BIG IDEAS BY NEW ECONOMIES

Ollie Forsyth

Welcome to BIG IDEAS by NEW ECONOMIES - a show where we learn how the most iconic founders have turned crucible moments into global companies. www.neweconomies.co

  1. 1h ago

    Webflow

    Subscribe to stay ahead of technology trends. Never miss future editions. Linda Tong, CEO of Webflow, joins us to explain how she's leading Webflow's transformation from a $4 billion website builder into an agentic marketing platform, why she believes the internet is filling up with AI-generated "garbage" from people who never asked what's worth building, and how she thinks about winning in a market where AI capability itself isn't a moat. During the episode, we also explore an interesting trend and tension: what it takes to build “taste” into AI-generated products when every model can now write clean code but none of them can reliably read a brand. Linda also shared how enterprise pricing negotiations are exposing the gap between what companies pay for and the value they actually get, and how she expects websites themselves to evolve from static pages into something closer to Google Maps: constantly reinteracting with and reshaping around each visitor. About Webflow Webflow gives every team the tools to build, manage, and grow a website that drives real revenue. Founded in 2013 by Vlad Magdalin, Sergie Magdalin, and Bryant Chou (via Y Combinator), it’s grown from a niche tool for freelance designers into infrastructure used by 300,000+ businesses. The company raised a $120M Series C in March 2022 at a $4B valuation and has taken in over $330M total. Watch now: Linda Tong, CEO at Webflow Watch or listen now across YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Linda Tong(2:04) The Current State of Building(2:40) What's Changed for Webflow in the Last 12 Months?(6:06) Base44 Reaches 10M Users and Lovable Raises $400M(8:02) How to Support Builders in This Era(9:18) How Do You Select Which AI Model to Partner With?(12:00) Is Taste the Next Biggest Moat?(13:41) Are Agentic Co-Workers Next?(16:03) Webflow's Current Challenges(18:46) How to Navigate Human Change(21:08) The Change of Software Pricing(25:12) Inside the Webflow CEO Role(26:32) How Do AI Models Affect Product Roadmaps?(28:35) Where Does AI Go Next Over the Next 6-12 Months?(32:52) Will Websites Still Be Relevant?(34:25) Building Trust With Your Fanatical Users(36:25) How Linda Runs Webflow(39:14) A Winning Mindset(41:10) Are We Just 1% of the Way There?(43:23) Airtable Acquisition(45:09) Ollie Joining as Linda's Chief of Staff(47:19) Personal Time Out(48:20) Board Members(50:50) Where Does Webflow Go From Here? Lessons from this episode with Linda: 1. Linda can build an app with a prompt, but still can’t book a doctor’s appointment less than 6 months out.Right after saying AI has barely scratched the surface of solving real problems, Linda brings up trying to schedule an appointment and being told the system doesn’t open bookings for another 6 months, so she’d have to call back in 3 months just to schedule it. Her point: we’re maybe 5% of the way to AI actually mattering in daily life. 2. “Just have everything run agentically. Go watch Netflix.” She’s not buying it.Pushing back on the one-employee-plus-millions-of-agents narrative, Linda says AI still isn’t reliable enough to run unsupervised. You still need people reviewing and coaching the system regularly, and anyone claiming they’ve replaced their whole workforce with agents “is just not real.” 3. “I’m paying for a million seats but only 10 people actually get value out of it.”Her example of what’s broken in software pricing: when she sits in on procurement negotiations, this is the exact complaint she hears. She argues it’s a sign the pricing was never actually tied to value in the first place, and that the constant tough renegotiations are the tell. 4. Airtable sold for 2.5x revenue, after being privately valued at $11.5 billion.On how fast valuations are resetting: Airtable, a $500M-revenue company, got acquired at roughly 2.5x enterprise value, a fraction of the $11.5 billion it was last valued at privately. Her takeaway: “times are changing,” and the old rules for pricing a software company no longer hold. 5. Internet garbage: Only 200 million of the internet’s 1.2 billion websites are actually alive.When Linda joined Webflow four years ago, she looked at the market and found roughly 1.2 billion websites live on the internet, but only around 200 million were active businesses actually being used. She says that ratio hasn’t meaningfully moved since, even as AI makes it trivial to spin up more of the other billion. The ability has shifted to build fast, people have built a lot of websites but that doesn’t automatically translate to tangible value. 6. AI didn’t kill the SDR job. It turned “send more emails” into “review the AI’s calls.”Her clearest change-management example: an entry-level SDR used to be capped by how many calls and emails they could physically make in a day. Now an AI agent makes the calls and writes the emails, and the job becomes reviewing what the agent learned and deciding what to test next. 7. Her agents don’t do one task and stop. They run until the goal is hit.She contrasts most “agents” today, which complete a task and hand it back for a human to judge, with what she calls closed-loop agentic workers: give it an outcome like “drive this much pipeline,” and it writes the brief, launches the campaign, measures results, and keeps iterating on its own. Her live example is Webflow’s AO agent, which pushes content and schema changes to improve a client’s visibility on answer engines like ChatGPT, then measures and repeats. 8. Pricing debates (subscription vs. seat vs. consumption vs. outcome) Her contrarian take: none of these pricing models are wrong, they’re just successive attempts to get closer to charging for the actual value delivered. AI just makes it possible to meter something closer to real value than ever before. Links Follow Ollie on X - https://x.com/ollieforsyth Follow Linda on X - https://x.com/YayLT Vist Webflow - https://webflow.com Episode Partner - Discover Harmonic, your go-to startup database - https://harmonic.ai Previous episodes include See all previous episodes here 👉 If you enjoyed this episode, help sustain our work by clicking ❤️ and 🔄 at the top of this post. Get full access to NEW ECONOMIES at www.neweconomies.co/subscribe

