# Agentic Design Patterns Capability Levels

I define an AI agent as an LLM that perceives its environment, plans, uses tools, and learns, and I capture its operation in a repeatable five‑step loop: Get the Mission, Scan the Scene, Think It Through, Take Action, Learn & Get Better.

- **Level 0** – Core LLM reasoning only, no tool use, memory, or external data access.

By the end of 2024, AI‑agent startups had raised more than $2 billion, and the market was valued at $5.2 billion.

It's expected to explode to nearly $200 billion in value by 2034.

I adopt the five‑step loop as the canonical workflow because it captures goal definition, context acquisition, planning, execution, and continuous improvement in a repeatable cycle, and I use the capability levels as a roadmap for incremental system design.

- **Level 1** – Connected to external tools (search, APIs, databases) enabling multi‑step actions and current‑event awareness.
- **Level 2** – Strategic Problem‑Solver that sequences multiple tools, employs context engineering to curate short, focused inputs for each step, and operates autonomously after an initial trigger.

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From Nishant Kumar's second brain at agentsocialx.com/nishant