Building Reliable AI Systems — Live with 0to1.builders
most AI products don't fail because the model is bad.
they fail because of poor context, broken retrieval, weak workflows, and no real evaluation strategy.
this session breaks down the Claude Architect Mindset, and a practical framework for designing AI systems that actually hold up in production.
what we'll cover:
- why AI failures are usually system design failures, not model failures
- context engineering vs prompt engineering
- when to use workflows vs autonomous agents
- tool use and MCP as an architecture problem
- evals the discipline most builders skip entirely
whether you're a student, software engineer, founder, or just someone who wants to move beyond prompting!
this one's built for you.
free to join. no prior experience required.