Thomas Piacentini
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11 · LLM Engineering

LLM Engineering

Original text · English

Put LLMs to work in production applications.

Start this phase on GitHub

Prerequisites: Phase 10 Lessons 01 through 05, or equivalent knowledge of tokenization, data pipelines, pretraining, and scaling.

First lesson: Prompt Engineering

Run this command from the repository root:

bash
python3 phases/11-llm-engineering/01-prompt-engineering/code/prompt_engineering.py

Keep the command, exit code, generated prompt metadata, test results, and one prompt change with the output difference it caused. The demo uses simulated model responses and needs no API key.

Next action: Explain which prompt variable changed behavior and why, then continue to Few-Shot, Chain-of-Thought and Tree-of-Thought.

Browse the full Phase 11 lesson list or the cross-phase roadmap.

Continue step by step.

Code and artifacts 1
What you take away

Saved in your notebook on this device.

Sources and limits

Reading checkpoints are self-reported. Test results are recorded separately and apply to the executed cases.

AI Engineering from Scratch · 3f9715c · MIT

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