Hands-on AI + Salesforce builds with real-life scenarios — each project tells you the problem, the stack and exactly what you'll learn.
Build, don't just read
Every brief links to a full hands-on article. More builds land as the AI push continues.
Scenario: Admins spend hours translating business rules into validation formulas. Build an Agentforce-powered tool where you type "Opportunity amount must be over 1000 for Closed Won" and it generates and deploys the rule via the SOAP API.
You'll learn: Prompt-to-formula generation, deploying metadata programmatically, and guarding AI output before it touches production.
Scenario: A manufacturer's customers live in a Next.js portal, not Experience Cloud. Embed an Agentforce agent behind the portal's chat widget using the Agent API — sessions, streaming responses and Case transcripts included.
You'll learn: Client-credentials OAuth, the Agent API session lifecycle, and keeping Salesforce credentials server-side.
Scenario: A retailer's returns agent needs live data from SAP and a courier API. Expose both through MuleSoft MCP servers so the agent discovers and calls them as governed tools — no custom integration actions.
You'll learn: The MCP tool contract, enterprise MCP registry governance, and swapping backends without touching the agent.
Scenario: Support answers live in hundreds of PDFs and knowledge articles. Ground an agent on that content with Agentforce Data Library so it answers from real sources instead of hallucinating.
You'll learn: How Data Library auto-builds chunks, search indexes and retrievers, and how to write grounded prompts.
Scenario: Wire the open-source @salesforce/mcp server into your AI coding assistant so "run the failing tests and explain the coverage gap" executes against your scratch org — a real agentic-DevOps workflow.
You'll learn: MCP client configuration, safe org toolsets, and where AI genuinely speeds up Salesforce development.
Scenario: Refunds must follow policy — no exceptions, no LLM improvisation. Build a refund topic where Agent Script enforces eligibility checks deterministically and the LLM only handles the conversation.
You'll learn: Hybrid reasoning, deterministic transitions, and testing probabilistic agents in the Testing Center.
Scenario: Tier 2 engineers lose 10 minutes per escalation reading case history. Auto-generate a structured handoff summary with a grounded Prompt Builder template fired from a record-triggered Flow — zero code.
You'll learn: Grounded prompt templates, invoking them from Flow, and designing AI output people actually trust.
Scenario: Sales wants a one-paragraph account brief before every call — on the record page, in a nightly digest and as an agent action. Build it once in Apex with the Models API and reuse it on all three surfaces.
You'll learn: Calling LLMs through the Einstein Trust Layer from Apex, grounding with USER_MODE queries, and reuse patterns.
Scenario: Most support tickets are the same handful of "where's my order / how do I reset this" questions. Stand up an Agentforce service agent on an Experience Cloud help site and Messaging, grounded on Knowledge, that resolves those itself and hands off to a human through Omni-Channel when it can't.
You'll learn: Deploying an agent to web and messaging channels, grounding answers on Knowledge, and designing a clean escalation-to-human handoff.
Scenario: An agent that can only talk is half a product — the value shows up when it can act. Build a custom Agentforce action that logs a warranty claim through a Flow, with typed inputs, validation and a confirmation step, so the LLM never writes junk into your records.
You'll learn: Designing agent actions with input/output types, choosing Flow vs invocable Apex, and guarding writes so AI stays inside policy.
Scenario: Sales ops fields "what's the status of the Acme renewal?" in Slack a hundred times a day. Deploy an employee-facing Agentforce agent in Slack, grounded on CRM data through Data 360, so the team self-serves answers without ever opening Salesforce.
You'll learn: Employee vs customer agent design, deploying an agent to Slack, and grounding it on live CRM data with Data 360.
Scenario: Speed-to-lead wins deals, but reps can't answer every web inquiry in minutes. Configure an Agentforce SDR agent that engages inbound leads over email, answers product questions from grounded content and books meetings — escalating qualified leads to a human seller.
You'll learn: Configuring autonomous outreach guardrails, grounding responses on approved content, and handing off qualified leads to sellers.