Topline

Amanda Kahlow, Founder & CEO of 1mind, joins Sam Jacobs, AJ Bruno, and Asad Zaman to break down how an AI-powered solutions engineer named Nigel took 33% of the talk time in a two and a half hour enterprise meeting and produced a $278,000 deal. Topics include why AI aimed at efficiency gains misses real revenue impact, Amanda's prediction that marketing, sales, and customer success collapse into one function within 12 months, and why AI adoption has to be top-down instead of bottoms-up. Plus, the 15 agents running behind every superhuman, a 98% accuracy bar measured by live evals, whether agents will negotiate with other agents on the buy side, and a bulls versus bears round on Salesforce, sales dinners, and the health of the average go-to-market team.
Key Takeaways:
- Most go-to-market teams are pointing AI at the wrong layer. Better forecasting, faster research, and cleaner dashboards make the people you already have marginally more productive, which is not where the revenue is. As Amanda Kahlow, Founder & CEO at 1mind, framed it: "My thesis is that buying and selling happens in the conversation." Everything built around the conversation to enable a seller is, in her words, yesterday's workflow.
- Trust, not novelty, is what moves an enterprise deal. Amanda flew a red-eye to Austin for a second meeting with a CPO and CMO, brought a superhuman named Nigel on screen, and watched the room turn to the AI for depth even she could not provide. As she told it, "the CPO was like, Amanda, shut up, basically. I wanna talk to Nigel." The meeting scheduled for an hour ran two and a half, and produced "a $278,000 deal from one in-person meeting going through procurement in one week". Her read on why it worked: "People say people buy from people. You buy when you trust."
- The human face on an AI agent is a click-through device, not the value. Amanda's verdict after a year of selling them: "The face is a novelty." 1mind drops the face entirely on live calls because the movement distracts. The important part is the conversational AI, where "each superhuman has roughly 15 agents working behind the scenes." One handles small talk, another loads the live demo, another builds the perspective slide a human seller would normally take a week to produce.
- Bottom-up AI adoption is where the value leaks out. Amanda's pushback on the idea that people who use AI will simply eat the people who do not: telling every individual to go be more efficient produces slop and no measurable gain, while the real impact, in her words, "is going to come at the top down when we think about restructuring the org".
Connect with the Hosts & Guests:
Host: Sam Jacobs, CEO at Pavilion - https://www.linkedin.com/in/samfjacobs/
Host: AJ Bruno, CEO at QuotaPath - https://www.linkedin.com/in/ajbruno3/
Host: Asad Zaman, CEO at STA - https://www.linkedin.com/in/azaman1/
Guest: Amanda Kahlow, Founder & CEO at 1mind - https://www.linkedin.com/in/amandakahlow/
Topline is more than a YouTube Channel:
Subscribe to Topline Newsletter: https://toplinemedia.substack.com/
Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech: https://www.joinpavilion.com/topline-podcast
Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack
Chapters: 
00:00 Introducing Amanda Kahlow
00:59 Building Superhumans At 1mind
03:24 Why Efficiency Gains Miss The Point
06:04 GTM Functions Collapse In 12 Months
08:48 The Ghost Note Debate
15:20 Nigel Takes 33% Of Talk Time
20:41 The Face Is Just Novelty
22:27 Fifteen Agents Behind One Superhuman
38:46 Compute Costs And AI Margins
41:19 How Accurate Are AI Agents?
47:08 Positioning An AI Company
52:13 When Agents Negotiate With Agents
53:54 Will CSM Jobs Survive?
57:56 Bulls and Bears
1:06:15 Boards, 6sense, And Burnout