  2. 3d ago

    Pegasystems

    Subscribe to stay ahead of technology trends. Never miss future editions. Alan Trefler, Founder and CEO of Pegasystems, joins us to unpack how a 40-year-old, $6 billion public company is thinking about AI, why he refuses to charge customers for tokens, and what it actually takes to survive five generational shifts in technology without losing your edge. You might not know this about Alan, but Pega’s first two clients, Citibank and Bank of America, signed on in 1984 and are still customers today. He shared why he thinks the real risk in enterprise AI isn’t the technology, it’s the incentive: “These guys are a little bit like drug dealers… passing out packets of tokens and getting people hooked.” About PegasystemsPega is an enterprise workflow automation company Alan founded in 1983 on the tagline “build for change.” The company has been public for 30 years, does close to $2 billion in annual revenue with over 5,000 employees, and serves roughly 800 of the world’s largest enterprises, including four decades of continuous relationships with the same banks it started with. Watch the episode now Throughout this episode, we also cover why Pega put a literal “no token cost” badge on stage at Pega World and how it can actually afford that promise, the vector database strategy Pega chose over building its own foundation model so it can move freely between OpenAI, Claude, and Gemini, why Alan thinks the “cost cap on tokens” debate misses the point because competition, not government, is what brings prices down, and the math behind why a workflow running on a CPU is thousands of times cheaper than a reasoning session on a GPU. As the SaaS apocalypse debate rages on, we asked Alan directly whether AI coding tools are about to eat Pega’s forty-year business. We learn why he thinks the real moat was never the code, “they can compete on code, but they can’t compete on trust” - why his succession plan is basically “I’m not leaving” (his words: “my exit strategy is going to be a pine box”), and much more. Available everywhere you listen to podcasts: YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Alan Trefler(2:23) What Is Pegasystems?(5:26) How to Build Trust Today?(6:32) Being Public for 30 Years(7:59) The First Year of Going Public(11:56) Navigating the Frothy AI Market (?)(14:00) Stock Price Ups and Downs(20:00) Measuring the Cost of AI Compute(22:30) Why Absorb the Cost of Tokens for Customers?(26:57) Will There Be a Cost Cap on Tokens?(28:02) Treating AI Models with Fungibility(31:14) The SaaS Apocalypse(34:35) Does AI Replace Trust?(35:37) Inside Pega's Opportunities & Challenges(39:14) New Tools Outpacing Entire Revenue Streams(41:50) AI Talent & Agent Managers(43:46) New Roles Being Hired Today(45:46) Succession Planning(47:04) Ollie Joins Alan as Chief of Staff(48:45) Preparing for an Earnings Call(50:05) Being a Hands-On Leader(52:28) What Alan Does Outside of Work (55:03) One Board Member You Would Have on Your Board (56:11) Alan's Legacy Lessons from this episode with Alan 1. Customers do not need to pay for tokens Alan’s explanation for why Pega doesn’t charge customers for tokens: design the recipe once in the test kitchen, serve it a million times, no need to reinvent the dish every order. Concrete framing of design-time vs. runtime AI cost. 2. “A token is just an example of the BS that’s going on”The token-vs-words rant, why calling it “tokens” instead of “words” obscures cost on purpose. 3. Bubblicious behavior "I think the reality is that a bunch of what we're seeing is I would describe as bubblicious behavior. And so there is going to need to be some reallocation and there will be corrections." 4. “My exit strategy is going to be a pine box”Some founders just keep going until the end of life and Alan said he is one of those. 5. The 27-slide self-congratulatory deckHis take on organizational culture and why he actively discourages “brilliant group” presentations. 6. Don’t go public too earlyPega was so advanced but also very early in their journey when they decided to go public. Looking back, Alan says - ‘‘Don’t go public too early’’ 7. Trust vs. transactional relationships“The people in transactional environments only show up when there’s a transaction.” Links Follow Ollie on LinkedIn: https://www.linkedin.com/in/ollieforsyth Follow Alan on LinkedIn: https://www.linkedin.com/in/alantrefler Visit Pegasystems: https://www.pega.com Episode Partner - Discover Harmonic, your go-to startup database: https://harmonic.ai Previous episodes include See all previous episodes here 👉 If you enjoyed this episode, support our work by clicking ❤️ and 🔄 at the top of this post. Get full access to NEW ECONOMIES at www.neweconomies.co/subscribe

