Andre Muniz

Most AI agents are unnecessarily expensive and the problem is usually architecture, not the model.

One of the biggest pain points when building AI agents is LLM cost. Many teams use high-end models like Claude Sonnet or GPT-5 for everything, even tasks that don’t need that level...

You don’t need a premium model for every AI task. Yet most AI agents today are built like this: everything runs on high-end models, there’s no task segmentation, and no cost control layer. This works… until it doesn’t. Costs scale linearly, while revenue usually doesn’t.

Here’s...

Most AI projects fail because they’re just API wrappers.

Real AI systems need: • structured workflows • reliable data pipelines • scalable backend architecture

I build production-ready AI systems with agents, RAG, and automation.

If you’re serious about AI, let’s build it right.

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