AI isn't just changing sales. It's completely rewriting how revenue teams operate.
In this episode of Topline Spotlight, Sam Jacobs sits down with Justin Shriber, CEO of Terret AI, to break down how modern revenue organizations are using AI to improve forecasting, shorten sales cycles, ramp reps faster, and operationalize winning sales behavior in real time.
Justin shares:
Why traditional sales enablement is broken
How AI helped reduce rep ramp time by 40%
The "answer-to-action" engine powering modern RevOps
The hidden dangers of decentralized AI adoption
Why companies are struggling with inconsistent AI-generated data
The real debate: build your own AI stack vs buy from vendors
How leading teams are using AI agents today
One of the most interesting conversations in GTM right now.
If you're a CRO, RevOps leader, founder, or GTM operator trying to understand where AI is actually delivering value, this episode is worth your time.
Chapters:
00:00 Intro
00:40 Meet Justin Schreiber and Terret
04:17 How AI is changing sales productivity
06:07 The biggest problem in revenue execution
09:37 Why great strategies never get executed
11:01 Building AI that's secure, accurate, and scalable
13:32 Buy vs. build: The future of enterprise AI
16:25 Why AI needs centralized governance
17:35 Jurassic Park, AI agents, and organizational chaos
20:15 Justin's biggest inspirations for building great companies
22:58 Where to find Justin and Terret
Try Terret: terret.ai

Tim Rutten, CMO of Backbase, the €2.5 billion Amsterdam tech company whose AI-native Banking OS powers 120+ banks worldwide, joins Sam Jacobs, AJ Bruno, and Asad Zaman with the clearest AI ROI numbers we have heard on the show: double the pipeline on 25% less budget. Topics include the custom go-to-market operating system his team built on the Vercel stack, why real bank deployments are 99% deterministic, the 90% cost reduction banks are finding in customer care, and why most enterprise workloads do not need frontier-model intelligence. Plus, where the AI bubble breaks, what happens to judgment and taste when anyone can generate output, and a bulls-versus-bears round on LinkedIn, banking apps, and sales spiffs.
Key Takeaways:
- Backbase's marketing org runs on GTMOS, a custom go-to-market operating system built on the Vercel stack and wired into Salesforce and the company's finance tools, and the numbers behind it are specific. As Tim Rutten, CMO at Backbase, put it: "Double the pipeline, 25% head cut on my budget... So with 25% less budget, I'm actually still doubling the pipeline." The unlock came from rebuilding how the team works rather than layering tools on top of it.
- Shipping AI into a regulated industry means using AI more narrowly than you might expect. On what real bank deployments look like, Tim Rutten said: "the actual implementations are almost 99% deterministic, and there's this one little percent that actually gets them to gain, to reason at the right moment in time." That same architecture caps the bill, because most banking workloads are repetitive and rule-bound. But the same rigor can net fantastic results from AI in broader applications as well.
- Backbase treats AI slop as an architecture problem, containing content generation inside hard boundaries. Per Tim Rutten: "You have tone of voice, you have guardrails that we don't have AI slop. There's like 22 rules that are applied. If they don't check out, the agent needs to rewrite and continuously learns to rewrite." The human half of the risk is harder to engineer around, as Asad Zaman, CEO of Sales Talent Agency, framed it: "a lot of people that didn't have a skill are using AI for that thing. And if you didn't have a skill in an area or judgment or taste in that particular area, you have no mechanism to stress test the quality of what is coming out."
- On how the AI bubble pops, Sam Jacobs, CEO of Pavilion, put the risk on the business model sitting underneath the capex: "if everybody presumes the way that all these companies make money is selling tokens… and then all of a sudden it turns out selling tokens is a really terrible business. Well, then that's a thing that would compress." Tim Rutten lands in a similar place on timing while staying long on the outcome: "a little bit bearish on timing, massively bullish on the future… it will happen nevertheless, but it's going to be a very rocky ride."
Connect with the Hosts & Guests:
Host: Sam Jacobs, CEO at Pavilion - https://www.linkedin.com/in/samfjacobs/
Host: AJ Bruno, CEO at QuotaPath - https://www.linkedin.com/in/ajbruno3/
Host: Asad Zaman, CEO at STA - https://www.linkedin.com/in/azaman1/
Guest: Tim Rutten, CMO at Backbase - https://www.linkedin.com/in/timrutten/
Topline is more than a YouTube Channel:
Subscribe to Topline Newsletter: https://toplinemedia.substack.com/
Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech: https://www.joinpavilion.com/topline-podcast
Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack
Chapters:
00:00 Introducing Tim Rutten
03:11 Inside Backbase And 120 Banks
09:42 90% Cost Cuts In Call Centers
12:04 Why The Application Layer Wins
15:23 Europe, The US, And Regulation
21:50 Where The AI Bubble Breaks
27:24 Why Banks Skip Frontier Models
34:34 Bank Budgets Shift To AI Native
38:23 Real ROI At Lloyds And JPMorgan
44:31 Quiz Pro Quo
49:37 GTMOS, The Go To Market OS
52:02 Double Pipeline On 25% Less Budget
53:53 Judgment, Taste, And AI Slop
1:06:15 Real Time Marketing By Christmas
1:09:30 Bulls and Bears

