How to Give AI Coding Agents the Right Context for Better Results

Agentic coding lowers the barrier to building software, but the quality of the generated code depends heavily on the context the agent receives. This session explains which inputs matter most and how builders can stay in control of the agent's decisions.

■ Core Context Inputs for Coding Agents
- Files and existing code, plus how to point the agent in the right direction
- Repository structure and compact repo maps
- Dependencies and lock files, including version accuracy
- Tests that give the agent a feedback loop
- Documentation such as conventions, build commands, and agents.md
- Developer intent, constraints, and definitions of done

■ Getting Context from the Agent
- Interviewing you before writing code
- Exploring the repo and explaining its structure
- Making a plan with stated assumptions and recording findings

■ Managing Context Effectively
- Why longer inputs receive uneven attention
- Filtering for task-relevant information
- Starting fresh sessions and clearing noise

This is useful for beginners and experienced builders alike who want practical, repeatable habits for working with coding agents. After watching, you will be able to identify which context to supply, ask an agent to surface what it needs, and keep decision-making authority in your own hands.