Advanced LLM Agents MOOC Spring 2025 - video 10 - 1:32:39

Memory and planning

Agents forget, repeat work, or plan against a false model of the environment.

memoryplanningRAG
Reasoning, Memory & Planning of Language Agents by Yu Su

Problem-first learning

The problem this lecture is trying to solve

Agents forget, repeat work, or plan against a false model of the environment.

Lowest-level failure mode

Memory retrieval and world modeling decide what the agent believes is true before acting.

Frontier update

RAG is becoming active memory: agents choose what to store, retrieve, validate, and forget.

Transcript-grounded route

How the lecture unfolds

This is built from 1,581 caption segments. Use the timestamp buttons to jump into the original video when a term feels fuzzy.

0:00-15:30

Pass 1: That

The lecture segment repeatedly returns to that, reasoning, just, more, what. Treat this part as the board-work for the mechanism, not as a definition list.

Write one line that connects the terms to the central failure mode: Memory retrieval and world modeling decide what the agent believes is true before acting.

15:30-30:53

Pass 2: Memory

The lecture segment repeatedly returns to memory, that, will, rag, planning. Treat this part as the board-work for the mechanism, not as a definition list.

Write one line that connects the terms to the central failure mode: Memory retrieval and world modeling decide what the agent believes is true before acting.

30:53-46:22

Pass 3: Memory

The lecture segment repeatedly returns to memory, rag, that, reasoning, hipporag. Treat this part as the board-work for the mechanism, not as a definition list.

Write one line that connects the terms to the central failure mode: Memory retrieval and world modeling decide what the agent believes is true before acting.

46:22-1:01:48

Pass 4: That

The lecture segment repeatedly returns to that, facts, data, training, atomic. Treat this part as the board-work for the mechanism, not as a definition list.

Write one line that connects the terms to the central failure mode: Memory retrieval and world modeling decide what the agent believes is true before acting.

1:01:48-1:17:16

Pass 5: That

The lecture segment repeatedly returns to that, grokking, will, circuit, entity. Treat this part as the board-work for the mechanism, not as a definition list.

Write one line that connects the terms to the central failure mode: Memory retrieval and world modeling decide what the agent believes is true before acting.

1:17:16-1:32:39

Pass 6: Planning

The lecture segment repeatedly returns to planning, that, just, actions, very. Treat this part as the board-work for the mechanism, not as a definition list.

Write one line that connects the terms to the central failure mode: Memory retrieval and world modeling decide what the agent believes is true before acting.

Build the mental model

What you should understand after this lecture

1. Start from the bottleneck

Agents forget, repeat work, or plan against a false model of the environment. The lecture is useful because it does not treat this as a naming problem. It asks what breaks at the operational level and what design pattern removes that break.

2. Name the moving parts

The recurring vocabulary in the transcript is that, memory, will, planning, reasoning, just. When studying, do not memorize these as separate buzzwords. Ask what state is stored, what action is chosen, what feedback is observed, and what verifier decides whether progress happened.

3. Convert the idea into an architecture

Separate episodic memory, semantic memory, and working context. Planning needs a model of action consequences. Long-horizon agents need checkpoints and summaries. In exam or interview answers, this becomes a four-part answer: objective, loop, control boundary, evaluation.

4. Know the failure case

Memory retrieval and world modeling decide what the agent believes is true before acting. If you cannot say how the proposed system fails, the explanation is still shallow. Always include the failure it prevents and the new cost it introduces.

Concept weave

Ideas to remember

  1. Separate episodic memory, semantic memory, and working context.
  2. Planning needs a model of action consequences.
  3. Long-horizon agents need checkpoints and summaries.

Visual model

Agent system view

Use the graph to ask where the intelligence really lives: model, memory, tools, environment, verifier, or orchestration.

Written practice

Questions that make the idea stick

Drill 1Design memory for a coding agent.
  1. Store repo map, user constraints, test results, decisions.
  2. Retrieve by task and file path.
  3. Expire stale assumptions.
Drill 2When does memory hurt?
  1. Poisoned memories.
  2. Over-retrieval.
  3. Outdated facts.

Written answer pattern

How to write this under pressure

ClaimMemory and planning solves a concrete control problem, not just a prompt-writing problem.
MechanismState the loop: observe state, choose action/tool, get feedback, update memory or plan, stop using a verifier.
Why it worksIt makes the hidden failure mode visible: Memory retrieval and world modeling decide what the agent believes is true before acting.
TradeoffExtra orchestration improves reliability only if evaluation, cost, and authority boundaries are explicit.

Build skill

How to apply this in your own agent

  1. Write the concrete task and the failure mode before choosing any framework.
  2. Choose the smallest architecture that handles the failure: workflow, single agent, orchestrator-worker, or evaluator loop.
  3. Define tool schemas, memory boundaries, and a success checker.
  4. Run a small eval set with failure labels, cost, latency, and trace review.

Source route

Original course links and readings

Page generated from 1,581 YouTube captions. Raw transcript files are kept out of the public site; this page publishes study notes, timestamp routes, and paraphrased explanations.