Agentic Coding Roadmap
Practices you can use to improve your Agentic Coding workflow.
This page is under heavy development and will change. More detailed information will be added.
Agent generates code that looks like yours. Reviews stop being about formatting.
Read more →Better first-attempt output. Less back-and-forth. Include file paths, constraints, architecture context.
Start with plan mode. Review the plan, stay in planning until the plan is solid, then approve implementation. Catches misunderstandings before they become code.
Agent succeeds more often when each prompt has one clear responsibility.
Agents understand data shapes and constraints through types. Fewer implicit rules to guess at. Free leverage in strongly typed languages like TypeScript or Go.
Automated first pass catches style violations, missing tests, and common mistakes before you look at it. Invoked by coding agent for immediate feedback loop.
Flat beats deep nesting. Agents get lost in complex directory hierarchies with many micro-packages, just like new team members do.
Agent knows your codebase persistently — architecture, patterns, conventions. No more explaining from scratch. Keep it minimal: onboarding doc, not encyclopedia.
Enforcing cognitive/cyclomatic complexity keeps generated code reviewable and maintainable.
Read more →Write a markdown plan with goals, constraints, edge cases, and step breakdown before prompting. Acts as a contract between you and the agent — better plans produce better code.
Security, performance, accessibility — different concerns need dedicated reviewers at scale.
Agent gets a possibility to get instant feedback about written code. Reduces a chance of regression.
Trust that a generated feature works as a whole, not just in parts.
Enforce boundaries programmatically — dependency rules, layer violations, import restrictions. The agent can't break what's mechanically enforced.
Specs docs with acceptance criteria, edge cases, and constraints. Better specs produce better first-attempt code.
Automated safeguards at three levels: review during generation, pre-commit check on staged files, full branch check before PR. Creates a refactoring loop on any quality regression.
Delegate research and different components to different agents. Each agent is focused on one feature slice improving efficiency.
Is there a Level 4?
Yes, some people do magic with agents orchestration. But I will be focusing on the first 3 levels as they can make your team multiply their performance.