  3. 6d ago

    Felicis Ventures

    Subscribe to stay ahead of technology trends. Never miss future editions. Aydin Senkut, Founder and Managing Partner at venture firm Felicis, joins the podcast at a pivotal moment in tech to unpack what’s happening across venture, whether LPs are concerned, and how to win as a firm in the current environment. You might not know this about Aydin, but he was actually one of the first employees at Google, working directly alongside Sergey Brin and Larry Page, with a key lesson: “Why the clearest signal from Larry Page wasn’t what he said yes to but the 80% of the time he said no.” About FelicisFelicis is a venture capital firm that backs iconic founders starting at Seed, with early bets on Notion, Canva, Shopify, Adyen, n8n, Supabase, and Mercor. Over 20 years, Felicis-backed companies have driven more than $300 billion in market value, and Aydin has appeared on the Forbes Midas List for 13 consecutive years. Watch Now - Investing In 50 Unicorns Throughout this episode, we also cover the origin of Felicis’s 1% founders pledge, a co-CEO’s idea borrowed from tennis mental coaching that now covers health therapy and coaching for 100+ founders with no strings attached; why Felicis is obsessed with “global resilience” and the four markets (space, defense, manufacturing, energy) big enough that 1% share still returns a fund; and the stat from Felicis’s own data showing the top 1% of exits have doubled in value every five years while the bottom 90% have stagnated. As venture faces its own AI challenges, we asked directly whether AI is coming for the junior analysts and associates learning the trade underneath Aydin. We learn why he thinks trust, not analysis, is the one thing AI can’t replicate, and why founders keep telling him they picked Felicis for the person across the table, not the term sheet, and much more. Available everywhere you listen to podcasts: YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Aydin Senkut(2:21) The State of Venture Today(3:49) About Felicis Ventures(6:35) Google's First Early Employees(8:09) Lessons from Larry and Sergey(10:11) Building Google from Nothing(13:10) Great Investors: Operators or Founders?(15:57) 13x on the Forbes Midas List(17:28) What Makes Felicis Successful(20:11) Navigating Crucible Bets(22:16) Characteristics of Unicorn Companies(25:22) Coaching Founders to Stay Disciplined(28:30) Longevity and Stewardship(32:56) The 1% Founders Pledge(40:21) Founders' Hardest Challenges Today(43:07) Building an Enduring Fund(46:52) From Meeting to Term Sheet(49:02) Inside Felicis(51:32) Are LPs Concerned About Venture?(57:28) AI and the Future of Young Venture Talent(1:00:29) The Opportunity for Emerging Managers(1:03:39) How Aydin Spends Time Outside Venture Lessons from this episode with Aydin 1. Being ruthlessly focus: “Cut nine things off your list” The core operating principle: it feels productive to work on 10 things, but real focus means having the courage to kill nine of them and go all-in on one. 2. “Your weakness can be your strength” Aydin wasn’t an engineer, never worked at a big tech company, and built a philosophy around not needing technical depth, just needing to understand what makes a company succeed. 3. Authenticity, trust, and doing the homework: “The personality of the investor really matters” Three concrete, teachable behaviors for building trust fast: no hidden layers, a track record of not going against people, and showing up with a prepared, original point of view. 4. Market-sizing lesson for founders and investors: “Chase markets where 1% share still wins” The math behind why Felicis is focused on “global resilience”: pick markets big enough that even a small share of them clears the bar for a great outcome. 5. Where does AI leave young talent in venture? Why he believes relationships, not analysis, are becoming the scarce resource in venture, and the “orchestra conductor” framing for how humans and AI should actually divide labor. Previous episodes include See all previous episodes here 👉 If you enjoyed this episode, support our work by clicking ❤️ and 🔄 at the top of this post. Get full access to NEW ECONOMIES at www.neweconomies.co/subscribe

