Here’s a deeper breakdown of an example infra agent stack:
• Adapter Agent – Connects to third-party APIs and services
• Routing Agent – Directs requests to the right agents based on intent
• Context Agent – Gathers relevant data and context for each task
• Observer Agent – Monitors for state changes, triggers actions
• Memory Agent – Writes structured memories into long-term storage
• Memory Retrieval Agent – Pulls relevant history and long-term state
• Vector DB Sync Agent – Keeps embeddings fresh and synced
• Model Adapter Agent – Interfaces between local agents and foundation models
• Telemetry Agent – Collects signals, usage, outcomes, and feedback
• Data Coordination Agent – Brokers shared data across agents, APIs, and models
• Real-Time Event Agent – Listens for streaming or real-time events and reacts
• Signal Agent – Translates signals into structured triggers
• Output Post-Processor Agent – Cleans and formats model outputs before sending
• Execution Agent – Coordinates complex tasks across agents
• Sync Agent – Updates source-of-truth systems with new state
• Action Recorder Agent – Logs what was done, when, and why
• Intent Refinement Agent – Clarifies ambiguous input before dispatching
• Schema Agent – Generates, updates, or maintains internal schemas
• Failure Recovery Agent – Detects failures and re-routes or retries
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