𝐓𝐡𝐞 𝐂𝐡𝐚𝐭 𝐓𝐞𝐦𝐩𝐥𝐚𝐭𝐞𝐬 𝐇𝐚𝐧𝐝𝐛𝐨𝐨𝐤: 𝐴 𝐷𝑒𝑣𝑒𝑙𝑜𝑝𝑒𝑟'𝑠 𝐺𝑢𝑖𝑑𝑒 𝑡𝑜 𝐽𝑖𝑛𝑗𝑎, 𝑎𝑝𝑝𝑙𝑦𝑐ℎ𝑎𝑡𝑡𝑒𝑚𝑝𝑙𝑎𝑡𝑒, 𝑎𝑛𝑑 𝑅𝑒𝑛𝑑𝑒𝑟𝑖𝑛𝑔 𝑀𝑜𝑑𝑒𝑙-𝑅𝑒𝑎𝑑𝑦 𝑃𝑟𝑜𝑚𝑝𝑡𝑠

#llm #ai #genai #agents

Your model passed every benchmark. Then it quietly got worse in production - and nothing in the logs explains why.

The usual culprit isn't the model. It's the chat template: the code that turns your list of messages into the exact tokens the model was trained on. Get it wrong and the model still answers - just worse, silently, with no error to chase.

I wrote a book on that layer.

𝐼𝑛𝑠𝑖𝑑𝑒: rendering conversations the way the model was actually trained, reading and writing Jinja templates (including the whitespace bugs that silently break tokenization), handling tool-calling, reasoning, and multimodal templates, authoring a correct template for your own fine-tuned model, debugging with golden-token tests in CI, and fixing the cross-engine differences between Transformers, vLLM, and llama.cpp. There's a chapter on the security side too - chat templates are a real, documented inference-time attack surface.

If you ship LLM features, fine-tune open models, or serve them across multiple engines, this is written for you.