AI-Assisted Development

What Is AI-Assisted Development?

AI-assisted development covers a wide spectrum — from inline code suggestions to autonomous coding agents that can receive an issue, plan a fix, write the code, and open a pull request.

Our team explores this range of development capabilities from multiple angles. The Copilot Experiment documents the journey from AI skeptic to productive user with GitHub Copilot CLI; Teaching an AI to Build Software tests how process and guardrails affect agent output by building the same app five different ways; Agentic AI Tools & Resources for Senior Developers maps the broader tooling landscape in a concise and easy to reference way for experienced senior developers.

The through-line across all of this work is consistent: humans stay accountable for intent, architecture, review, and release quality. AI accelerates execution within those guardrails.

Why It Matters

Leaders need AI adoption to deliver value without quietly eroding code quality. That requires treating AI output with the same rigor as any code contribution — through evaluation frameworks, quality reporting, and AI-ready coding practices that give tools the context they need to succeed.

For teams just starting out, the AI Prototyping series offers a structured approach: short-lived builds that demonstrate viability and surface risks before committing to production.