Dan Yeates has helped build sales teams at some of the fastest-growing software companies around. He started out selling £5k road bikes in his family's shop, dropped out of a maths master's with a UBS grad job lined up and made 100 cold calls a day in recruitment before moving into tech at AppDynamics. He was the first commercial rep in Europe at Harness, then helped ClickUp grow from $50M to $350M ARR. He's now Sales Director at Metaview, the AI recruiting platform that's just raised a $60M Series C led by Insight Partners.

In this episode Dan explains how he tests whether a champion can actually influence a deal, why a rep with two years in enterprise might have worked only 25 opportunities, and why cold calling works better the more senior the buyer. He also covers how ClickUp mixed product-led and sales-led growth, how Metaview's AI agents and Filmore (its recruiting coworker that lives in Slack) are changing hiring, and why the seller's job is moving from explaining the product to helping buyers build the business case.

We also talk about the hardest stretch of his life. Three months into his job at Harness, Dan was diagnosed with leukaemia. He worked through his treatment and had to give up on leading teams for a while before he found his way back.

If you're building a sales team, moving into enterprise or trying to get better at building champions, this one's worth your time.

Laura Bartkiewicz is a Senior Sales Manager at Ironclad, the contract lifecycle management (CLM) platform that passed $200 million in ARR in February 2026. She graduated in Boston as the housing market collapsed, started in recruitment, then used LinkedIn to find a visa sponsor and move to Sydney. There she joined LinkedIn's sales team in 2014, two years before the Microsoft acquisition, running outbound with Outlook mail merges, Salesforce and cold calls. She later moved to London with Beamery, took her first management role at Deputy, and joined Figma as one of its first 20 hires in London, where she built the mid-market team under Pierre Berlin and helped hire for the Berlin and Paris offices.

Laura breaks down what she hires for in a sales rep: self-awareness, ambition, drive, resilience, optimism, and enough emotional intelligence to read a room on a video call. She describes her management style as direct, blunt and friendly, with clear expectations and real accountability. She explains why selling is a team sport across solutions engineers, architects and executives, and why she trains reps to play chess, not checkers: plan several moves ahead and keep the client aligned with a long-term vision.

She also gets into what Ironclad does and why Salesforce chose it after trialling eight CLM platforms. Ironclad sits inside the CRM so reps never leave Salesforce to manage redlines, and it routinely cuts contract cycle times by more than half. Under CEO Dan Springer, formerly of DocuSign, the company has hired ex-Google CTO Sunita Verma and CPO Herman Man to ship new AI agents every quarter. On AI in sales, Laura's view is simple: trust and relationships still close deals, and AI is the velocity layer on top, handling follow-ups, tightening agendas and using tools like Gong to flag gaps in a deal cycle. Outside of work, she talks about investing her commissions every quarter into the tech companies she used daily, taking a sabbatical after her father passed, and why 20 nos will get you a yes.

If you're moving from SDR or AE into sales management, hiring your first reps, selling B2B SaaS into Salesforce customers, or working out where AI actually fits in an enterprise sales cycle, this one's worth your time.

Conor Hyland is Regional Vice President of GTM for EMEA at ComplyAdvantage, the AI company helping enterprises fight financial crime. He started his career selling on the shop floor at Ted Baker, worked across the Middle East, then moved into SaaS before joining GoCardless as an Enterprise Account Executive and progressing into sales leadership. He later joined ComplyAdvantage to help build its sales-led growth motion, hire the team and bring more process and rigor to how the business goes after larger accounts.

Conor breaks down why the old idea of a high-performance sales culture, built on pressure, micromanagement and fear, gets performance wrong. For him, the foundation is trust: clear standards, psychological safety, shared goals and a team that is willing to challenge each other because everyone knows it is in service of getting better. He also explains the ICE framework he uses when hiring, prioritising intelligence, character, coachability and entrepreneurship over simply choosing the candidate with the most experience, and why "trajectory beats position" when assessing talent.

He also gets into why ComplyAdvantage still invests heavily in cold calling despite the rise of automated outbound, how his team uses data to identify exactly where a rep's conversion is breaking down before coaching them, and why enterprise sellers need to arrive at an account with a genuine point of view before they ever make contact. Outside of sales, Conor talks about reading roughly a book a week for several years, learning to become more vulnerable as a leader, and how becoming a father changed his definition of hard work from always being available to being deliberate with his time.

If you're building a sales team, hiring for potential rather than pedigree, trying to create a high-performance culture without falling back on pressure and micromanagement, or figuring out what great enterprise sales leadership looks like today, this one's worth your time.

Will Tomlins is Regional Vice President of Mid-Market and Enterprise Sales at Wiz, the cloud security platform Google acquired for roughly $32 billion in the its largest acquisition to date. He spent almost 11 years at Canon, then three years at AWS leading commercial and financial services sales teams. He joined Wiz in June 2025, weeks after the Google deal was announced, and was still there nine months later when it actually closed.

Will breaks down why "pain and champion" remain the two things every deal lives or dies on, even inside a MEDDPICC, playbook-driven org like Wiz, and why deals that tick every box on paper still die without the EQ to find them. He talks about how buyer conversations have shifted from passive infrastructure security to visibility and governance as Wiz pushes into AI security, tracking developers who deploy code and adopt AI tools without anyone signing off. He also explains "clock speed," his own hiring bar for how fast someone learns something and puts it into practice the same day, over people who just show up with big numbers on their resume.