Buyers stopped picking up the phone. They research on their own, ask their peers, and now they ask AI which vendors to consider before a single salesperson ever hears about it. So where does that leave marketers?
Sam Jacobs sits down with Alexander Kesler, founder and CEO of Infuse, to break down the dark funnel and what it means for B2B demand gen right now. They get into why most of the buying journey happens before you're ever contacted, how AI tools are generating "day one" shortlists on the spot, and why the real game is earning a spot on the day zero shortlist — the vendors a buyer already trusts no matter what ChatGPT says.
Alex has spent 25+ years building companies across marketing, media, and data, and is the author of two books on B2B marketing best practices. His advice for marketers comes down to one thing: stay flexible, read the research, and build the relationship before the buyer is in market.

What we get into:
Why the traditional B2B sales funnel no longer reflects how today's buyers actually buy
What the Dark Funnel is and why 80% of the buying journey happens before prospects contact sales
The difference between Day Zero and Day One shortlists and why every marketer needs to understand both
How AI and Generative Engine Optimization (GEO) are reshaping vendor discovery
Why building trust and thought leadership before buyers are in-market is the new competitive advantage
Alex Kesler's advice for modern B2B marketers on staying relevant in an AI-first world
Chapters:
00:00 Intro 00:36 Meet Alex Kesler and Infuse 03:10 The dark funnel explained 05:16 Why buyers don't want to talk to sales anymore 08:07 The AI buying journey and Day One shortlists 11:28 GEO: Winning recommendations from AI search 14:07 Day Zero vs. Day One: The new marketing playbook
16:06 Marketing 101 is making a comeback 16:27 Why ABM can limit your growth 17:35 The #1 trait every modern B2B marketer needs 19:20 Alex's leadership philosophy: Do the right thing 20:36 Where to find Alex and Infuse
Try Infuse: infuse.com

A rep says "follow up on that" on a call, then buries it under five more calls and a late-night inbox. Three days later the deal's gone cold, but the CRM still says it's live. The manager forecasts off that. 

The CRO forecasts off the manager. The board asks the CEO if anyone actually has a grip on the number. The whole thing was built on a promise nobody kept. 
Adam Liska worked on the early Gemini models at Google DeepMind before leaving to close that gap. His company, airspeed, just raised a $20M Series A on a bet that "revenue execution" is the next real category, not another tool that logs calls and calls it intelligence. 
Sam Jacobs traces the full arc with him: DeepMind to founder-led sales to the unglamorous work of turning a founder's instincts into a system a team can actually run. 
What we get into: 
Why "follow up on that" breaks the forecast chain from rep to CRO to board What "revenue execution" means, and why it isn't revenue intelligence with a new label 
Whether you own the interface or hand it to a chat model and live as middleware 
The Nashville lunch that became airspeed's first six-figure deal 
The real sequence from founder-led to scalable: capture the data first, then build the playbooks 
Owning your data instead of renting Salesforce's architecture 
The modern Turing test, AI-native orgs, and where the back office is headed
Chapters:  
00:00 Intro
00:44 From DeepMind to airspeed, and the $20M Series A 
01:30 "Follow up on that" — the execution gap that breaks forecasts 
04:00 What category is this? Revenue execution, defined 
05:40 Headless vs. owning the interface 
08:00 The origin story: leaving DeepMind in 2022 
11:39 Founder-led sales and the Nashville lunch that closed a six-figure deal 
13:18 The hard part: turning founder-led into a repeatable system 
14:14 Why they recorded everything from day one 
16:35 Owning your data, and where the source of truth lives 
19:03 The playbook: data first, then hierarchical playbooks 
20:52 Influences: the modern Turing test and AI-native orgs 
23:37 Where to find airspeed 
Try airspeed: goairspeed.com