Agent Architecture

⚡ 1-Minute Summary Instructions resolve top to bottom. Logic lines run. Prompt lines become English. The model never sees your script. It sees only the finished prompt your logic built. Shorter reasoning instructions produce more accurate agents. Verbosity is not thoroughness. Module map MODULE 2 root: 'What actually happens in one turn?' ├─ 2.1 Anatomy of one turn ├─ 2.2 How the prompt gets built └─ 2.3 Why shorter instructions win Anatomy of One Turn 💬 In plain words: Every message follows the same seven steps: router, before-reasoning, instructions, model, tools, after-reasoning, reply. Learn this sequence and every design decision in Agentforce explains itself. 📌 Example: A Meridian customer says "is my power back yet?". The router picks the outage subagent. Before-reasoning verifies their meter. Instructions run a status action and branch. The model phrases the answ...

💬 In Plain Words: When building enterprise AI agents, you must decide in advance which parts of a conversation the Large Language Model (LLM) is allowed to influence, and which parts are strictly off-limits. Remember this golden rule: An instruction is just a request; a filter is an absolute control. When money, compliance, or eligibility are on the line, you cannot rely on polite instructions in a prompt. You must use hardcoded determinism mechanisms to force certainty.

💬 In plain words: About twenty core words carry most Salesforce Agentforce conversations. Learn these fundamental terms once, and every technical module, architectural diagram, and certification guide will read significantly faster. Each entry below points directly to the system component that powers it. 📌 Key Points Covered in This Guide The difference between internal Employee Agents and external Service Agents . How the Agent Router intelligently hands off conversations to specialized Subagents . Why developers must understand the technical divide between Actions and Tools . How Grounding and the Data Library connect Large Language Models (LLMs) to your private CRM data securely. The role of the Einstein Trust Layer in maintaining data privacy. 🤖 Core Architecture: Agents & Routing To build effectively on Salesforce's modern AI stack, you must understand the primary actors in the system. An Agent is ...

💬 In plain words: Abstract concepts are hard to memorize. To understand how Salesforce Agentforce really works, we use one single running example throughout this guide: Meridian PowerPack . Meridian is a fictional electricity utility company. They sell power, read meters, dispatch repair crews, and handle billing disputes. By applying Agentforce features to Meridian's daily operations, the technical architecture becomes instantly clear. 📌 Key Points Covered in This Guide How to map standard Salesforce objects (Accounts, Cases, Work Orders) to an AI Agent's thought process. The difference between good AI use cases (unpredictable language) and bad ones (deterministic batch processes). How to use Data Libraries to ground your agent in reality, preventing dangerous hallucinations. Why you must split massive business requirements into specialized Subagents rather than building one mega-agent. How strict guardrails prevent your ...

⚡ 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 dat...