  4. Sep 3

    Bebo

    Subscribe to stay ahead of technology trends. Never miss future editions. Our latest podcast guest is one incredible founder: Michael Birch, co-founder of Bebo, who shares how he started and scaled the social network into one of the most popular sites of its time before selling it to AOL for $850 million in 2008, how he reinvented himself after Bebo, and what he’s building now that Bebo is closed for good after 21 years. Watch now - Bebo Co-Founder: How to Build an $850 Million Social Network During the episode, we learn about Michael’s first entrepreneurial attempt, Ringo.com (another social network), which landed 400,000 members in three months on a $6,000 database server; how Bebo grew to a million users in nine days before going quiet for six months, until a basic quiz feature cracked engagement; and how The Battery, a members’ club in San Francisco, became his next act after the acquisition. We also explore an interesting question: what happens to a founder’s sense of identity when the company he and his wife, Xochi, spent years building is no longer theirs to run? Michael also shared that, although he’s technical at heart, he hasn’t written a line of code since January, building his latest venture almost entirely with AI, a glimpse of what building without a team could look like for the next generation of founders. Watch or listen now across YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Michael Birch(2:58) The Founding Story of Bebo(8:55) Why Bebo Went Viral(11:19) Bebo's First 12 Months(21:40) How Much Has Social Actually Changed?(23:58) Selling to AOL for $850M(29:50) Reinventing Your Identity Post-Acquisition(31:12) Starting The Battery(38:47) Technology or Hospitality?(39:54) Michael's Take on AI's Future(45:00) Is IRL Being Affected by AI?(47:55) Michael's Latest Venture: Bluebell(1:02:08) Building With Your Spouse Our notes from this episode with Michael 1. Virality gets people in, engagement keeps them. Bebo stalled after launch despite a working social graph. A single “how well do you know me” quiz, which required non-members to create an account to see their results, fixed that and pushed growth to hundreds of thousands of users a day. 2. ‘‘We killed virality on purpose outside English-speaking markets.’’ Bebo blocked non-English IP addresses from viral features so it wouldn’t blow up in markets he couldn’t support, staying deliberately focused on the UK, US, and other English-language countries. 3. A password scraper added 40 million users a year. Michael built a tool that logged into people’s Hotmail and Yahoo using their own passwords, pulled their address books, and mass-invited every contact. One overnight run alone added 100,000 members. 4. The $850M sale. Although a life changing amount of money to retire on, Michael never actually met anyone from AOL until the sale was officially closed. 5. The day the sale closed, he was unemployed. Michael and his wife were the only two people at the company not offered a job when AOL took over, despite three and a half years of building it together. 6. He thinks the technical moat he’s built his career on is gone by next year. He hasn’t written a line of code since January 1st, building his new app Bluebell entirely by directing AI, and expects deep technical understanding to stop mattering for shipping real products within the year. Links Follow Ollie on X: https://x.com/ollieforsyth Follow Michael on X: https://x.com/mickbirch Sign-up to Michael’s Newsletter - The Long Way Back to Friends: Sign-up to Bluebell - Michael’s latest venture: https://bluebell.social About BluebellBluebell is the social and messaging app Michael and Xochi Birch built as Bebo’s successor. It fuses DMs, group chats, and a feed into shared spaces called “pods,” with no public timeline, no follower count, and no feed of strangers to perform for. Previous episodes include See all previous episodes here 👉 If you enjoyed this episode, help sustain our work by clicking ❤️ and 🔄 at the top of this post. Get full access to NEW ECONOMIES at www.neweconomies.co/subscribe

