Use Claude for Thinking. Use Agentforce for Reacting.
The Salesforce ecosystem treats AI as a platform loyalty test. It shouldn't be. Here's what I learned building with both Claude and Agentforce — and why the right answer is almost never one tool for everything.
They're complementary, not competing.
The Salesforce ecosystem has a framing problem with AI. Every conversation about AI tools turns into a platform loyalty test. Are you an Agentforce shop or are you using third-party AI? Pick a side.
That's the wrong question. And if your consultant is asking it, they're optimizing for the wrong thing.
Use Claude for thinking. Use Agentforce for reacting.
Eric Lovgren, lovgren.ai
The right question is: which tool is right for which job?
I run a Salesforce consulting practice. I implement Agentforce. I also use Claude — Anthropic's AI — wired directly into Salesforce via MCP. I use both, and I use them for different things, because they're good at different things.
This isn't a hot take or a contrarian stance. It's what you learn when you actually build with both tools instead of picking one based on a vendor relationship.
The two tools sit in different parts of the work. One is built to think; the other is built to react. Hold that distinction and most of the "which AI" debate dissolves.
| Claude (thinking) | Agentforce (reacting) | |
|---|---|---|
| Best at | Open-ended judgment, research, synthesis | Rule-based actions inside Salesforce |
| Trigger model | Polls on a schedule (deliberate) | Event-driven (instant) |
| Reach | Browses the open web, follows links | Native to your data, no API calls |
| Sweet spot | Lead enrichment, qualitative analysis | Tasks, routing, notifications, updates |
A real example: Lead enrichment.
I recently rebuilt my own lead enrichment pipeline. The old system used a web scraper, the OpenAI API, and custom Apex to automatically research new prospects — scraping their website, running it through a prompt, and populating a summary field in Salesforce. It worked, but it was rigid. Every enrichment type needed its own hand-crafted prompt. The scraper cost $145 a month. When it failed, it failed silently.
The old pipeline: a $145/month web scraper, hand-crafted prompts for each enrichment type, and silent failures. It worked, but every edge case needed custom code.
When I redesigned the system, I had a choice: build it as an Agentforce agent, or build it with Claude.
When a new Lead enters Salesforce, go to the company's website, intelligently browse the homepage and a few relevant sub-pages, and come back with qualitative assessments. Not just "what industry are they in" — I can get that from ZoomInfo. I needed things like: What's the most likely business workflow where AI would deliver visible ROI? Are they already exploring AI or is this a new concept? Is there a specific personalization hook — a recent award, an expansion — that makes outreach feel researched instead of mass-produced?
That's a thinking task. It requires browsing the open web, following links based on judgment, reading unstructured content, and producing qualitative analysis that adapts to what's actually on the site.
Agentforce can't do this well. It doesn't browse the web. To make it work, I'd have had to wire up an external scraper (there goes the cost savings), pass the scraped text into a prompt template (there goes the adaptability), and hope the rigid prompt produced useful output for every type of business (there goes the quality). I'd have been rebuilding the old pipeline in newer packaging.
Claude does this naturally. It fetches the website, decides which sub-pages are worth reading, synthesizes what it finds, and populates the fields — with no hand-crafted prompt for each enrichment type. The field descriptions on the Salesforce object are enough instruction. When a site doesn't mention AI, it says "none found" instead of fabricating something. When the homepage is thin, it follows the About page. It thinks.
So why not use Claude for everything?
Because Claude has a real limitation: it's not event-driven inside Salesforce. It polls on a schedule. Every 15 or 30 minutes, it checks for new work. That's fine for enrichment — nobody needs their website summary populated in under a second. But it's not fine for things that need to happen immediately in response to a Salesforce event.
When a Lead's enrichment comes back as "Hot," I want things to happen right now. Create a Task. Log an Activity. Check for duplicate Accounts. Maybe trigger the first step of an outreach sequence. That's reactive work — responding to a data change inside Salesforce with immediate, rule-based actions.
That's exactly what Agentforce is built for. It's native to the platform. It's event-driven. It has direct access to your data without API calls. And for internal, rule-based automation — routing, task creation, notifications, record updates — it's the right tool.
The architecture that actually works.
Here's what I built:
- A Salesforce Flow detects when a Lead meets my enrichment criteria and sets a status field to "Pending." That's the trigger — event-driven, instant, native Salesforce.
- Claude picks up Pending leads on its next scheduled pass, does the web intelligence work — browsing, reading, judging, synthesizing — and populates the enrichment fields. That's the thinking — external, deliberate, adaptive.
- When Claude sets the verdict to "Hot," Agentforce handles the downstream reaction — creating tasks, alerting me, checking for duplicates, kicking off sequences. That's the reacting — internal, immediate, rule-based.
Flow for triggering. Claude for thinking. Agentforce for reacting. Each tool doing what it's actually good at.
This handoff pattern — Flow for triggering, Claude for thinking, Agentforce for reacting — works for any AI automation in Salesforce, not just lead enrichment. Anywhere you need external intelligence feeding internal action, this is the architecture.
Why this matters for your business.
If you're a small business running Salesforce, you don't have the budget or the patience to bet on the wrong AI approach. You need someone who has actually built with both tools and can tell you which one to reach for — and more importantly, which one not to reach for — for your specific situation.
The consultant who only offers Agentforce will try to force every problem into Salesforce's native AI, even when an external tool would do it better, faster, and cheaper. The consultant who dismisses Agentforce entirely will build external dependencies where a native solution would have been simpler and more reliable.
The right answer is almost never "one tool for everything." The right answer is knowing what each tool is good at and bad at, and designing an architecture where they cooperate.
Use Claude for thinking. Use Agentforce for reacting. Know which is which. That's the job.
I wrote more about this both-paths approach — and why your consultant's platform loyalty shouldn't drive your AI strategy — in Red Pill or Blue Pill: The SMB Guide to AI on Salesforce.