Ready to move beyond single-model agents? Dive into continuous improvement loops (Kaizen) using Genkit and Vertex AI Model Garden. We show you how to use models from multiple providers as a 'writer' and a 'critic' to build AI agents that critique and refine their own outputs for maximum quality and improved results.
Dive in
Simplify your LLM development by using one Genkit plugin to access models like Claude, Mistral, Gemini, and Llama from Vertex AI's Model Garden. Learn how to switch between large language models without the hassle of rotating API keys or tracking multiple quotas.
Dive in
We’re diving deep into the latest paradigms in AI development, starting with the difference between traditional context files (Gemini.md) and the new "Agent Skills" dynamic. We also share a story about using the Vertex AI Prompt Optimizer to automate our YouTube descriptions. It took 5 hours and nearly 100 million tokens, but the results were surprisingly consistent. Finally, we geek out on the Model Context Protocol (MCP), experimenting with exposing Flutter application state as local tools using Unix sockets.
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Learn how to use the Vertex AI Prompt Optimizer to automatically tune your prompts to get better results by iterating on your prompts and then running an evaluation on the outputs assessing their quality to see if it has improved.
Read at firebase.blog