New course! Spec-Driven Development

2026-04-15 · Source: DeepLearningAI · Field: Technology & Digital — Software Development & Engineering, Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

JetBrains has partnered to launch a new course on spec-driven development (SDD), a disciplined, agentic coding workflow. This approach emphasizes starting with a detailed markdown file or prompt, known as a "spec," to guide AI agents in code generation, contrasting with traditional live coding. The course, instructed by JetBrains developer advocate Paul Everett, teaches participants to write high-quality specs for both new and existing codebases. It addresses challenges like reducing the risk of agents producing incorrect or mismatched code, preserving context across multiple agent sessions, and improving intent fidelity. Participants will build a web application called Agent Clinic, designed to help AI agents with issues like hallucination and context rot, while learning to manage cognitive debt by operating at the intent level rather than the code level.

Key takeaway

For AI Engineers and Software Engineers adopting agentic coding workflows, this course offers a structured approach to improve code generation and reduce cognitive overhead. You should consider learning spec-driven development to enhance intent fidelity, ensure agents match your goals, and manage complex projects by working at the intent level rather than getting overwhelmed by generated code. This can significantly streamline your development process.

Key insights

Spec-driven development uses detailed specifications to guide AI agents, improving code quality and managing developer cognitive load.

Principles

• Control large code changes with concise specs.
• Preserve high-quality context across agent sessions.
• Manage cognitive debt at the intent level.

Method

Start with a markdown file or long prompt (the "spec") explaining exactly what to build, then let the AI agent generate code based on that specification, focusing on context the agent lacks.

In practice

• Write specs to control AI agent output.
• Use specs for iterative, automatable workflows.
• Translate application trade-offs into clear specifications.

Topics

• Spec-Driven Development
• AI Agents
• Code Generation
• Agent Clinic Application
• Cognitive Debt Management

Best for: AI Engineer, Machine Learning Engineer, Software Engineer

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• What If Your AI Had a Constitution? — Spec-Driven Development uses structured, version-controlled documentation to guide AI coding assistants, preventing technical debt and ensuring compliance.
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Editorial summary, takeaway, and curation by AIssential. Original article published by DeepLearningAI.