  5. Aug 27

    Lambda

    Subscribe to stay ahead of technology trends. Never miss future editions. Will GPUs become a new asset class? Our latest podcast guest may have some answers. Stephen Balaban, co-founder and CTO of Lambda, joins us to explain why a $40,000 monthly AWS bill was the best thing that ever happened to the company in its early days, why he recently handed over the CEO title after fourteen years at the helm, and what is really going on in the GPU market, and whether we should be concerned or excited about the opportunity. About LambdaLambda, branded “The Superintelligence Cloud,” is an AI infrastructure company founded in 2012 that builds and operates gigawatt-scale AI factories and GPU supercomputers for training and inference, serving AI researchers, enterprises, and hyperscalers. Watch now - Stephen Balaban, co-founder at Lambda During our latest episode, we also learn how Lambda pivoted from a facial-recognition startup, to a data-collection hardware product called Lambda Hat, to an AI consulting shop nobody would fund, to the largest generator of Deep Dream images on the internet, before finally landing on an opportunity that very few saw coming: GPU cloud businesses. We also explore an interesting trend and opportunity: could GPUs become a new institutional asset class? We also discuss the lessons Lambda learned from partnering with one of the world’s most talked-about companies: Nvidia. Watch or listen now across YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Stephen Balaban(2:13) The State of GPUs(4:40) 2026: Is This the Breakthrough Year?(6:27) Starting Lambda in 2012(11:14) Spotting the GPU Opportunity(16:42) How Stephen Stays Focused(18:47) Starting a Company with Your Brother(21:44) Stepping Down as CEO(27:52) How to Find a New CEO(29:34) Not Raising from Traditional VCs(31:30) Where Does the GPU Opportunity Go Next?(34:35) GPUs Becoming an Asset Class(36:15) What Keeps Stephen Up at Night(39:33) How Many AI Models Will There Be?(41:15) Partnering with Jensen Huang(46:21) How Technology Has Changed Our notes from this conversation 1. Pivoting isn’t a failure mode for Lambda, it’s the operating model.Since 2012 the company has run through roughly half a dozen pivots: facial recognition software, an AR data-collection hardware product called Lambda Hat, a failed “Accenture for AI” consulting play no VC would fund, and Dreamscope, an app that became the largest generator of Deep Dream images on the internet before the fad died. Stephen’s rule: try something, if it works keep doing it, if it doesn’t move on. 2. An expensive AWS bill accidentally invented the company’s real business.At the peak of the Deep Dream craze, Lambda was paying $40,000 a month to Amazon, nearly enough to sink it. An early investor pushed the team to build their own servers instead. The $60,000 CapEx bet to build workstations wiped out that $40,000 monthly OpEx completely. Workstation sales went from $35,000 in March to $140,000 in May, on the way to $3 million in revenue that first year. The GPU cloud business was the byproduct of a cash crunch, not the plan. 3. GPUs are becoming an asset class, not a depreciating expense.Short sellers have argued GPUs carry a three-year usable life. Lambda’s counterevidence: V100s launched in 2017 are still nearly fully sold out in its cloud today, generating cash flow almost a decade later. Balaban’s comparison is insurance companies parking their float in power plants and toll roads, stable infrastructure that institutional and eventually retail capital moves toward as a category matures. 4. Starting a company with your brother for moral support.As a solo founder, your mood on any given day is the company’s mood that day. A co-founder averages two signals instead of riding one. Stephen credits this as much as anything for surviving Lambda’s early years, run out of a small Chinatown apartment with his brother and co-founder, Michael. 5. The requirement to study computer science to build software is gone.The clearest signal: anyone can now ship real tools built with Claude, people he describes as "meant to be programmers" who majored in something else. The real gate was never a CS credential, it was structured thinking, and that gate is now open to anyone. Links Follow Ollie on X: https://x.com/ollieforsythFollow Stephen on X: https://x.com/stephenbalabanVisit Lambda: https://lambda.ai Previous episodes include See all previous episodes here 👉 If you enjoyed this episode, help sustain our work by clicking ❤️ and 🔄 at the top of this post. Get full access to NEW ECONOMIES at www.neweconomies.co/subscribe

