Bye, AI SDRs - Hello Superhuman Agents
HubSpot's AI agent Fiona handles what would take 83 SDRs and 19 sales engineers - and lifts trial conversions 78%
Supported by 1mind → AI Superhumans for revenue teams
Superhumans (1mind’s Agentic Conversational AI Agents) integrate seamlessly into existing workflows to qualify buyers, book meetings, deliver pitches, give demos, handle objections, uncover pain points, build value models, and onboard customers. They delight buyers, drive operational efficiency, and scale beyond human limitations focusing on increasing revenue, shortening sales cycles, and increasing ACV.
Founded by Amanda Kahlow, former founder and CEO of 6sense and a trailblazer in account-based marketing (ABM) who has now created AILG (AI Led Growth). 1mind has raised $40 million from Battery Ventures, Primary Ventures, Wing Venture Capital, Harmonic Growth Partners, Operator Collective and Success Venture Partners, and prominent executives from Monday, ZoomInfo and Databricks.
Dear GTM Strategist,
I used to think selling would be the last human frontier. The relationship work, the trust-building, the reading-the-room work - I assumed AI would help around the edges while humans stayed in the seat.
Then I met Nigel, 1mind’s newly launched Ride-Along Superhuman. My honest reaction: “I thought this would be possible by 2030. And yet, here we are.”
Here’s the thing most GTM leaders don’t talk about openly: the Solutions Engineer (bottleneck is the silent killer kof B2B deal velocity.
The median AE:SE ratio is 4:1. In many orgs, it’s 10:1. Which means most live sales calls have zero technical support in the room. The buyer asks a hard question, the rep stalls, and the deal goes cold. Qualified pipe doesn’t lose to competitors. It loses to friction.
Teams try to patch this with duct tape: AI listeners, Slack-based help channels. Fine for nudges, useless when the prospect asks something off-script.
The old answer is to hire more SEs. The smarter one is a two-layer SE org: AI handles the repeatable 60-70% of Q&A live on the call, humans handle the strategic 30-40% (where most SEs want to be anyway).
That’s the bet 1mind is making. They are aiming to scale the SE motion, not replace it. Boston Consulting Group predicted this in their August 2024 The Future of Sales with AI report. 1mind is one of the first to deliver on it.
Nigel reads the room like a seasoned pro, stays focused on what he was trained for, and never bluffs. Which is more than I can say for most human-led demos I’ve sat through.
In this edition, I invited Jonathan Kvarfordt to join forces again. Jonathan has a great eye for winners and is one of the sharpest minds in our space.
Here’s what you’ll learn in this edition:
Why the standard SaaS buyer journey is structurally broken, not just slow
The OAR Matrix: how to decide whether to Optimize, Amplify, or Reinvent with AI
The four lanes every GTM team will pick from in the next 18 months
Three concrete moves every GTM leader should make this quarter
What “AI-first GTM” actually looks like in practice, with proof points
Jonathan, the floor is yours 🎤
The buyer journey was built for 2018. Your buyers live in 2026.
Walk through your own funnel as a buyer. The pattern is painfully consistent.
A prospect researches their problem on Perplexity or ChatGPT. They have recommendations from AI and then they land on your site, like what they see, and fill out the inbound form. A 22-year-old BDR who started six weeks ago calls them and asks the same qualifying questions Perplexity already answered.
They get scheduled into discovery with an AE, who asks most of the same questions again.
Meanwhile the buyer is pinging peers and former users to self-educate, because nobody on your side has actually answered their question yet. Eventually, a demo happens. Then come the follow-ups, the stakeholder alignment calls, and - if everyone is still awake - a close.
Sound familiar? It should. This is the standard SaaS playbook, and it has a clear lineage. Predictable Revenue in 2012 gave us the SDR/AE split. SalesLoft, Outreach, and 6sense around 2014 gave us sequenced cadences, lead scoring, and intent data. 2020 forced the entire industry online. 2022 added the PLG layer.
By 2018, the model had settled: deterministic workflows, MQL-to-SQL handoffs, BANT-or-MEDDIC qualification gates, seat-based pricing, and 80-90% gross margins that made it all economically viable. That model was beautifully tuned for its world.
And then came AI-led growth (AiLG) and changed everything. Buyers self-educate before they ever talk to us, AI has compressed research time from weeks to minutes, gross margins on AI-native products have collapsed to 50-60%, and the buyer increasingly knows more about your category than your rep does.
We are running a playbook designed for a world that no longer exists. It is yielding diminishing returns and is expensive to run.
How to fix it?
Humans are only capable of so much and 75% of the drag is internal friction anyway
Here is the part of this conversation almost nobody is naming.
When my team at Momentum ran the analysis, 75% of the friction slowing down sales cycles came from inside the company, not from the buyer. It wasn’t RFP processes, security review, or buyer indecision dragging deals out. It was internal handoffs, approval queues, and CRM hygiene. SDRs reminding AEs, AEs chasing SEs, SEs waiting on implementation.
