Everyone says agentic coding builds whole projects. Why doesn't it work for me?
Q: Everyone says agentic coding builds whole projects. Why doesn’t it work for me?
While agentic engineering is incredibly powerful and shows great promise, its capabilities are sometimes overhyped. Reports of AI agents ‘one-shotting’ complete applications from scratch usually involve simple projects where the agent cannot really go wrong. In those scenarios, as long as the generated code compiles and does something useful, it is considered a success.
Applying agentic coding to more complex, existing projects with many interdependent components and legacy code requires a deliberate approach. To achieve high-quality, dependable results, two foundational practices are crucial: Context Engineering and Specification.
Context Engineering
Context engineering involves providing the agent with project-specific instructions and background knowledge. This grounds the agent in the reality of your codebase, ensuring its outputs align with established patterns. Key methods include:
Configuration Files: Using dedicated files, such as
AGENTS.md, to outline base rules.Progressive Loading: Supplying context dynamically through specific Agent Skills.
Project Documentation: Sharing architectural decisions, coding conventions, and system designs.
Workflow & Testing Guidelines: Providing explicit information on how to use the project’s infrastructure and test suite.
Specification
Specification is the practice of guiding the agent step-by-step using complete, unambiguous information about the immediate task. Rather than relying on the agent to infer your goals, you must define the boundaries explicitly. This can be achieved through:
Spec-Driven Development: Utilising comprehensive specification documents, such as formal product requirements or detailed roadmap instructions.
Detailed Prompting: Crafting prompts that clearly articulate the core intent, constraints (what the agent should not do), what a successful outcome looks like, and how to verify that success.
By rigorously applying both context engineering and specification, developers can tame the inherent unpredictability of agentic engineering – transforming it into a dependable approach even within the most intricate legacy systems.
…
Looking to learn how to use AI agents effectively for software development? The spring cohort of Elite AI-Assisted Coding, the #1 comprehensive course on making the most of agentic software development, is open for signups, and we’re offerring a 25% early bird discount until March 23rd. Join us!