He also gets into why he still sits in on economic-buyer meetings and no-go conversations as an RVP instead of stepping back, the two Wiz values, "win together" and "lead by example," that actually show up inside deals rather than on a slide, and the risk balance between company and employee he thinks is the real ingredient behind reps doing unbelievable things.

If you're leading enterprise sales through long, multi-stakeholder cycles, trying to figure out what AI is actually doing to cybersecurity buying, or thinking about what's left for sales leaders to teach once the process is automated, this one's worth your time.

Jay Mirpuri leads GTM at Light, an AI native finance platform, and he built its cold calling program from nothing into a team that books 30 to 35 meetings a week. Before that, his first startup failed. He built Alchemy, an AI marketing agency, moved to London to launch it, and struggled without local connections or a clear customer profile. So he cold messaged Jonathan Sanders, founder of Light, using a three pronged pitch built on his own founder story and a shared CFA Level 1. It worked, and he became Light's first sales hire.

Light replaces the patchwork of Xero instances and 12 month NetSuite rollouts that scaling companies get stuck with, closing a $13M seed from Atomico and a $30M Series A in September 2025 out of its Copenhagen HQ. Jay breaks down why cold calling still beats email in B2B sales when most competitors have given up on it, how his eight BDRs earn the right to pitch inside the first ten seconds, and the thought leadership events that built his earliest pipeline.

He also gets into why he changed his mind on hiring technical BDRs, how Light's Astra system catches financial anomalies without the hallucination risk of generative AI, and the story of Keyshot, a client that scaled from $5M to $30M ARR with one CFO and a part time bookkeeper.

If you are building an outbound sales team from zero, wondering whether cold calling still works, or curious where AI in finance is heading, this one is worth your time.

Callum Matthews-Mackay leads sales at Onetrace, the compliance software fire protection subcontractors use to prove installations were done right, turning what used to be a paperwork scramble into a one click report. Before Onetrace, he spent over a decade selling into industries nobody else wanted to touch: corporate partnerships at Macmillan Cancer Support (Nestlé, Morrisons, a four year Pizza Express deal, over £1m in new business), the £700bn interior design trade at eporta, and hospitality partnerships with Best Western, Macdonald Hotels and Searcy's at Bridebook.

In this episode, Callum breaks down what it actually takes to build pipeline into an audience that's on scaffolding, not checking inboxes. He gets into why cold email dies in construction, how regulation like the Building Safety Act turns into a genuine sales trigger, and what it means to earn trust when your software is tied to life safety. He's candid about what hasn't worked, not just what has, and talks through building a sales team from scratch in a market this hard to sell into.

We also get into where AI is actually pulling its weight in his go to market motion versus where it's just noise, and the one lesson from Bridebook that's reshaped how he leads a team today.

If you're selling into trade, construction or any hard to reach frontline audience, this one's worth your time.

Max Greenbury is part of OpenAI's go-to-market team, working the startup side with around 14 later-stage accounts from the UK to Israel and Lithuania. He didn't get there in a completely straight line (although it was quite straight): three years running his own subscription platform for secondhand clothing came first, three years on AWS's startup team, then Google selling into regulated enterprises.

In this episode, Max opens up how OpenAI actually sells and why enterprise and startup deals are almost different jobs. Enterprise sales is a stakeholder maze, won by surfacing "unrealized pain" the buyer hasn't named yet. Startups are the opposite: founders are already pushing the models past their limits, so the job becomes optimizing for latency and cost, then routing what's missing straight back to OpenAI's research team. Max also breaks down OpenAI's AI-first culture, where tools like Codex handle data pulls and CRM updates before a human touches them, and why Generative Engine Optimization, showing up as the answer ChatGPT gives when someone asks for a recommendation, is becoming a real go-to-market priority.

Five years out, Max thinks AI takes over the admin grind of selling. What it won't replace, he argues, is trust. If you sell into startups or enterprise, or you're figuring out where GEO fits your own GTM strategy, this one's for you.

Nick Taylor has spent his career inside three of London's most important AI and fintech companies. He worked with high-growth neobanks like Monzo and Revolut during his time at Onfido, watching the company pivot from background checks into an identity verification leader. He then joined Synthesia through its hyper-growth phase, helping scale the team from 40 people to over 600 as the AI video platform went global. Now he leads customer success at Granola, the AI notetaker that's quickly becoming something bigger.

In this episode, Nick explains why he sees customer success as a flexible role built around one goal: getting clients to value as fast as possible so renewals take care of themselves. He talks about Granola's real ambition, building a "central cortex" for business context by capturing what actually gets decided in internal and external meetings, and why LLMs only get useful once they're fed an organisation's specific context. He also shares his "landlord" analogy for handling unhappy customers: listening for the human frustration behind a technical complaint before jumping to a fix.

Nick also gets into why he's changed his mind about needing deep technical expertise to build good products. In an AI-driven world, he argues, having more ideas matters more than having more code.

If you're thinking about customer success, AI-native tools, or what it takes to scale through hyper-growth, this one's worth your time.