AI is often sold as a magic switch. Flip it on, and suddenly your pipeline problems vanish, replaced by a flood of qualified meetings. But any seasoned revenue leader knows that technology doesn't solve process problems; it amplifies them. If your messaging is generic, AI helps you send generic messages faster. If your data is dirty, AI scales that chaos instantly.
We recently partnered with a $20M B2B SaaS company to implement HubSpot’s Prospecting Agent (part of the Breeze AI suite). This client had a mature sales team, dedicated BDRs, and a solid product, but they struggled with sales efficiency. Their reps burned valuable hours on admin work (researching accounts, drafting emails, and manually enrolling contacts) rather than selling. They wanted to increase pipeline velocity without resorting to the "spray and pray" tactics that damage brand reputation.
So, we built a system for them using HubSpots newish AI Agent: Prospecting Agent..
This is the exact playbook we used to roll out the Prospecting Agent, turning it from a shiny new toy into a reliable revenue engine that saves their team hours every week while still keeping the pipeline full.
(And Why Ours Don’t)
The biggest mistake we see teams make is rushing to "turn it on" without first designing the thinking behind it. When you deploy AI without structure, you get noise at scale. The Prospecting Agent is powerful, but it acts as a magnifying glass for your existing operations. It will magnify your Ideal Customer Profile (ICP) clarity, the quality of your CRM data, and the discipline of your messaging.
For our client, this meant we had to pause and refine the fundamentals before letting the agent send a single email. We had to ensure the agent wasn't just "doing tasks", but was actually executing a strategy.
We started by sitting down with the client’s VP of Sales to validate the "revenue reality." It’s tempting to skip this step, but for a company in the $5M–$20M range, you cannot afford experimental outbound that confuses the market.
We validated the revenue model first. Was this a pure sales-led motion or a hybrid model? For this client, it was high-touch B2B sales with a significant Annual Contract Value (ACV). This dictated that the agent couldn't sound like a bot; it had to sound like a consultant. It also meant we had to have workflows that seamlessly transitioned the prospect from a bot to a human-led sales system.
We also looked at who actually owns outbound. Is it the SDRs, the Account Executives (AEs), or the founders? In this case, dedicated SDRs owned the process. This mattered because the Prospecting Agent’s behavior needed to mirror how they worked, not how a generic salesperson works. If the agent’s cadence didn't match the team’s deal velocity, it would create friction.
The "Seller Profile" in HubSpot is where you give the agent its identity. Most teams set this up as a generic "Sales Rep" role. That is a mistake.
For our client, we configured the profile to mimic their top-performing seller. We defined the specific role, seniority, and sales motion. Crucially, we established strict territory and account ownership rules. The agent needed to know exactly which product to pitch. If you try to make the agent pitch "everything to everyone," you end up with diluted messaging that converts no one.
Best Practice: Create one seller profile per sales motion, ICP, or CTA, not per rep. Keep the agent voice specialized, but the focus on the message should be on providing the most valuable offer to the prospect.
JARS Insight: The agent should sound like your best rep on their best day. It should not be your entire organization blended together. We configured the agent using proven outreach examples, approved messaging guidance, and strict tone constraints drawn from what had historically driven closed-won deals. The goal wasn’t to let AI invent messaging, but to consistently scale what had already worked.
This is where most teams get sloppy, leading to high bounce rates and annoyed prospects. Enrollment isn't just about who could buy; it's about who is ready to be contacted.
For our client, we established rigorous enrollment criteria based on firmographic fit (industry, size, geography) and life-cycle stage alignment. But the most critical piece was the suppression rules.
We ensured the agent explicitly excluded:
Best Practice: Aim for fewer accounts with higher confidence. Enrollment is not a volume play; it is a precision play. By narrowing the focus, we ensured the client’s domain reputation remained pristine.
Tools don't close deals; timing does. We leveraged HubSpot’s buyer intent signals to turn the Prospecting Agent into a sniper rather than a shotgun.
We activated tools to track website behavior, engagement depth, and CRM history. We used these signals to rank accounts by probability, not just curiosity.
For example, if a prospect visited the pricing page and downloaded a technical whitepaper, that is a high-intent signal. If they just read a blog post, that’s low intent. We aligned these signals to actual buying/lifecycle stages, that then triggered automated outreach.
JARS POV: Intent data is useless unless you tell the agent what “ready” actually means. We configured the agent to reference specific research points—like recent funding news or a new hire in the department—to show the prospect, "I know who you are, and this isn't a blast email."
We defined a messaging framework that explicitly stated the primary pain points the buyer was already feeling. We taught the agent to look for trigger events worth mentioning and to use proof points (like specific case studies) rather than listing product features.
Equally important were the "Do Not Say" rules. We forbade the agent from using jargon that the client’s audience hated, or sounded to much like a bot.
Messaging Structure: Context → Relevance → Next Step.
Best Practice: One message per ICP, per use case. Generic messaging kills AI credibility fast. We built distinct messaging tracks for their Finance persona versus their Operations persona, ensuring the agent spoke the right language to the right person.
Trust drives adoption, and adoption drives ROI. The client’s SDR team was initially skeptical that an AI could write emails that converted into meetings. To bridge this gap, we implemented strict guardrails.
We initially set the agent in semi-autonomous mode. This meant every email drafted by the agent had to be reviewed and approved by a human rep before sending. This created a review loop where reps could see the quality, make minor edits, and train the model further.
We also set performance thresholds. The agent wasn't allowed to scale up volume until it proved it could generate replies at a specific benchmark rate.
This approach transformed the SDRs from "email writers" to "email editors." They maintained control over the relationship, but the heavy lifting of research and drafting was done for them.
Vanity metrics can be deceptive. We ignored raw send volume. A bot can send 10,000 emails a day; that doesn't mean it's adding value.
Instead, we focused on:
By focusing on these metrics, we could prove to the executive team that the investment in HubSpot’s AI tools was paying off in hard revenue, not just "activity."
Throughout this deployment, we navigated around several common pitfalls that often derail AI projects:
The Prospecting Agent is a multiplier, not a shortcut. For our client, it didn't replace the need for skilled salespeople. It removed the drudgery from their day, allowing them to focus on high-value conversations.
The teams that win with AI start with strategy, enforce discipline, and let AI scale what already works. If you try to scale a broken process, you just break it faster.
Short answer: No — and teams that treat it that way usually fail.
Prospecting Agent is designed to support reps, not replace them. It handles research, prioritization, and first-touch assistance, so reps can spend more time on conversations that actually matter.
Yes — and you should.
While you’re not training separate AI models, you can configure Prospecting Agent differently by:
This allows the agent to stay specialized instead of sounding generic. We recommend configuring the agent around motions, not individual reps, to keep messaging consistent and credible.
Prospecting Agent doesn’t invent messaging on its own.
It operates within:
The goal isn’t creativity. It’s consistency. The agent should sound like your best rep on their best day, every time.
Prospecting Agent is only as effective as the system around it.
It pulls from:
This is why clean data, clear ICPs, and enrollment discipline matter more than the tool itself.
This comes down to guardrails.
Best practices include:
Prospecting Agent should scale what already works. not amplify bad habits.
If you want the Prospecting Agent to drive revenue, and not noise, the setup matters more than the tool. At JARS Digital, we specialize in turning HubSpot into a demand generation powerhouse. Let's build your AI-powered workflow together.