⚡ 1-Minute Summary
- An agent understands language, decides what to do, and acts. A chatbot only answers.
- Every example in this notebook uses one company: Meridian Power. Same company, every module.
- Learn the 360 Card first (0.5). It is the shape of every good answer: rule, gain, price, limits.
Module map
MODULE 0 root: 'What is Agentforce, and how do the modules fit together?'
├─ 0.1 The map: one agent, six layers
├─ 0.2 Meridian Power — the example company
├─ 0.3 Key terms in plain words
├─ 0.4 The rename map (2024-2026)
└─ 0.5 The 360 Card — how to answer any question
0.1 The Map: One Agent, Six Layers
💬 In plain words: Agentforce looks like many products. It is not. It is one agent with six layers stacked under it. Each layer answers one question, and each module of this notebook lives on one layer.
📌 Example: A customer types "my power is out." Identity decides whose data can be touched. Routing picks the outage specialist. Reasoning builds the prompt. Actions create the case. Grounding supplies the outage map. Operations records what happened.
Concept
- Read the layers bottom to top. Each one stands on the layer below.
- 1. Identity: Which user the agent runs as. Question: What may it touch?
- 2. Reasoning: How one turn is built and resolved.
- 3. Routing: Which specialist handles this message.
- 4. Doing: Actions, and the script that ties them together.
- 5. Knowing: Grounding, prompt templates, retrieval.
- 6. Trusting: Determinism, guardrails, security.
- On top sits Operations — where the agent runs, how you test it, what it costs, how you ship it.
- If an answer feels lost in an interview, name the layer first, then go one step down.
AGENT
├─ Identity → which user, which permissions
├─ Reasoning → how one turn resolves
├─ Routing → which subagent handles it
├─ Doing → actions + Agent Script
├─ Knowing → grounding, templates, retrieval
└─ Trusting → determinism, guardrails, security
Operations on top: channels, testing, cost, ALM
🧠 The stack: "I Reason, Route, Do, Know, Trust." Identity first, trust last. Name the layer, then go one step down.
🧭 360 Card — The Map: One Agent, Six Layers
Rule: Name the layer before you answer. Identity, reasoning, routing, doing, knowing, trusting.
Gain: You never freeze. Every Agentforce question belongs to exactly one layer.
Price: It is a mental model, not a Salesforce feature. Do not quote it as product architecture.
Limits: 20 active agents per org. 15 subagents per agent. 15 actions per subagent.
Mirror — feature-list thinking: You can name every button and still not explain why an agent misbehaved.
Later: This map is also your revision order. Weak on a layer means weak on its modules.
At volume: One agent cannot span a large enterprise. The 15-subagent ceiling forces an orchestrator plus specialists.
⚠ INTERVIEW TRAP: Do not open with a feature list. Interviewers hear "Agentforce has topics, actions, and Data Cloud" from everybody. Open with the layer the question lives on.
Core Q&A
Q: Explain Agentforce to someone who knows Salesforce but has never built an agent.
🎯 Say this first: It is one agent with six layers under it — identity, reasoning, routing, doing, knowing, trusting.
A: Start with what makes it different from a chatbot.
- A chatbot follows a decision tree somebody drew in advance. Off the tree, it fails.
- An agent reads the request, picks one specialist, and calls real actions that write to Salesforce.
- Underneath, six layers. Identity decides which user it runs as, and that is the hard ceiling on what it can touch.
- Reasoning turns your instructions into a finished prompt before the model is ever asked.
- Routing picks exactly one subagent. Doing is the actions. Knowing is grounding.
- Trusting is where you decide which parts the model is allowed to influence at all.
- The stronger answer names the layer the question is really about, rather than listing features.
Follow-ups (Scenario-Based)
Q1: Where does Data 360 sit in that picture, and is it required?
A1: It sits on the knowing layer, and it is required only for some grounding.
- Record data, related lists, Flow and Apex grounding need no Data 360 at all.
- Retrieval from documents does — that is where Data Library, search index, and retriever live.
- Common mistake: Saying Agentforce needs Data Cloud. It does not, unless you are grounding on unstructured content.
- One more dependency worth knowing: The Einstein Trust Layer settings page needs Data 360 before it will display.
Q2: A stakeholder asks why you would not just build this in Flow. What do you say?
A2: Frame it as predictability of input, not capability.
- Flow is right when the steps are always the same and the input is structured.
- An agent earns its cost when the input is human language and the path varies.
- Flow is also free. Agent conversations consume credits, so volume matters.
- Architect answer: Most real solutions use both. The agent handles the conversation, while Flow performs the deterministic work behind it.