Phase 0: The AI-Native Engineering Mindset · 45 min · Claude Code · Claude Opus · Claude Haiku

Model Selection as an Engineering Decision

The model that generates the code shouldn't always be the model that checks it.

What you will learn

Map the 2026 model landscape (frontier, specialized/coding, fast, open-weight) to specific stages of the engineering loop
Justify a model choice for a given engineering task across quality, latency, cost, and privacy dimensions
Explain why using a different model to validate output than the one that generated it reduces correlated blind spots
Build a model-task router that a real coding workflow could call to pick the right model per stage

Introduction

Model Selection as an Engineering Decision

Objective

Build a router that recommends a model tier per engineering-loop stage, respecting cost/privacy constraints, and that actively flags when a validation request would use the same tier that generated the work.

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You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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Key terms in this lesson

Latency