This guide provides hands-on instruction and conceptual grounding for leveraging Large Language Models to accelerate the process of turning technical specifications into working software. Balance the speed of AI with the rigor of a spec-first approach.
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Transform Specs into Code, Faster
Discover practical techniques to go from specifications – whether functional requirements, API designs, or user stories – to generated code drafts using LLM coding assistance. Learn to apply a workflow where the specification remains the primary source of truth, enhanced by AI acceleration.
Who This Guide is For
Designed for senior software engineers, software architects, product owners, and product managers who have intermediate familiarity with AI tools and some ad-hoc experience with coding assistants. We bridge the gap between understanding the potential of LLMs and applying them effectively in development workflows.
Our Core Philosophy
At the heart of this guide is the principle of specification-centered development. We show you how to use LLMs as powerful accelerators for code generation and translation, but always grounded in and verified against a clear, robust specification. Code is secondary; the spec is primary.
How the Guide Helps You
Structured using the Diátaxis framework, this guide is organized to support different learning and doing styles:
Tutorials
Guided, step-by-step paths to achieve tangible outcomes, like building an API endpoint or a React component from a spec.
How-to Guides
Practical instructions for solving specific problems, from setting up your environment to crafting effective prompts and validating generated code.
Explanations
Conceptual background to help you understand why spec-centered development with LLMs works, their capabilities, and limitations.