and hollow. When your systems falter and hope is your only strategy, it’s time to move past the demo. Nick recounts the death of the "vibe check"—that quick, gut-feeling review that fails when you’re not looking. He spent the last three months building a real validation pipeline, shifting from fragile prompts to a system that actually earns its keep. This is about fighting the silent decay of AI performance, about replacing theory with a foundation that holds while you sleep. For more detail on the validation build, find the companion post [link]. Listen to the full episode.
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    9 mins
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