Video: https://www.youtube.com/watch?v=ysPbXH0LpIE

- [00:00] Introduction to the session by Hannah and Christian from Anthropic's applied AI team.

- [00:20] The session focuses on prompting best practices using a modified real-world scenario.

- [02:10] Scenario description: Swedish insurance company analyzing car insurance claims.

- [02:30] Information used: car accident report form and a human-drawn sketch.

- [03:50] Use of Anthropic's Claude model with specific settings.

- [04:05] Settings include temperature zero and a large max token budget.

- [05:40] Best practices for prompt structure: setting task description up front.

- [06:00] Include content, detailed instructions, examples, and repeat important information.

- [08:30] Importance of task context and tone context in prompt engineering.

- [09:00] Ensuring Claude stays factual and confident without guessing.

- [11:20] Version 2 of the prompt has more detailed instructions.

- [11:50] Claude identifies the scenario as a car accident and reflects vehicle involvement.

- [13:40] Background information about the Swedish car accident form.

- [14:00] Details like form structure and common markings explained.

- [15:50] Use of delimiters like XML tags and markdown to organize information.

- [16:10] XML tags help Claude reference information during task execution.

- [20:10] Importance of examples or few-shot learning in steering Claude.

- [20:30] Examples can include data and descriptions for better model understanding.

- [22:00] Conversation history as a tool to enrich Claude's context.

- [22:20] Useful for user-facing applications with ongoing interactions.

- [24:30] Final task reminder and guidelines to prevent hallucinations.

- [24:50] Claude is instructed to answer only when confident, with references to data.

- [28:30] Output formatting ensures data is stored correctly for applications.

- [28:50] Use of XML tags for final verdicts to integrate with systems.

- [31:20] Prefilled responses to shape Claude's output format.

- [31:40] Ensures structured JSON output for serializable data handling.

- [33:10] Claude 3.7 and 4 as hybrid reasoning models with extended thinking.

- [33:30] Extended thinking allows analysis of Claude's reasoning process.