Our honest read on GitHub Copilot for Salesforce devs closed on a problem we hadn’t solved. Copilot is a real productivity gain on the parts of our codebase that look like the rest of GitHub. It is not platform-aware. It does not know what an sObject is, what a governor limit is, or which fields actually exist in the org you are connected to.
So we added a second assistant. One that does.
This is the rollout story for Agentforce Vibes (formerly Agentforce for Developers) — what it sees that Copilot can’t, where the two coexist cleanly, and the per-task rule we wrote so that nobody on the team has to guess which one to reach for at 3pm on a Thursday.
What Agentforce Vibes knows that Copilot doesn’t
Agentforce Vibes is Salesforce’s first-party coding assistant. It ships as a VS Code extension, bundled into the Salesforce Extension Pack and Salesforce Extension Pack (Expanded), and is also pre-installed in the Agentforce Vibes IDE — the browser-based VS Code environment Salesforce hosts for org-tied work (formerly Code Builder). Per the official extension docs, the default coding model is Claude Sonnet 4.5. It is available across the Developer, Enterprise, Partner Developer, Performance, and Unlimited editions.
The thing that matters is not the model. It is the context window the extension stuffs in front of the model on every request. That context includes things Copilot has no way to see:
- Governor limits. SOQL queries per transaction, DML statements per transaction, CPU time, heap size. The assistant treats these as hard constraints when it generates Apex, not as nice-to-have hints.
- Base LWC components. When you ask for a record picker or a record form, you get the platform components (
lightning-record-picker,lightning-record-form), not a hand-rolled HTML/JS approximation of one. - SOQL selectivity. The assistant has been trained to bias toward indexed fields and away from leading-wildcard
LIKEpatterns. It will not always get it right, but it knows the question exists. - Apex idioms.
with sharingdefaults,Database.SaveResulthandling, the bulk-pattern shape (query outside the loop, mutate inside, DML outside again). - sObject metadata for your connected org. This is the part that actually changes things. The assistant pulls live schema from the authenticated org, which means when it writes
Account.Customer_Tier__cit has actually checked that the field exists on Account in that org. Stale metadata is still possible (more on that in the failure-modes section), but the baseline is “real fields from your org,” not “plausible-sounding field name.”
The assistant also exposes Agentforce Chat, a multi-turn conversational pane in the editor for natural-language code generation, test-class generation, and code explanation. There’s checkpoint and git integration so agentic edits don’t sprawl across files unsupervised. Setup is documented here; for the platform-side framing of where Vibes sits in the broader Agentforce ecosystem, our Agentforce platform primer is the right starting point.
None of this makes Agentforce Vibes a replacement for Copilot. It makes it a complement. Copilot is still the better tool when the file open in front of you is plain JavaScript or a Jest test. Vibes is the better tool the moment the file becomes Apex or LWC against a real org.
Side by side: same prompt, two assistants
The clearest way to see the difference is to feed both tools the same prompt and read what comes back. We ran two scenarios on the same connected org during a weekly tech sync. Outputs are paraphrased for length; the shapes are accurate.
Scenario A — “Generate an Apex method that returns Accounts modified in the last 7 days”
Copilot’s first pass:
public List<Account> getRecentAccounts() {
Date cutoff = Date.today().addDays(-7);
return [
SELECT Id, Name, Industry
FROM Account
WHERE LastModifiedDate >= :cutoff
LIMIT 1000
];
}It compiles. It runs. The semantics are subtly wrong: LastModifiedDate is a Datetime, and comparing it against a Date works but loses the time component, so “the last 7 days” becomes “since midnight 7 days ago” in the user’s local timezone. The arbitrary LIMIT 1000 is a Copilot tic; it adds a limit because it has seen limits in training data, not because the business rule asked for one. And the method returns a raw list with no pagination affordance for callers that might process more than 1,000 records.
Agentforce Vibes on the same prompt:
Agentforce Vibes output (full Apex class)
public with sharing class RecentAccountService {
/**
* Returns Accounts modified in the trailing 7-day window.
* Uses LAST_N_DAYS to delegate timezone handling to the platform
* and keeps the query selective via the standard LastModifiedDate index.
*/
public static List<Account> getRecentAccounts() {
return [
SELECT Id, Name, Industry, LastModifiedDate
FROM Account
WHERE LastModifiedDate >= LAST_N_DAYS:7
WITH SECURITY_ENFORCED
ORDER BY LastModifiedDate DESC
];
}
/**
* Bulk-safe variant: callers that need more than the default
* SOQL row cap (50,000) should iterate via this QueryLocator.
*/
public static Database.QueryLocator getRecentAccountsLocator() {
return Database.getQueryLocator([
SELECT Id, Name, Industry, LastModifiedDate
FROM Account
WHERE LastModifiedDate >= LAST_N_DAYS:7
WITH SECURITY_ENFORCED
ORDER BY LastModifiedDate DESC
]);
}
}Three differences worth naming. First, LAST_N_DAYS:7 is the SOQL date literal the platform expects for trailing-window queries; it handles user timezone correctly without the dev having to think about it. Second, WITH SECURITY_ENFORCED adds field-level and object-level security enforcement automatically, which Copilot has no reason to add unprompted. Third, the assistant volunteered a QueryLocator variant for batchable callers, because it knows the default 50,000-row SOQL cap is a real ceiling that bites in production.
