Prompt Engineering Best Practices for Anthropic Claude
Refining GenAI Best Practices with AWS Support
This article was written by Jakob Panten and Christopher Lennan
At idealo.de, we recently engineered our first production GenAI use case: an LLM-based product comparison. We teamed up with AWS Solutions Architects on this project and shared our learnings at multiple AWS events, highlighting how the recent AWS migration technologically enabled idealo.
- AWS Summit Berlin (May 2024)
Speakers: Andreas Hankel (CTO, idealo) and Christopher Lennan (ML Engineer, idealo) - AWS Summit Stockholm (June 2024)
Speakers: Stefan Christoph (Principal Solutions Architect, AWS) and Jakob Panten (Software Engineer, idealo) - AWS Generative AI Deep Dive Day Zurich (June 2024)
Speakers: Dennis Bappert (Senior Solutions Architect, AWS), Jakob Panten (Software Engineer, idealo), Christopher Lennan (ML Engineer, idealo)
Learnings from GenAI project
We presented our experiences with a deep dive into our product comparison use case focusing on prompt techniques for structured output and production challenges. We provided many hands-on examples for the Anthropic Claude model family, which we ended up using through the AWS Bedrock API, and compared its performance to other state-of-the-art LLMs. We also explored tackling costs and latency with smaller fine-tuned open-source LLMs.
Regarding prompt engineering we presented essential techniques such as one-shot prompting and chain-of-thought reasoning. We also emphasized the importance of clear instructions for ensuring the model receives precise and unambiguous prompts, as well as test-driven development for iteratively testing prompts to refine performance.
For a deeper dive into these topics, watch the full session recording from the AWS Summit in Stockholm:
The events offered valuable insights into the transformative potential of generative AI. They underscored the importance of continuous innovation and collaboration in this rapidly evolving field.
At idealo, we are excited about the future of generative AI and its applications in enhancing user experiences.
