Countering the idea that AI sacrifices quality for speed, Honeybook's recruiting agent found four net-new, high-quality candidates the team had missed manually. The fifth candidate it found was one the team was already pursuing, validating the AI's quality and ability to augment human efforts.
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Honeybook built a ChatGPT agent that logs into LinkedIn, searches for candidates based on a job description, and applies nuanced filters (e.g., tenure, location, activity). This automates a time-consuming, multi-step workflow, freeing up the hiring team for higher-value tasks.
Don't just replace human tasks with AI. Deploy AI agents to handle leads your sales team ignores, like small deals or low-scored prospects. This untapped segment, as SaaStr found with a 15% ticket revenue lift, represents significant growth potential by filling a gap in your GTM process that humans create themselves.
Instead of replacing top performers, AI should be used to do work humans physically cannot. Salesforce targeted a backlog of 100 million 'orphan leads,' using an AI agent to work through 8,000 dormant leads in three weeks. This generated $500,000 in pipeline that would have otherwise been zero.
Contrary to expectations, job candidates found it easier to talk to an AI interviewer. The lower pressure of a non-human interaction allowed them to relax, be more open, and talk more freely about their experiences, leading to better outcomes.
As AI handles technical tasks, uniquely human skills like curiosity, empathy, and judgment become paramount. Leaders must adapt their hiring processes to screen for these non-replicable soft skills, which are becoming more valuable than traditional marketing competencies.
The next frontier for AI in product is automating time-consuming but cognitively simple tasks. An AI agent can connect CRM data, customer feedback, and product specs to instantly generate a qualified list of beta testers, compressing a multi-week process into days.
Traditional pre-qualification uses rigid scripts, potentially missing high-value clients who don't fit the mold. Agentic AI analyzes conversation nuances to identify various customer archetypes and high-intent signals beyond the primary avatar, ensuring top prospects aren't overlooked.
By building a custom AI agent for inbound lead qualification, Vercel reduced its inbound SDR team from ten people to one. The agent, which cost only $1,000 per year to run, maintained conversion rates while decreasing response time and number of touches needed.
The paradigm shift with AI agents is from "tools to click buttons in" (like CRMs) to autonomous systems that work for you in the background. This is a new form of productivity, akin to delegating tasks to a team member rather than just using a better tool yourself.
Powerful AI assistants are shifting hiring calculus. Rather than building large, specialized departments, some leaders are considering hiring small teams of experienced, curious generalists. These individuals can leverage AI to solve problems across functions like sales, HR, and operations, creating a leaner, more agile organization.
