AI Builders

Why EverWorker targets "boring billion-dollar companies" | Anton Antich

Most AI companies in 2023 raced to own a vertical. EverWorker made the opposite bet — build a horizontal platform that lets anyone create agents for any purpose, no code required. In this episode of BUILDERS, ⁠Anton Antich⁠ [https://www.linkedin.com/in/aantich/], CPO and Co-Founder of ⁠EverWorker⁠ [https://everworker.ai/], gets into what it actually takes to sell AI inside enterprises that are stuck between the hype and the reality, why he's making the case against SaaS entirely, and how an early PLG motion gave way to deep consultative selling once they realized the market wasn't where Silicon Valley thought it was. Anton helped scale a company from $0 to $1B ARR — and he's direct that most of what he learned there no longer applies. Topics Discussed: * Why the $0–$1B scaling playbook is obsolete in the AI era * EverWorker's pivot from PLG to enterprise consultative selling * Targeting "boring billion-dollar companies" as a deliberate ICP * Why most AI pilots never reach production — and the services motion that fixes it * The org-chart model for AI agent teams and the "Chief of Staff" product * The case for replacing SaaS entirely with agents, databases, and markdown files * Going down-market in 2026 and why community is the lead growth channel * Why instant product access has replaced "contact us for a demo" as the conversion standard GTM Lessons For B2B Founders: * Audit your team's DNA before choosing your GTM motion. EverWorker launched PLG, then quickly realized their entire founding team came from enterprise — Microsoft, VMware, Veeam. The pivot wasn't a failure; it was an honest read of where their unfair advantages actually lived. Before committing to a motion, map your team's network, sales instincts, and domain depth. Those signals will outperform market trend-chasing every time. * Build a services layer or watch your pilots die. The gap between AI pilot and production is where most deals go to die — Anton cites the widely-reported stat that the vast majority never make it through. EverWorker's solution was to build a services organization that identifies two or three mundane, high-friction processes — Anton's example is data entry, work humans find demeaning and AI handles well — automates them fast, and uses that visible win to build organizational trust. The services layer isn't a concession. For complex AI sales right now, it's the mechanism that actually converts pilots into production. * Your ICP should be defined by who won't default to "we'll build it ourselves." EverWorker learned this the hard way in enterprise. Walk into a Fortune 500 or a tech-forward company and IT shows up in the room and kills the conversation. Anton's team shifted toward what he calls "boring billion-dollar companies" — industries doing real, essential work that don't get the spotlight and can't afford to staff AI expertise internally. These buyers need the outcome, not the platform, and they don't have an internal team to rationalize building around. That dynamic is a structural GTM advantage. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership.⁠ www.FrontLines.io⁠ [http://www.frontlines.io] The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.⁠ www.GlobalTalent.co⁠ [http://www.globaltalent.co] // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here:⁠ https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM⁠ [https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM]

How Yutori landed enterprise contracts without a sales team by letting prosumer word of mouth do the work | Abhishek Das, Co-CEO at Yutori

Yutori⁠ [https://yutori.com/] is building web agents — AI that can monitor, navigate, and eventually act on the web on your behalf. Their first product, Scouts, launched in beta in June 2024 with one deliberate constraint: read-only web monitoring. No booking, no form-filling, no write actions. Just signal extraction from the open web. That narrow framing, paired with a $25K launch video that went viral on Twitter, drove 20–30K waitlist signups in a single week. M1 retention held above 80%. Enterprise contracts followed — entirely bottom-up, entirely unsolicited. In this episode of Unicorn Builders, Co-CEO Abhishek Das breaks down the thinking behind all of it. Topics Discussed: * Why scoping Scouts to read-only monitoring at launch was a GTM decision, not just a product one * The $25K launch video that went viral — what was in it and why it worked * How unsolicited enterprise contracts emerged from a prosumer product * Running two parallel GTM motions simultaneously with no dedicated marketing team * How hackathons became a developer acquisition channel * The browser automation API: a separate product with a separate motion, and why the two audiences cross-pollinate * What's next: authenticated browsing and write-action agents currently in alpha GTM Lessons For B2B Founders: * Constrain your launch scope to match what you can actually deliver. The AI agent space is full of products that promise to do everything and fail at anything. Yutori's answer was the inverse: launch Scouts as read-only monitoring only — no purchasing, no reservations, no form submissions. Abhishek was explicit that this was intentional: lower stakes for errors, a cleaner value prop, and a more honest promise to early users. The constraint wasn't a limitation — it was the pitch. If you're launching in a crowded category where trust is already eroded, scoping tightly is a competitive move. * Let retention data — not your roadmap — trigger monetization. Scouts launched free with no fixed plan to charge. When M1 retention held above 80%, the team pulled their monetization timeline forward and shipped a flat monthly subscription. No elaborate pricing research, no staged rollout. The data gave them the signal. For founders debating when to introduce pricing: retention is the clearest leading indicator that your product has earned the right to charge. Set a retention threshold before you launch, and let it make the call for you. * A $25K launch video beat the market — because the message did the work. The video was Abhishek on camera, directly explaining what Scouts can and cannot do. No cinematic production. It went viral because prominent builders — Guillermo Rauch from Vercel, Scott Belsky — reshared it organically. Abhishek is candid that going viral involves luck and that Twitter feels significantly more saturated today than it did at launch. The takeaway isn't "spend $25K on a video." It's that precise articulation travels further than high production value, and distribution through trusted voices matters more than raw reach. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership.⁠ www.FrontLines.io⁠ [http://www.frontlines.io] The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.⁠ www.GlobalTalent.co⁠ [http://www.globaltalent.co] // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here:⁠ https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM⁠ [https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM]