  6. Aug 21

    Superhuman

    Subscribe to stay ahead of technology trends. Never miss future editions. Shishir Mehrotra, CEO of Superhuman, joins NEW ECONOMIES to explain why he renamed a 16-year-old company mid-flight instead of just adding a new label on top, why he built his own board by ranking every past boss he’s ever had instead of chasing famous names, and why the real threat to a legacy SaaS category isn’t a faster competitor but the coordination problem AI agents are about to make bigger, not smaller. About Superhuman Superhuman is an AI-native productivity suite built from products including, Grammarly, Superhuman Mail (formerly called Superhuman), Superhuman Docs (formerly Coda), and Superhuman Go, serving over 40 million people and 50,000 organizations worldwide. During this episode, we also hear the four myths of bundling Shishir learned after his time running YouTube’s failed paid products, why marginal churn contribution, not usage, is the real basis for how bundlers split revenue, and how that same framework now governs how he prices and packages Superhuman’s four products. We get into why he treats a rebrand as a “do no harm” exercise for the existing brand first, the DACI-based ritual (Driver, Approver, Contributor, and Informed) his company uses to kill ad hoc meetings entirely, and why he thinks the SaaS apocalypse thesis has the coordination math backwards. We close on his “Jeopardy style” critique of most board meetings, why he’d rather ask a departing CEO to shadow him for a week than assume he already knows what’s unique about how he runs his own, and how a decade of hitting inbox zero taught him that the goal was never to answer faster, it was to never touch the same email twice. Watch or listen now across YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Shishir Mehrotra(1:50) The Naming Process for Superhuman(9:45) How Rahul (the original founder of Superhuman) and Shishir Met(11:28) Launching and Building Coda in 2014(14:42) Lessons from Reid Hoffman(17:51) Picking the Right Investors as Partners(19:49) What Is Bad Capital?(21:42) The Art of Bundling Products(31:38) The SaaS Apocalypse(37:50) What’s Missing from Superhuman’s Bundle(42:40) Getting to Inbox Zero(50:15) A Week with Shishir(54:50) How to Build a Board(1:00:30) Dream Board Member Our notes from this conversation 1. Bundles aren’t priced by usage, they’re priced by churn risk. ESPN and History Channel got nearly identical viewing hours on cable, yet ESPN was paid ~20x more. Shishir’s term for the real driver: marginal churn contribution, how many subscribers would cancel if you pulled that one product. That’s what bundlers were actually pricing, even without a name for it. 2. Renaming a 16-year-old company isn’t mechanical, it’s telling 1,500 people their login just changed. Google’s rebrand to Alphabet was additive; almost nothing changed for employees. Superhuman was different, a name change, not an addition, so every login and website had to move. Decision to roll out: ~4 months. 3. Pick a board member the way you’d pick a boss. Shishir and his co-founder listed every past boss they’d ever had, 12–15 people, and ranked by who got the best work out of them, not who they liked most. 4. AI agents don’t kill SaaS demand, they multiply the coordination problem. You don’t need a CRM because you have 10 humans selling; you need it to coordinate them. Swap in 100 virtual sellers and that coordination problem gets harder. His take on usage-based pricing: it’s less philosophy, more workaround, nobody knows how to price a “virtual seat” yet. 5. Inbox zero isn’t about answering fast. It’s about never touching an email twice. Auto-labels sort mail into ~10 “piles”: inbox, recruiting, customers, media, each handled at a different cadence. Borrowing from Intercom’s Des Traynor: your inbox is what others think you should work on, your to-do list is what you think you should work on, your calendar is what you actually work on. The job is making those three match. 6. The best bundles minimize super-fan overlap, not maximize it. Most founders assume a bundle should serve one audience deeply. Shishir’s thoughts: you want each product pulling in a different audience, Superhuman Mail skews sales/recruiting, Grammarly skews writers and students, so the bundle expands reach instead of just deepening engagement with the same crowd. 7. Casual fans, not super fans, are where bundles create value. A la carte pricing only captures people who both want a product enough to pay full price and have the energy to go find it, super fans. Bundling unlocks everyone else: people who wouldn’t have sought the product out alone but will use it once it’s already there. 8. Good investors act like long-term teammates. Bad ones act like bankers. Shishir’s litmus test: how does an investor behave when a company has to make a short-term-costly, long-term-right call? Reference-check by talking to people who worked with them for years, not just a call or two, the pattern only shows up under real pressure. Links Follow Ollie on X: https://x.com/ollieforsythFollow Shishir on X: https://x.com/shishirmehrotraDiscover Superhuman: https://superhuman.com Partners for today’s episode: Harmonic: Your go-to startup database: https://harmonic.ai Hostinger: A go-to tool for builders: https://hostinger.com/neweconomiesUse code NEWECONOMIES for 10% off. Previous episodes include See all previous episodes here 👉 If you enjoyed this episode, help sustain our work by clicking ❤️ and 🔄 at the top of this post. Get full access to NEW ECONOMIES at www.neweconomies.co/subscribe

