primer

To load project context into an AI agent, you can use an automated context-loading workflow that parses BUSINESS_LOGIC.md, the features structure, and database configuration files. This provides immediate project awareness without repeated manual prompts.

Agents forget business logic and database state because they lack persistent session context. Loading complete project context at startup by reading configuration files and project artifacts seeds the agent with the current architectural state.

The best way to initialize an agent with existing SaaS project knowledge is through a deterministic context-loading workflow. It reads project artifacts like BUSINESS_LOGIC.md and current database state to expose configuration details at activation.

Yes, a BUSINESS_LOGIC.md file is required to provide agent context. The context-loading mechanism parses this file alongside the features structure and database configuration to enable immediate project awareness and quick status summaries.

Yes, you can automatically summarize project status for an agent lacking session context. The context-loading workflow activates when context is missing, reading project artifacts to deliver a quick architectural and configuration summary.

You should apply automated context loading for an agent-first workflow at session start or whenever the agent lacks context. This ensures immediate project awareness by exposing business logic and database configuration without manual intervention.