Agent Engineering
Agent: AI That Gets Things Done
Click a capability card to see a step-by-step demonstration of how an Agent executes in real-world scenarios.
A regular LLM can only "say" things; an Agent can "do" them. The difference is that an Agent has four additional capabilities that allow it to execute tasks in the real world.
The Classic Architecture · Where It All Comes From
Lilian Weng@lilianweng
Former OpenAI VP of Research & co-founder of Thinking Machines Lab · Now back at OpenAI leading frontier research on recursive self-improvement (RSI)
Many of the ideas in this lesson — and in this entire Agent Engineering chapter — come from her June 2023 blog post "LLM Powered Autonomous Agents". A deeply respected pioneer, she laid out the profoundly influential Agent architecture in the famous "crab diagram" above: the Agent (LLM) sits at the center as the brain, reaching out to Planning, Memory, Tools, and Action.
This one diagram has shaped the entire AI Agent industry — nearly every Agent framework today traces back to it. We highly recommend following her on Twitter/X.
Four Core Capabilities (from Lilian Weng's Architecture) · Click to Switch Demo
Plan
Breaks complex tasks into executable step sequences — think before acting
Tool Use
Calls search, code execution, databases, and APIs — an extension of hands and feet
Memory
Short-term context + long-term vector storage — remembers users across conversations
Act / Reflect
Observes results after execution; on failure, automatically analyzes the cause and corrects course
Regular LLM vs Agent
Regular LLM
Question → Generate answer → Done
Can only "say," cannot "do"
Can only "say," cannot "do"
→
Agent
Task → Plan → Call tools → Observe → Correct → Complete
Step-by-Step Demo
Auto-plays on scroll into view · Click a capability card to switch demo
Takeaway
Takeaway Agent = LLM + Tools + Loop. The core is "Think → Act → Observe → Think again" — which is exactly Lilian Weng's architecture diagram in motion: the LLM is the brain, and Planning / Memory / Tools are its limbs. Every AI product is ultimately designed around this loop. The better the loop is designed, the more reliable the Agent becomes.