Scenario B — “Build an LWC that lets a user search and select an Account”
Copilot defaults to a hand-rolled component — input box, debounced fetch through an Apex controller, a results list with click handlers, manual selection state. Probably 80 lines of HTML and JS plus the Apex method. It works. It is also a small reinvention of a wheel the platform already ships.
Agentforce Vibes reaches for the platform component:
<!-- accountPicker.html -->
<template>
<lightning-card title="Select an Account" icon-name="standard:account">
<div class="slds-p-horizontal_medium">
<lightning-record-picker
label="Account"
placeholder="Search accounts..."
object-api-name="Account"
onchange={handleAccountChange}>
</lightning-record-picker>
<template lwc:if={selectedAccountId}>
<p class="slds-m-top_small">
Selected: <strong>{selectedAccountId}</strong>
</p>
</template>
</div>
</lightning-card>
</template>// accountPicker.js
import { LightningElement } from 'lwc';
export default class AccountPicker extends LightningElement {
selectedAccountId;
handleAccountChange(event) {
this.selectedAccountId = event.detail.recordId;
}
}lightning-record-picker is the platform’s standard record picker. It handles search, debouncing, accessibility, and recently-viewed records out of the box. No Apex controller needed. No reinvention. The whole component is fifteen lines instead of eighty, and it inherits behaviour the platform team is responsible for keeping correct.
This is the gap the side-by-side exposes. Both assistants produce working code on both prompts. Only one knows what the platform already gives you for free.
Decision rule: which assistant per task type
After about a month of running both tools in parallel, we wrote down a per-task matrix. Not as policy, just as a tiebreaker for when someone is staring at a file and wondering which autocomplete pane to listen to. It lives in our team handbook now.
| Task | Reach for |
|---|---|
| LWC styling, plain JS utilities, Jest setup | Copilot |
| Apex with governor limits, SOQL with selectivity concerns | Agentforce Vibes |
| Trigger handler scaffolding, batchable Apex shells | Agentforce Vibes |
| README writing, doc-comments, commit messages | Copilot |
| sObject-aware queries against the connected org | Agentforce Vibes |
LWC built from base components (lightning-record-picker, lightning-record-form) | Agentforce Vibes |
| Generic data-shaping helpers, array/string utilities | Copilot |
The shape of the rule is simple: anything where the suggestion needs to know something about the platform goes to Vibes. Anything where the suggestion is essentially generic JavaScript or English prose goes to Copilot. The middle is small, and when we’re in the middle we let whichever assistant fires first take the suggestion and we read it carefully before accepting.
In practice the seniors and the architect override this matrix all the time — sometimes Vibes just nails a JS utility, sometimes Copilot’s Jest setup is wrong for our test factory and we ask Vibes for the rewrite. The matrix is for the junior and the mid, who otherwise lose ten minutes per file deciding. With the rule written down, the default is the right tool, and overriding it is a conscious choice.
Failure modes we watch for
Vibes is the better Salesforce assistant. It is also new enough, and Salesforce-specific enough, that it has its own catalogue of ways to be wrong. These are the three we hit most often.
Over-correction
Sometimes Vibes refuses to suggest a pattern that is fine in the specific context. Asked for a single-record Apex insert inside a @future method, it has on a few occasions added bulk-pattern boilerplate that doesn’t apply (there’s no list, there’s no loop). The output still works, but it carries fifteen lines of ceremony for a five-line job. We delete the ceremony and move on. The lesson: bulkification training is a hammer, and sometimes it sees a screw.
Hallucinated field names
When the assistant’s view of org metadata gets stale (usually because someone added a field in setup but the local Salesforce extensions haven’t refreshed), Vibes will confidently reference Account.Account_Tier__c while your org actually has Account.Customer_Tier__c. Compile catches it. Code review catches it. But it happens often enough that we treat any custom-field reference in a Vibes suggestion as needing a glance at the actual schema before we ship. Run SFDX: Refresh SObject Definitions if you’ve added fields recently; it forces the metadata sync the assistant relies on.
Obsolete patterns
The training data goes back far enough that Vibes occasionally generates pre-LWC Aura idioms when the prompt is ambiguous. Asked to “add a button that shows a toast on click,” we have seen Aura’s force:showToast event surface in the suggestion instead of the LWC ShowToastEvent. This is rare on greenfield LWC files where the imports already establish the world, but it shows up on mixed-codebase files that still have Aura components nearby. Re-prompt with “in LWC” explicitly and the suggestion shifts.
The general pattern across all three: when Copilot and Vibes disagree, or when a Vibes suggestion looks slightly off, we cite the official Salesforce docs as the tiebreaker. Not the assistant that “feels more confident.” The docs.
Closing
Two assistants, one editor, one rule for which one owns which file. That is the shape of the layering. Neither one is enough alone. Together they cover most of what a Salesforce dev does in a sprint without us having to think about which tool to reach for on which task.
Next week we step past autocomplete entirely. Post 4 covers the Salesforce DX MCP server — the shift from line-by-line suggestions to whole-feature agentic workflows where the assistant runs sf commands against the org, reads the results, and chains the next step itself. What we let it do, what we did not, and the guardrails we wrote so the junior’s machine never accidentally deploys to production.
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