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Amphibious

Bridgic Amphibious is a dual-mode agent framework that lets you build agents operating in both LLM-driven and deterministic modes, with automatic fallback between them. Instead of choosing between full autonomy and rigid workflows, Amphibious gives you both — in the same agent.

The framework is built on two core design principles:

  • Agent = Think Units + Context Orchestration — An agent is defined by declaring CognitiveWorker think units and orchestrating them with scoped context, rather than wiring low-level LLM calls manually.
  • Functional Execution vs. Decision Making — Decoupled — Tools and skills are pure capabilities, while when and how to invoke them is handled by either LLM reasoning (on_agent) or developer-defined workflows (on_workflow).
  • Human-in-the-Loop — Three entry points for human interaction: code-level request_human(), workflow HumanCall yield, and the auto-injected request_human tool for LLM-autonomous requests.

Essential

These tutorials cover the fundamental concepts you need to build amphibious agents:

  1. Quick Start: Build your first amphibious agent in 5 minutes — run both Agent mode and Workflow mode to see the dual-mode experience firsthand.
  2. Dual-Mode Orchestration: Master the two orchestration modes — on_agent for LLM-driven decision making and on_workflow for deterministic step-by-step execution.
  3. RunMode: Explore the four run modes and learn how Amphiflow mode automatically switches between Workflow and Agent when things go wrong.
  4. Customizing the OTC Cycle: Override hooks in the Observe-Think-Act cycle — inject custom observations, reshape LLM messages, intercept tool calls, and post-process outputs.
  5. Execution Tracing: Record, export, and analyze the full execution trace of your agent for debugging and optimization.

Advanced

These tutorials dive deeper into specific capabilities for advanced use cases:

  1. Phase Annotation: Organize complex agent execution into structured phases using the snapshot context manager.
  2. CognitiveWorker & think_unit: Understand the framework's atomic building block — the pure thinking unit that only decides what to do, plus its declarative execution configuration and error strategies.
  3. Context & Exposure: Control what the LLM sees — manage agent state with Context and choose between full disclosure and progressive reveal with Exposure strategies.
  4. Cognitive Policies: Enable multi-round deliberation before action — let the agent gather details (Acquiring), mentally rehearse plans (Rehearsal), and assess information quality (Reflection).
  5. Cognitive History: Understand the three-tier memory system — Working Memory, Short-term Memory, and Long-term Memory — that automatically manages execution history.

This architecture makes Bridgic Amphibious a powerful platform for building agents that are both reliable and adaptive — bridging the precision of deterministic workflows with the creative problem-solving of LLM reasoning.