  7. Aug 19

    Europe Is Catching Up

    Subscribe to stay ahead of technology trends. Never miss future editions. Saul Klein, co-founder and Managing Partner of Phoenix Court, joins the podcast to make the case that the UK is quietly the third biggest innovation economy in the world after the US and China, why capital has become a commodity, and what real venture value-add looks like when every fund says “we have money.” Saul also walks through building LoveFilm as a scrappy answer to Netflix, joining Skype during its 400,000-users-a-day growth spurt, and how he things about venture stewardship. About Phoenix CourtPhoenix Court is the London-based home of LocalGlobe, Latitude, and Solar, backing entrepreneurs building global businesses from pre-seed through scale-up. Founded in 2015 by Saul and Robin Klein, the firm has helped back over 700 companies that have grown from seed to $100 million-plus in revenue, and LocalGlobe ranks as EMEA’s number one seed fund. Watch Now: Saul Klein — Co-founder at Phoenix Court Watch or listen now across YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Saul Klein(2:21) Starting LoveFilm(8:48) LoveFilm's Route to Market(11:10) Building Skype(17:30) Skype's Early Network Effects(19:29) Is Europe Still a Great Place to Build?(24:10) Which Are the Best Regions to Start?(31:10) Hardest Challenges in Scaling in Europe(35:26) How Should Founders Select Investors?(43:47) VC Stewardship & Shared Ownership(52:36) What Would Saul Build Tomorrow? Our notes from this conversation * Capital is a commodity. Access to a contract is not. With 20,000 VCs in the world, “we have money” isn’t a value proposition, it’s the line every fund uses. Saul’s actual differentiator: nondilutive revenue, a real purchase order or contract, then access to the right talent, then capital formation most founders don’t know exists. His analogy: 20,000 barber shops all shouting “I cut hair” until someone breaks the pattern. * Netflix’s real innovation wasn’t DVDs by mail. It was demand data. LoveFilm’s (the company Saul founded) edge wasn’t logistics, it was the queue: people ranked 20-50 titles, giving the business live demand data that became leverage with studios. The company hit $100M+ revenue growing 30-40% a year, largely by powering DVD rental for Tesco, ITV, Odeon and MSN. * Skype grew 400,000 users a day, and Saul couldn’t spend a marketing budget. Product-driven virality was adding users faster than paid acquisition could. In 12-18 months the team went from ~20-30 people to 500, and Skype’s revenue went from zero to $200 million. * Blindly chasing the US as market #2 is what Saul calls a catastrophic error. Most investors are “sheep,” and following them west assumes the US is one easy market, it’s actually fifty fragmented jurisdictions and usually the toughest “red ocean” to enter second. Zoopla, a strong #2 to Rightmove in a market worth hundreds of millions, is his proof a well-chosen home market often beats the US by default. * Phoenix Court’s & venture stewardship. Structured as a company, not an LLP, since year one, a rarity among ~20,000 global funds - Phoenix Court has always shared profit and carry with every employee, not just partners. Links Follow Ollie on X: https://x.com/ollieforsyth Follow Saul on X: https://x.com/cape Phoenix Court: https://www.phoenixcourt.vc Our partner for today’s episode is Harmonic - the go-to startup database: https://harmonic.ai Previous episodes include See all previous episodes here 👉 If you enjoyed this episode, help sustain our work by clicking ❤️ and 🔄 at the top of this post. Get full access to NEW ECONOMIES at www.neweconomies.co/subscribe

