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Reference
  • Introduction to the AI Team
  • Introduction to Maestro
  • Introduction to the Prospector
  • Introduction to the Qualifier
  • Introduction to the Reacher
  • Introduction to the Deal Manager
  • Introduction to the Booker
  • Introduction to the Notetaker
  • 1-on-1 Coaching Meetings
  • How Harp Learns From You
Help/The AI Team/How Harp Learns From You

How Harp Learns From You

Your AI team gets smarter over time. Learn how coaching, context, and feedback help agents improve, and how you shift from hands-on to monitoring and autopilot.

ReacherToday

C-level contacts convert better than managers

QualifierYesterday

Prioritize healthcare and funded startups

Our coaching and training approach

Harp is built around a simple idea: your AI team should get better the more you use it. We don't ship a fixed model and hope it fits. Instead, we give you tools to coach and train your agents so they match your business, your tone, and your ideal customer.

1-on-1 coaching meetings are the fastest way to onboard the team. You run structured sessions with Maestro to build battle cards, define your tone of voice, document pricing, and handle objections. Everything you share becomes knowledge the agents use. Benefit: your outreach and follow-ups sound like you from day one.

Beyond 1-on-1s, you can add learnings anytime. Tell Maestro "C-level contacts convert better" or "Prioritize healthcare." The agents apply these rules when they work. The more you teach, the more precise the team becomes.

Why more context helps

Agents perform better when they have more context. Your ideal customer profile, battle cards, tone of voice, and objection handling all feed into how the Prospector searches, how the Qualifier scores, and how the Reacher drafts. Sparse context means generic output. Rich context means emails that feel personal and leads that match your sweet spot.

Invest early in your knowledge base and 1-on-1s. A few hours upfront pays off in higher reply rates, better-qualified leads, and fewer edits. Over time, add learnings from wins and losses. "We lost that deal because of pricing" becomes a learning the team uses next time.

How agents learn from you

Agents learn from your actions, not just your words. When you approve an email, the Reacher remembers what worked. When you reject a lead, the Qualifier adjusts. When you edit a draft before sending, the Reacher picks up on your changes. Thumbs up and thumbs down on leads and emails feed into the model.

You don't have to write formal feedback. Just use the platform. Approve, reject, edit. The team adapts. Benefit: less manual configuration, more natural improvement as you work.

From hands-on to monitoring and autopilot

Most users start by approving every email and reviewing every lead. That's the right approach. Build trust first. See how the team performs. Give feedback.

As the team improves, you can shift to monitoring. Let the Prospector and Qualifier run on their own. Review the Reacher's drafts in batches instead of one by one. Use Maestro to check pipeline health and pending approvals instead of clicking through every screen.

Eventually, many users turn on autopilot for initial and follow-up emails. The team sends first touches and follow-ups automatically. You still approve every reply. Your reputation stays protected while the team runs more of the workflow. Benefit: scale your outbound without scaling your hours.

The goal is not to replace you. It's to free you for meetings, strategy, and high-value conversations. The more you coach the team, the more it can run on its own.

Table of contents
  • Our coaching and training approach
  • Why more context helps
  • How agents learn from you
  • From hands-on to monitoring and autopilot

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