Standardising Agentic AI: The A1/A2/T1/T2 Framework

2. Standardising Agentic AI: The A1/A2/T1/T2 Framework

A landmark survey paper (arXiv:2512.16301) has provided the industry with a unified vocabulary for agentic adaptation. The framework categorizes agents across four paradigms:

• A1/A2 (Architecture-centric): Focused on the model's internal structures.
• T1/T2 (Tool/Task-centric): Focused on how the model adapts to external environments.

T2 (Tool Adaptation) is being hailed as the most significant breakthrough for practical deployment. It allows models to "learn" how to use new APIs and software environments through interaction rather than retraining. OpenClaw was specifically highlighted as a representative case study of a system that excels at T2 adaptation, making it a benchmark for agentic autonomy.

Why it matters:

• Clear definitions allow enterprises to evaluate which "level" of agentic capability they actually need for specific business problems
• T2 adaptation offers a path to "capability accumulation" that is significantly cheaper than traditional fine-tuning
• OpenClaw's architecture is being validated as a blueprints for future autonomous systems

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