  8. Aug 16

    Xero

    Subscribe to stay ahead of technology trends. Never miss future editions. Sukhinder Singh Cassidy, CEO of Xero, joins NEW ECONOMIES to explain why cracking the US took twenty years and an acquisition despite Xero being the more open, cheaper alternative to Intuit, why she treats “respected vs. liked” as a false choice a new CEO has to reject on day one, and why the biggest threat to a twenty-year-old platform isn’t a faster competitor but the capital and infrastructure it takes to replicate what that platform already owns. About XeroXero is a global small business platform serving over 5 million customers across 180 countries, providing cloud-based accounting, payments, and payroll software for small businesses and their advisers. Watch Now - Sukhinder Singh Cassidy - CEO at Xero During this episode, we also cover the strategy behind narrowing Xero’s US focus from “5 million customers” to a single unicorn-revenue number, how a survey of Xero’s own customer base splits into a majority still non-native to AI and a fast-growing minority already building on the company’s APIs (4x since January), and why Airtable selling for $1.2B on $450M in revenue is the cautionary tale for the current market. As we know, layoffs happen across many companies, and Xero was no exception. Six weeks after joining as CEO, Sukhinder laid off 700–800 employees. We get into how she ran the numbers and surveys, and why she believes accountants will outlast the “Claude will just tell you the answer” argument because human judgment and advice still matter. We close on why she’d rather be model-agnostic than bet the business on a single AI partner, what a week actually looks like running a 5,000-person public company, and how she keeps a fiercely scheduled career next to a deliberately unscheduled personal life. Available everywhere you listen to podcasts: YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Sukhinder Singh Cassidy(2:17) The Current State of Xero(5:35) Why America Was So Hard to Crack(10:05) Why It's Important to Focus(12:55) Joining Xero as CEO(16:40) Being Respected vs. Liked(22:57) How to Prepare for a Layoff(27:30) Being a Publicly Listed Company CEO(30:07) The State of SMBs(33:30) Thinking How to Partner with AI Models(36:24) How Much Code Is Written by AI?(38:39) How Does Xero Stay Relevant?(42:51) Is Trust the Next Biggest Moat?(43:39) The Biggest Opportunity for Xero(46:00) Will Accountants Still Be Relevant?(48:08) Companies Who Aren't Hiring AI Talent(49:05) Ollie Joins as Sukhinder’s Chief of Staff(50:39) Personal Time Out Our notes from this conversation 1. Being liked and being respected are different jobs, and she picked one.When we asked during the episode, Sukhinder is direct about it: over a thirty-year career, she’s optimized for going where her strengths are valued and her values fit, not for being liked. That meant walking into Xero, presuming people are smart and honest, and telling them the hard truth on day one rather than sugarcoating the situation. 2. She benchmarked the layoff before she announced it. Three months before officially becoming CEO, she surveyed over a thousand Xero employees, ran an outside-in with McKinsey against comparable SaaS companies, and read the data back to the company twice before cutting 700–800 roles six weeks later. The data made the decision defensible: it didn’t make it easy. She openly shares that she was heartbroken announcing it, and got Slack messages that day from employees she’d never met, checking if she was okay. This can say a lot about the company culture. 3. Cracking America took twenty years because incumbency beats a better product.Intuit is twice Xero’s age, born in the US, with 100% of its attention on that one market. Xero had to double its US organic growth rate, bring on US engineers building for US customers instead of running the market from the southern hemisphere, and narrow its pitch to “easier, cheaper, more open” before the US became its fastest-growing region, helped along by the Melio acquisition. 4. Public company CEO in a choppy market means the job doesn’t change. Her answer to “what’s hardest right now” is basically: nothing new, be a value creator, be focused, keep delivering through good times and bad. She thinks the market currently can’t tell one SaaS company from another, and her job is to keep 5,000 employees focused on Xero’s own numbers rather than the noise. 5. Most SMBs aren’t using AI yet, and that gap is the opportunity.Xero’s own customer survey shows the majority of small businesses are still early in their AI adoption. A smaller, fast-growing minority is already comfortable enough to use Claude for real financial actions: API usage on Xero is up 4x since January. She sees Xero’s job as meeting the whole spectrum, from AI chat for the least advanced to XeroForce for the most. 6. Trust, not code, is becoming a real moat for companies. Her response to a competitor who can build “a thin slice of software faster” is: sure, but can you raise the capital, acquire the customers, get the data trusted, and be accurate and compliant across every job a customer needs done? Ollie points to Airtable’s $1.2B sale on $450M in revenue as the cautionary tale: the product was replicable, the twenty years of infrastructure, data, and distribution weren’t. Links Follow Ollie on LinkedIn: https://www.linkedin.com/in/ollieforsythFollow Sukhinder on LinkedIn: https://www.linkedin.com/in/sukhindersVisit Xero: https://www.xero.comEpisode Partners - Harmonic, the go-to startup database: https://harmonic.aiEpisode Partners: Hostinger, a go-to tool for builders: https://hostinger.com/neweconomies. Enter code NEWECONOMIES for 10% off. Previous episodes include See all previous episodes here 👉 If you enjoyed this episode, help sustain our work by clicking ❤️ and 🔄 at the top of this post. Get full access to NEW ECONOMIES at www.neweconomies.co/subscribe

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Welcome to BIG IDEAS by NEW ECONOMIES - a show where we learn how the most iconic founders have turned crucible moments into global companies. www.neweconomies.co

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