AI-Led Sales: How 1Mind's Superhumans Drive Exponential Growth, from the Agents of Scale Podcast

Amanda reveals that OneMind's AI superhuman 'Mindy' sources 76% of their pipeline opportunities. When selling to HubSpot, instead of personally answering questions from 20+ stakeholders, Amanda directed them to Mindy, shrinking the typical 90-day enterprise sales cycle to 30 days. HubSpot became a reference customer reporting 25% revenue increase after deploying superhumans.

• •OneMind's superhuman generates 76% of pipeline opportunities through AI-led engagement
• •HubSpot deal cycle reduced from 90 to 30 days by having Mindy handle stakeholder questions
• •HubSpot achieved 25% revenue increase using superhumans in their PLG motion
• •Amanda could see all conversations with Mindy and came to final calls knowing exactly what prospects cared about

Amanda argues that separating marketing, sales, and customer success into silos is a human capacity constraint that AI eliminates. She criticizes the traditional buyer journey where prospects get passed from SDRs to AEs to solutions engineers to customer success, calling it 'a nightmare what we do to our buyers.' AI superhumans can support the entire lifecycle with one cohesive experience.

• •Traditional org silos exist because of human capacity limitations, not optimal customer experience
• •Buyers currently suffer through handoffs between SDRs, AEs, solutions engineers, and CS teams
• •AI superhumans can manage entire customer lifecycle from first touch through upsell
• •Future org structure needs one unified team managing customer lifecycle end-to-end, not separate departments

Amanda explains how superhumans differ from chatbots through their ability to share slides, give live demos, read screens, and recall from thousands of decks instantly. At HubSpot, 88% of visitors engaged with the superhuman, with 35% having deep, meaningful conversations. This contrasts sharply with typical chatbot engagement of ~5% and conversion of ~2%.

• •Superhumans can share slides, give demos, and instantly retrieve relevant content from thousands of decks
• •HubSpot saw 88% visitor engagement rate with superhuman vs. typical 5% chatbot engagement
• •35% of HubSpot visitors had deep conversations where pain points were uncovered and solutions proposed
• •Traditional chatbots just route to content or book meetings with unqualified SDRs
• •Superhumans speak any language, understand any industry vertical, and maintain full conversation history

Amanda identifies AEs as currently safest from AI replacement due to soft skills like navigating organizations and building relationships. However, she sees SDR roles (qualifying leads) and solutions engineers (doing demos) as highly vulnerable since 80% of deals involve information transfer, which AI handles exponentially better. She notes AI doesn't 'hallucinate nefariously' like salespeople do to close deals.

• •Account Executives are safest because organizational navigation and relationship building remain hard for AI
• •SDRs focused on qualification are at highest risk - AI can qualify better without human limitations
• •Solutions engineers doing demos are vulnerable - AI can instantly access and present any technical content
• •80% of typical deals involve information transfer, where AI excels over humans
• •AI provides more accurate information than humans who 'hallucinate nefariously' to close deals

Amanda introduces 'AI-Led Growth' as the solution for PLG companies trying to convert free trials to paid without knowing if a lead is a $500/month or $5M/month deal. Superhumans can have sophisticated conversations with every prospect regardless of deal size. One large social networking platform saw sales cycles drop from 22 days to 2 days and doubled their average selling price using this approach.

• •PLG companies can't afford human sales for every lead when deal size is unknown
• •AI superhumans enable sophisticated conversations for both $500 and $5M potential deals
• •Social networking platform reduced sales cycles from 22 days to 2 days with AI
• •Same platform doubled their average selling price (ASP) using superhumans
• •AILG bridges the gap between pure PLG and sales-led enterprise motions

Amanda reveals OneMind's remarkable policy: if employees can eliminate their own role with AI, they'll be rewarded financially and given a new role at the company. She emphasizes the need for transparency about job displacement, stating 'we do the world a disservice when we tell people their jobs aren't going to be replaced.' She's hiring for curiosity and ability to transition roles.

• •OneMind rewards employees financially if they successfully automate their own jobs
• •Company commits to finding new roles for employees who eliminate their positions with AI
• •Amanda is transparent that job displacement is real and inevitable
• •Hiring focuses on people capable of transitioning and learning new skills
• •Considers offering equity to employees who successfully replace themselves with AI

Amanda discusses the new critical role of managing AI agents across the entire organization. This person needs to understand all functions because agents must communicate across departments. She's currently hiring for this position and compares it to a 'chief of staff for AI.' The role involves managing agent-to-agent handoffs, workflows, and ensuring agents work cohesively rather than in silos.

• •New role needed: someone to manage all AI agents across the organization
• •This person must understand the full organization since agents cross functional boundaries
• •Role is similar to 'chief of staff for AI' - hands in everything across the business
• •Involves managing agent-to-agent communication, handoffs, and workflows
• •OneMind's CTO, head of product, and head of CS currently meet weekly on this until dedicated hire

Amanda shares her philosophy that hearing 'no' is essential for category creation. If everyone says yes, you're just incrementally better than existing solutions. She and her early head of sales would celebrate rejections, knowing that widespread acceptance meant they weren't pushing boundaries enough. She warns against being too close to current reality when building transformative products.

• •Category-defining companies must get rejections - universal acceptance means incremental improvement
• •Amanda celebrates 'no' responses as validation of pushing boundaries beyond current playbooks
• •If product fits too neatly into existing frameworks (like 'better chatbot'), it won't create new category
• •Early OneMind team would 'kick each other under the table' celebrating rejections
• •Rejections provide valuable feedback on how to evolve product while maintaining vision

Amanda envisions a future where AI abundance allows society to deemphasize economic contribution and value work that serves human well-being. She shares her brother's story of leaving a CEO role to become a chaplain, doing 'God's work' with no economic value but immense human impact. She hopes for a value shift where such work becomes recognized and supported.

• •AI abundance could enable meeting basic needs without requiring traditional economic contribution
• •Amanda's brother left CEO role to become chaplain, sitting with dying patients and homeless - no economic value but profound human impact
• •Society needs to shift what we value from purely economic productivity to human well-being
• •People should be able to pursue work that brings joy and elevates energy, not just economic necessity
• •Comparison to agrarian ancestors who would view today's jobs (Twitch streamers, YouTubers) as 'just fun'