Changelog Master Feed Programming with LLMs (Changelog Interviews #629)
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Feb 19, 2025 David Crawshaw, CTO and co-founder of Tailscale, shares his insights on integrating Large Language Models (LLMs) into programming workflows. He highlights how LLMs enhance productivity and discusses the evolving landscape of tools like Augment AI for more tailored coding assistance. The conversation also covers the role of networking for LLM deployment, the intricacies of managing machine networks, and the balance between coding efficiency and developer experience. Plus, David reflects on the impact of AI interactions and the importance of context in communication with language models.
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David's LLM Journey
- David Crawshaw intentionally used LLMs while programming for a year to learn about them.
- He now uses LLMs regularly, finding them beneficial for productivity.
LLMs for LLM Networking
- LLMs are surprisingly useful for networking related to LLMs, specifically for inference tasks.
- Multi-cloud environments and complex GPU setups benefit from Tailscale's networking.
GPU Hunting
- Finding GPUs for LLM inference is tricky due to cloud provider variations in availability and pricing.
- This complexity pushes users towards multi-cloud environments.