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Most software projects focus on producing outputs. Most AI projects focus on producing predictions. But real organizations don't operate on outputs or predictions alone. They operate on decisions. A decision has consequences. A decision creates risk. A decision consumes resources. A decision changes
The architectural decisions that came before the agent — and an honest look at what a basic LLM chatbot can and cannot do. 📚 The CloudSeven Agent series · Part 1 Building a production-grade AI agent in public, one phase at a time. ← Series introduction: I'm building a production-grade AI airline as
Good models don't save bad architecture, and most teams learn that the hard way. The post Most AI Agents Fail in Production Because They’re Built Backwards appeared first on Towards Data Science.
Generic tech DD templates miss what actually kills deals in 2026: AI claims that aren't production-grade, architecture that won't survive 2× traffic, and eng teams that look senior on LinkedIn but can't ship. This checklist is what I use when doing independent engineering due diligence for VCs and a
Imagine you’re building a personal research assistant. Its job is to ingest hundreds of academic PDFs, learn your unique writing style, and eventually draft comprehensive reports for you. When you first launch it, you connect it to a bleeding-edge cloud model like Claude 3.5 Sonnet or GPT-4o via Ope