The deal moves slowly because we move slowly.
And the cost model is breaking right alongside it. Depending on stage and industry:
10-50% of CAC goes to sales and marketing
20-50% of revenue is spent on sales alone
50-80% of cash burn is driven by headcount
So we’re running an expensive, slow model in a market that rewards the opposite.
Most GTM teams aren’t built for the AI world. Handing your 2018 playbook a ChatGPT license is not transformation. You do not transform from writing emails faster.
Most “AI in GTM” conversations stop at the buyer-facing surface - chatbots, AI demos, automated outreach. That’s treating the symptom, not the system. You cannot fix what’s broken by trying harder on top of it.
Let me be very clear here. The old world would say, “hire more humans” but countless thought leaders, analysts, and companies in the space have already identified that growth at all costs does not work.
Here is the other side of the coin: even if you could have all the funding in the world, humans have capacity constraints. Knowledge limits, only work at certain times, talent quality variability, scheduling nightmares, etc. These constraints cause, as we have talked about, which is the horrible buying experience. So what if we looked at the issue from first principle thinking? What if we ask the question, what is best for the buyer and customer experience?
After working with thousands of individuals, hundreds of companies, and working on AI strategy and implementation since before ChatGPT was released, I can tell you, you can only optimize a human so much because of the constraints, at some point, you hit a ceiling. When I was at Momentum, we released the book called Ignite, where we interviewed 30+ experts in the space about this and everyone came to the same conclusion, which is to think in systems and that means balance between humans and AI, not only AI and not just only humans - it’s a harmony between the two. Architecting the intelligence of both humans and AI, not one replacing the other.
At 1mind, every use case we solve for is something that humans do not do right now anyway. For example, how many companies do you know of that have an expert human on their website (not an SDR), ready to jump on a Zoom call at any time and able to answer deep technical questions 24/7?
The answer is… no one. Why? Because no one can afford it.
How many companies have 1:1 coverage of AE to SE? Not many… why? You got it, no one can afford it, let alone find enough talent to fill the gaps, even if they could.
How many companies have a product expert ready to answer deep technical questions right after someone buys a product? Again, not many.. Most give you a few hours of onboarding or some sort of onboarding doc and send you on your way…
How many Customer Success teams have deep technical support anytime they need it?
If anything, every customer success leader and team I have been on has been begging for more help, not less.
But what if we ask the question, what if we gave a genuinely delightful experience? What if we gave our BEST to our customers from the start? What if we used technology as a way to make the customer experience better? Is that not a good thing?
This is me as a human actually typing a phrase that AI usually does, but this is NOT about replacing humans, it is about doing things that humans are not doing right now in the first place.
What to do instead?
The OAR Matrix: put AI where it actually belongs in your org
Most GTM teams I work with want to jump straight to “AI transformation.” The smarter move is to know which level you are actually playing at.
At GTM AI Academy, which has helped over 10,000 leaders on their AI Adoption Journey, I teach a simple framework called the OAR Matrix to help them figure out where they are and where they want to head next.
Optimize. Same process, made faster with AI. Realistic gain: 10-30% time savings. For a large org, that is a serious ROI number. Start here if your team has low AI maturity or low appetite for disruption.
Amplify. Real structural changes. More revenue, real cost savings. Realistic gain: 20-40%. You are not blowing up the function, but you are seriously rewiring it.
Reinvent. Burn the playbook. Rebuild from first principles. Realistic gain: 100x on the right function.
Most organizations are optimizing where they should be reinventing. You may be asking, but will humans actually talk to an AI and get value? Will businesses actually use this?
To make that concrete, look at HubSpot - one of the most sophisticated demand engines in B2B.
HubSpot could have gotten stuck on the Optimize path: better sequences, ChatGPT licenses for the SDR team, faster routing. Instead, they put an AI Superhuman named Fiona at the front of their funnel and let her handle the buyer conversation end-to-end.
The results speak for themselves:
88% of buyers who landed on the page engaged with Fiona
32% had a meaningful conversation - averaging nearly 8 minutes, with 90% surfacing real pain and 55% getting into pricing
78% increase in free trial conversions
25% increase in influenced pipeline
But the number that should stop every RevOps leader cold is this:
HubSpot estimated it would have taken 83 SDRs and 19 sales engineers to deliver the same volume and depth of buyer conversations.
Remember, this putting AI in a place that HubSpot could not hire for in the first place, so this comparison is not saying they replaced this many people, they identified how many people it would have taken them to hire to be comparable.
That is the gap between Optimize and Reinvent. Optimize gives you 20% more from your current 102-person team. Reinvent reimagines the entire process where AI gets put into the mix for a better buyer experience and allows humans to do more of what you need your humans to do, like build better relationships, stakeholder management, and connect with customers the way that only humans can.
Reinvention always feels like a slingshot pulling backward. It takes time to reinvent and build from the foundation up. So you feel like a rock in a sling shot and while everyone is on Linkedin posting about the latest agent that made them $2 million in 2 days that they built over the weekend, you are feeling like you are falling behind. But trust me, when you do this right, you accelerate faster than ever. You don’t catch up to where you were, you launch past it.
