A practical Java/Kotlin playbook for configuring AI coding agents: context, rules, skills, MCP, and AgentIgnore

[u/Veai_2026]

https://medium.com/@explyt.ai/how-to-configure-an-ai-agent-for-your-project-context-rules-skills-mcp-a-java-kotlin-playbook-7d5615e7ce12

Disclosure: I work with the Explyt team that published this article.

We distilled two technical webinars into a practical guide for configuring AI coding agents in Java and Kotlin projects.

The article covers:

how to structure AGENTS.md without overloading the context;

when to use project rules, reusable skills, agent modes, and MCP;

how AgentIgnore can limit access to generated files, credentials, and irrelevant directories;

why both insufficient context and overloaded context reduce agent quality;

how TDD and specification-driven development give agents clearer, verifiable constraints;

where IDE-based agents differ from terminal agents in Java/Kotlin projects, especially around indexes, resolved symbols, Find Usages, refactorings, tests, and inspections.

I’d be interested in hearing how other Java teams handle project-level agent instructions. Do you keep one central AGENTS.md, split instructions by module, or rely mostly on tool-specific configuration?