What Is Agentic Development
Agentic development shifts how you work with AI-powered tools. Instead of receiving suggestions one line at a time, you delegate multi-step tasks to an autonomous agent that knows your Salesforce org. It plans, executes, and iterates using your org’s metadata, project context, and your team’s coding standards—while you direct and review.
Traditional AI-assisted tools are reactive. You type code, and the tool suggests the next line. You ask a question, and the tool returns a single response. It doesn’t take initiative, coordinate across files, or execute anything on your behalf.
Agentforce Vibes is fundamentally different. The agent:
- Plans before it acts. Given a task description, it breaks work into steps, identifies dependencies, and sequences execution. It produces a plan with Goals, Non-Goals, and numbered Tasks. You approve the plan before any files change.
- Acts in your environment. It creates files, modifies code, runs commands, and deploys metadata directly in your local workspace. Before making changes, it creates a Checkpoint so you can roll back if the output isn’t what you expected.
- Coordinates parallel work. It assigns work to specialized sub-agents—Logic Builder, Component Builder, and QA Validator—each operating in an isolated Git worktree.
- Iterates on failures. When a test fails or a deployment errors, it diagnoses the problem and attempts a fix rather than presenting an error and stopping.
Your role shifts from prompting and copying chat responses to directing autonomous execution and reviewing results.
| Previous Multi-Turn Chat | Agentic Workflow |
|---|---|
| You prompt the chat, review diffs, and approve changes one file at a time | The agent produces a structured Plan with Goals, Approach, and sequenced Tasks. You approve once and it executes all changes. |
| You prompt for one class, approve it, then prompt separately for the test class | The agent generates the Apex class, handler, and test class together as a coordinated unit |
| You copy error output into chat and prompt for a fix | The agent runs tests, reads failures, and iterates toward a fix within the same task |
| You re-provide context each session since the chat doesn’t retain project knowledge | Skills and Rules in your .vibes/ folder persist team conventions and org patterns across every session |
| You sequence multi-file work by deciding what to prompt for next | Teams Mode assigns parallel layers to sub-agents. Each sub-agent works in an isolated Git worktree, then Agentforce Vibes merges the result. |
This shift doesn’t mean you stop thinking about the code. You still:
- Define what the code should do (business logic, acceptance criteria)
- Review generated output for correctness and security
- Make judgment calls the agent can’t (trade-offs, org-specific conventions, architectural direction)
- Decide when to accept, modify, or reject the agent’s work
The agent operates with real information from your connected Salesforce org and local project. It isn’t guessing in a vacuum.
What the agent can access:
- Your project’s file structure, source code, and metadata
- Connected org metadata via the Salesforce DX MCP (Model Context Protocol) server: sObjects, fields, record types, profiles, and permission sets
- SOQL (Salesforce Object Query Language) queryable data about your org’s schema
- Skills and Rules defined in your
.vibes/folder and the Toolkit panel - Open files in your editor (if enabled in context settings)
- Conversation history within the current session
What you must tell the agent:
- Business logic intent—why a field exists, what a process should do, which edge cases matter
- Org-specific conventions not expressed in code or captured in a Skill or Rule
- External system integrations—API (Application Programming Interface) contracts, authentication flows, third-party service behavior
- Deployment targets and environment differences between sandboxes and production
When the agent lacks information, it either asks you or makes assumptions based on what it observes. Reviewing those assumptions is part of your role.
Agentforce Vibes targets Salesforce platform work, not general-purpose code generation:
- Metadata-heavy projects benefit from org-aware automation. The Salesforce DX MCP server gives the agent direct access to your org’s sObjects, fields, and permission sets. It generates code that references real API names, not placeholder values.
- Cross-cutting features require coordination. A feature that touches Apex, LWC, a Flow, and a permission set spans four file types with multiple deployment dependencies. Agent Mode coordinates these files as a single unit of work and creates a Checkpoint before execution so you can roll back cleanly.
- Team conventions carry forward automatically. Skills in
.vibes/skills/encode your team’s patterns—trigger frameworks, test data factories, naming standards—and apply them every time the agent generates code. Rules enforce constraints like bulkification requirements or governor limit checks across all generated Apex. - Test coverage is mechanical but required. Test class generation is time-consuming but well-suited to agent execution. QA Validator in Teams Mode handles assertions, bulk test data, and governor limit coverage.
Agentforce Vibes has two modes. You control how much structure you want before the agent acts.
The default mode. The agent responds directly to your prompt—answering questions, generating code, or making changes based on what you ask. The agent uses the Salesforce DX MCP server to look up org metadata in context. Use Chat for questions, quick changes, and single-file tasks.
Plan Mode produces a structured plan—with Goals, Non-Goals, an Approach section, and numbered Tasks—before any files change. You review and iterate on the plan, then click Approve Plan. The agent executes using the Skills and Rules you’ve configured and creates a Checkpoint before making changes. Use Plan Mode for multi-step work where you want to see and approve the approach first.
- Agentic development isn’t fully autonomous development. The agent makes mistakes—hallucinated method names, incorrect assumptions about your org, code that compiles but doesn’t meet your intent. Human review isn’t optional.
- The agent’s context has limits. Long-running sessions accumulate context. Agentforce Vibes manages this context through auto-compaction and sub-agent isolation. Start a fresh session for unrelated work.
- Permission boundaries matter. Your permission mode settings control what actions the agent can execute. Per-tool settings in the Toolkit let you set individual tools to Always ask or Auto-approve. Start restrictive and expand as you build confidence.
- Generated code requires the same review as human-written code. Verify security, bulkification, governor limits, and error handling regardless of who wrote the code.