How Cassidy achieved 90% content performance consistency across TikTok and Instagram | Justin Fineberg

Justin Fineberg⁠ [https://www.linkedin.com/in/justin-fineberg/] built a 500,000+ follower audience on TikTok and Instagram before launching ⁠Cassidy⁠ [https://www.cassidyai.com/], an AI automation platform for non-technical users. By consistently creating content about AI and technology, he turned inbound interest into his initial customer base and market validation. In this episode of BUILDERS, Justin breaks down how he leveraged short-form video to identify product opportunities, the mechanics of maintaining authentic audience relationships while monetizing, and how to transition from social-led distribution to scalable B2B SaaS go-to-market. Topics Discussed: * Leveraging ChatGPT's launch as an inflection point to ride mainstream AI interest * Converting consultant requests into product insights and early customer signals * The platform mechanics of TikTok vs Instagram for B2B content * Transitioning from 100% social-sourced revenue to multi-channel B2B sales * Building repeatable content systems that survive founder time constraints * Testing product messaging and features through content before formal launch GTM Lessons For B2B Founders: * Timing content focus with market inflection points compounds growth * Inbound consulting requests are product requirement documents in disguise * Content systems must be friction-free or they'll die under operational load * Good content transcends platform-specific algorithm hacking * Social distribution creates unfair launch advantages, not permanent moats // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership.⁠ www.FrontLines.io⁠ [http://www.frontlines.io] The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.⁠ www.GlobalTalent.co⁠ [http://www.globaltalent.co] // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here:⁠ https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM [https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM]

How Positron AI is driving sales ahead of product | Mitesh Agrawal

Positron AI is a 2+ year old silicon company targeting decode-heavy AI inference workloads where memory bandwidth, not compute, is the bottleneck. Launching end of 2025/early 2026, their architecture delivers 2TB of on-chip memory capacity versus Nvidia Rubin's 0.4TB—enabling 3-5x better performance per dollar and per watt for reasoning models, code generation, and video generation. In this episode, ⁠Mitesh Agrawal⁠ [https://www.linkedin.com/in/mitesh7/] shares how ⁠Positron⁠ [https://www.positron.ai/] identified the memory bandwidth gap in a market where Nvidia controls 90%+ share, why they're prioritizing anchor customer commitments over product completion, and the hard lessons from Lambda Labs about rapid iteration and customer-driven optionality. Topics Discussed: * Positron's technical approach: focusing on memory bandwidth and capacity over compute for inference workloads * Why decode-heavy applications (reasoning models, video generation, code generation) are becoming memory-bound * The challenge of selling silicon to hyperscalers when Nvidia controls 90%+ of the market * Building optionality into product strategy: air cooling vs. liquid cooling as unexpected GTM advantage * Learning to sell hardware before the product ships and why anchor customers matter * Lambda Labs experience: lessons on rapid iteration and thoughtful hiring during hypergrowth * Maintaining engineering-centricity: 47 of 50 employees focused on product development GTM Lessons For B2B Founders: * Find technical bottlenecks in high-growth markets: Positron identified that memory bandwidth wasn't scaling as fast as compute, creating a bottleneck for inference workloads. While Nvidia dominates with 90%+ market share, they optimize for training revenue. B2B founders should analyze where dominant players are constrained by their own economics or existing roadmaps, then build specifically for those underserved segments. * Markets default to oligopoly, not monopoly: Mitesh observed that customers actively seek alternatives even when one vendor is superior. "Markets want oligopoly structure to exist," he explained. B2B founders shouldn't be discouraged by dominant incumbents—customers want optionality for leverage, supply chain resilience, and risk management. Position yourself as the credible alternative in specific use cases. * Discover optionality through customer conversations: Positron initially pitched performance per watt without realizing air cooling capability was a major advantage. Only after selling their first product did they learn customers valued deploying in existing data centers without infrastructure overhauls. B2B founders should systematically debrief early customers to uncover which features solve problems you didn't anticipate. * Sell before shipping in hardware: The biggest priority between now and product launch is securing anchor customers willing to commit purchase orders. "If you have someone to build for, the fillip it gives the engineering team, the confidence it gives operations and supply chain vendors—we underwrite that," Mitesh emphasized. Pre-sales derisk production, prove demand, and create momentum. * Build storytelling into technical sales: Convincing customers to buy unshipped hardware requires months of narrative work. "It becomes like, if I sell it to you, why will it be useful to you? Is it going to save cost? Attract new customers? Drive growth?" Success means co-creating the internal business case your champion will present. * Maintain rapid iteration cadence: Nvidia ships every 12-15 months versus the industry standard of 3-4 years. "If you tell me that in 10 years you've launched 10-12 products in silicon, I will give much more probability we will be successful," Mitesh stated. * Delay non-engineering hires until product proves itself: With 47 of 50 people in engineering, Positron has consciously prioritized product over go-to-market. "It was a very conscious decision," Mitesh emphasized. For deep-tech companies, this focus ensures you can actually deliver before scaling sales.