In 2027, buyers will choose how they want to buy from you
Up to this point, I have been talking about what AI does inside your GTM team. Here is the harder question: what AI does to the buyer’s experience of you.
Within the next 18 months, every company will land in one of four lanes. There is no neutral position, and the lane you pick becomes part of your brand whether you intend it to or not. Because the BUYER is the one who will control how they want to interact with you, because now they have options. Which means we as companies need to think about giving them a “choose your own journey” type of experience.
For example:
1. Human only. The buyer demands human only experiences. For whatever reason some humans will reject AI and demand a human only experience. No one knows the size of this group, but it will be a reality at least for the coming future. If this is the case, those human buyers will expect the best of the best. Mediocrity will not be tolerated because just like how Amazon released 2 days shipping and you expect every company you work with to have 2 day shipping, buyers will have the same expectations when it comes to overall experience. The Tide lifts all boats and that tide is a better buying experience is a minimum requirement.
2. Human, with AI assist. The buyer goes through a similar experience to what most have right now where the seller stays in the seat; AI handles the back-office work. This is Optimize on the OAR Matrix. Most GTM teams I work with are aiming here - realistic, achievable, a solid place to operate from. AI is here and there in the process, but it focuses on human-to-human interaction.
3. Human to AI. This is where things start to shift into AI Led Growth. Gartner surveyed 646 B2B buyers and identified that 67% PREFER a rep-free buying experience. If someone is willing to work with your company but is tired of the old-school buying process that we already walked through, why not give them the option of doing more with AI? HubSpot is running this. Seismic is running this. ZoomInfo is running this. The bet is that buyers want optionality, and the data so far says they do not only in surveys, but in real life.
4. AI to AI. This is the one most people are not ready for. Within 12 to 18 months, a meaningful share of your inbound traffic will be AI agents - OpenClaw, Hermes, or self built Claude Code or Cowork or ChatGPT AI Agents all acting on behalf of a human buyer, doing the research, comparing vendors, and in some cases making the purchase recommendation. Is your website, your pricing page, your demo flow designed to be evaluated by an AI agent in 90 seconds? The future will be where the human buyer has a fleet of agents not only doing research, but has a wallet with a budget that they can pay for solutions. Are you ready?
The strategic question is not “will AI replace my salespeople.” That is the wrong question, and it makes leaders defensive. The right question is: what buying experience does our brand want to be known for? Pick your best fit. Design for it.
The principle underneath it all: design around the buyer, not the seller
The single biggest mindset shift required to operate in any of the four lanes above is this: stop designing your GTM motion around what the seller does, and start designing it around what the buyer needs at each step.
Once you do, you discover that a lot of seller activity exists only because the seller’s workflow demanded it - the BDR call, the AE re-discovery, the qualification gate. AI handles the parts the buyer never needed a human for. Humans show up where buyers actually want them: judgment, negotiation, edge cases, relationship.
That is the actual reorganization. Not your org chart. Your workflows.
Three things to do this week
You do not need to rebuild your GTM org by Friday, but you do need to start. Three moves:
1. Walk your own funnel. Pick a friend in your industry and have them go through your buyer journey end to end - inbound form, BDR call, AE call, demo, follow-up. Measure how much time it takes to get to the end goal. Have them rate the experience 1 to 10 and answer one question: would they recommend it to a friend? Most GTM leaders have never done this exercise on their own funnel. Most are stunned by what they find.
2. Map the internal handoffs, not just the buyer journey. Where does the deal slow down inside your walls? SDR to AE? AE to SE? Approval queues? Quote desk? Pricing exceptions? Map every handoff and time-stamp each one for your last ten closed deals. The pattern will be obvious within an hour, and it will tell you exactly where AI belongs first especially when you map these frictions to your buyers journey. Optimize in areas where these frictions overlap.
3. Pick one workflow to redesign around the buyer. Don’t try to fix everything. Pick the single most expensive workflow in your funnel - your AE discovery process, your trial-to-paid motion, your renewal flow - and ask which steps exist because the buyer needs them, and which exist because your process demanded them. In that area, give the buyer and customer the option of AI. You will be surprised how many will not only use the AI, but prefer it.
A year from now, the GTM orgs that win will look smaller, faster, and weirder - fewer humans, doing the parts only humans can do, with AI doing the rest. The org chart won’t look like 2018. Neither will the revenue per head. This will cause disruption of the old world
And one more thing
You can read about AI Superhumans all day. The only way to understand what one actually feels like in production is to have a conversation with one. Mindy at 1mind, Fiona at HubSpot, and others are running live - go talk to them for five minutes.
It will tell you more about where GTM is headed than another article will.
Explore the Customer Superhumans →
The question worth sitting with
What buying experience does your brand want to be known for in 2027 and beyond?
Because if you don’t decide, your 2018 playbook is deciding for you.
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