<ul data-eligibleForWebStory="true"><li>The breakthrough in improving an AI coder's performance came from writing better prompts rather than more code.</li><li>The process starts with submitting a Markdown 'design card', leading the AI to iterate by writing tests, generating code, and refining based on feedback.</li><li>Despite a well-established setup, the AI faced challenges with simple tasks due to communication issues, not coding bugs.</li><li>The generated code technically worked but didn't meet real-world Python testing, logging, and project layout expectations.</li><li>The key change that enhanced the AI's performance was improving the instructions or prompts provided to it.</li><li>Enhancing the prompts led to a more effective and reliable AI performance.</li><li>Interested in agentic AI, test-driven development with LLMs, or creating intelligent coders? Follow the author's journey on Medium or connect on LinkedIn to explore building trustful code-writing systems.</li></ul>

The Art of Guiding AI: My Journey in Prompt Engineering for an Agentic Coder

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