Why aiOla targets CFOs — not IT buyers | Amir Haramaty, Co-Founder at aiOla

aiOla is pioneering speech-to-data technology that transforms unstructured speech into actionable data for enterprise operations. As a serial entrepreneur on his sixth startup, Co-Founder ⁠Amir Haramaty⁠ [https://www.linkedin.com/in/amirharamaty/] built ⁠aiOla⁠ [http://www.aiola.ai] after witnessing firsthand how traditional AI implementations fail to deliver ROI in enterprise settings. The company has developed proprietary technology that achieves near-100% accuracy in challenging environments with heavy jargon, multiple languages, and difficult acoustics. With strategic investors including a major airline and partnerships with Nvidia, Accenture, and USG, aiOla is addressing the fundamental challenge that 95% of enterprise AI pilots fail to show value by focusing on immediate, measurable ROI through speech-based data capture. Topics Discussed: * The genesis of aiOla from consulting work revealing AI's implementation gaps in traditional enterprises * Solving the triple challenge of speech recognition: accuracy in jargon-heavy environments, separating signal from noise, and converting speech to structured workflow data * aiOla's "jargonic" approach: creating hyper-personalized language models for specific processes without retraining * Early customer acquisition through serendipitous encounters and demonstrating immediate ROI * Vertical expansion strategy from food manufacturing to aviation, travel, hospitality, and retail * Channel partnership strategy refined from previous startups to achieve scale * The shift from convincing customers about speech technology to being pulled into diverse use cases * Building the aiOla Intelligate orchestration layer to dynamically select optimal speech recognition models GTM Lessons For B2B Founders: * Make CFOs your best friend, not IT departments: Amir explicitly targets CFOs rather than IT as primary buyers because "it doesn't matter how small or big you are, you still have to do more with less." While IT serves as facilitators, CFOs control budgets focused on operational efficiency and ROI. B2B founders should identify which executive truly owns the pain point and budget authority, even if IT will implement the solution. * Deploy capital strategically to remove obstacles before they emerge: aiOla convinced their airline investor to provide working capital specifically to fund POCs for prospects without existing budgets. This eliminated the "we don't have pilot budget" objection before it arose. B2B founders should proactively identify and neutralize common barriers in their sales process, whether through creative deal structures, proof-of-concept funding, or implementation support. * Prioritize instant ROI over long-term transformation promises: Amir explicitly avoids "digital transformation" conversations, instead selecting use cases delivering "biggest impact within shortest period of time with minimum obstacle possible." The airline baggage tracking example saved 110,000 hours immediately, creating momentum for expansion. B2B founders should resist selling comprehensive transformation and instead identify narrow use cases with quantifiable, rapid returns that create internal champions. * Replicate proven use cases across customers rather than customizing: Once aiOla achieved success with specific applications like CRM data entry or pre-op inspections, they "stop, print, replicate" rather than reinventing for each customer. This approach reduced a two-hour inspection process to 34 minutes in food manufacturing, then replicated across industries. B2B founders should document successful implementations as repeatable playbooks and resist the urge to over-customize for each prospect. * Channel success requires speaking the partner's economic language: When working with telcos, Amir demonstrated that his solution increased ARPU by 34% and reduced churn by 17%—the only two metrics telcos prioritize. He built predictable models showing exactly how many units each channel rep would sell by geography.