Show Notes
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 m
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Subscribe to stay ahead of technology trends. Never miss future editions. Two to three years ago, software companies were still planning product roadmaps in years and quarters. Today, as one of our guests put it, the only question that matters is “what are we shipping this week?” That guest was Chano Fernández, co-CEO of Klaviyo. He joined us to explain how AI agents are reshaping marketing and customer engagement, why taste may be the biggest moat AI companies can build, and what it really takes for a public software company to stay relevant when the ground keeps moving. Chano held senior leadership roles at SAP before becoming co-CEO of Workday, where he helped expand its global and enterprise business. He was then co-CEO of the AI-native talent platform Eightfold, and spent two years on Klaviyo’s board, most recently as interim executive. In January, he became co-CEO alongside co-founder Andrew Bialecki. Andrew focuses fully on Klaviyo’s AI vision and products, while Chano runs go-to-market, operations, and G&A. Klaviyo now serves more than 200,000 customers, with around 9 billion profiles and 250 billion transactions a quarter on the platform. In our in-depth episode, we discuss: * Why email may become less relevant as AI agents start reading it for us, and why Klaviyo’s 14 years of data and infrastructure can’t be replicated with vibe coding * Inside Composer, Klaviyo’s agentic marketing tool: seven or eight sub-agents, and why getting a campaign to come out “80% or 90% right” for a CMO comes down to taste * Where software pricing is heading: from seats to consumption to outcome-based deals, and the 5% to 6% revenue share Chano is seeing emerge across the industry * How 70% to 80% of Klaviyo’s code is now written by AI, why its Friday product meetings show what shipped that week, and why a new product only needs to be 60% to 70% ready at launch * How the co-CEO model works in practice: a written operating agreement, two to three calls a day, and why only a handful of decisions each year really need both of them Watch or listen now across YouTube, Apple Podcasts, Spotify, and X
Subscribe to stay ahead of technology trends. Never miss future editions. During San Francisco Tech Week a few weeks ago, we co-hosted our first New Media Summit with Yahoo, bringing together media’s biggest names for candid conversations on where the industry goes next. One of our speakers was Dylan Abruscato, President of TBPN, which has had a huge year. He joined us to share how a bootstrapped, 10-person live tech show became one of the most valuable ad slots in Silicon Valley, why live remains “a truly unskippable ad format,” and why reaching a niche audience can be worth more than reaching a big one. Dylan began his career in live TV at SNL and CNBC. He then helped run HQ Trivia through its rise and fall, and built his own live interactive game show before joining TBPN, a daily, three-hour tech variety show hosted by John Coogan and Jordi Hays. Under Dylan, it grew to roughly $25 million in annual revenue with 30 year-long sponsors, led by presenting sponsor Ramp. Six months ago, it was acquired by OpenAI. In our in-depth episode, we discuss: * Why the OpenAI deal had little to do with the show itself, and how the marketing and comms advisory work built into TBPN’s sponsorships became the real reason behind the acquisition * The Super Bowl stunts that preceded the deal: a hyper-local 15-second spot built from over a thousand founder logos, and claudewithads.com * How TBPN copied Formula 1’s sponsorship model: year-long deals, category exclusivity, 100% share of voice, and an ad read to Mark Zuckerberg as he took his seat * Why the show stayed intentionally niche, and why it only takes one or two founders switching platforms for a tech sponsor’s ad to pay for itself * Inside a daily live show: the 6 a.m. gym sessions, the three-hour run of show, last-minute guest booking, and the vibe-coded internal tools that power it all Watch or listen now across YouTube, Apple Podcasts, Spotify, and X Download the transcript 👇 Timestamps (0:00) Meet Dylan Abruscato(2:20) Why OpenAI acquired TBPN(6:48) What changed after the acquisition(7:43) Will frontier models come on the show?(8:17) What makes TBPN so vibrant(9:32) Prepping for a daily live show(10:46) Why live streaming is hot(12:04) Are niche audiences more valuable?(12:58) How the ad integrations work(15:44) Calling partners post-acquisition(17:10) Building alongside legacy media(18:17) The copycats(19:38) Will another TBPN-style acquisition happen?(20:08) OpenAI’s marketing services(21:02) Thinking about distribution channels(22:10) Dream guests(22:59) TBPN’s next 12 months(23:22) Audience Q&A Lessons from this episode with Dylan 1. The OpenAI deal was for the team, not the show Dylan says most people misread why OpenAI bought a live tech talk show. “I think what a lot of folks got wrong about the deal is that it had very little to do with the show itself and much more to do with the interest in us and the brains behind the operation.” Many of TBPN’s 30 sponsorship deals included marketing and comms advisory work, a tactic the team first used to win sponsors. OpenAI’s offer was simple: keep doing the show, wind down the advisory clients, and make OpenAI the only one. TBPN was profitable, had raised no money and had no plans to sell. Fidji Simo reached out the morning after the Super Bowl. 2. Build the show you’d want to watch The two stunts that came right before the deal both started as ideas the team found funny. “The truth is we’re just building the show that we always wanted to watch.” The first was a hyper-local 15-second ad that aired in San Jose at noon but still counted as a Super Bowl spot. It spelled out TBPN using over a thousand logos of past guests, and those founders shared it everywhere. The second was claudewithads.com, a reskinned Claude that gave one real answer and then rotated through sponsor ad reads. The team’s brainstorming rule is that if an idea makes them laugh, they run with it. 3. Live is the last unskippable ad format Dylan has worked in live TV at
Subscribe to stay ahead of technology trends. Never miss future editions. Eric Ries, creator of The Lean Startup and author of Incorruptible, joins us to explain why “financial gravity” pulls even the best companies away from their mission. He explains why the standard best practices founders are handed “are designed to make you lose control of your company.” Eric published The Lean Startup 15 years ago and went on to found the Long-Term Stock Exchange. He co-founded the AI research lab Answer.AI and helped start Virgil, an AI-enabled law firm for early-stage companies. In his latest book, Incorruptible, he studies the companies that have resisted this force, from Costco to Novo Nordisk to Anthropic. In our in-depth episode, we discuss: * How the default “any lawful act or activity” clause in a Delaware charter quietly commits founders to maximizing shareholder value, and why lawyers rarely tell them * The story of Sol Price, FedMart and the origins of Costco, and the “governance fortress” that has protected Costco’s $1.50 hot dog for 40 years * The three mission protective provisions every founder can set up in a matter of weeks: becoming a PBC, adopting a director’s oath, and appointing a mission guardian * The difference between a mission statement and a mission, and what Silicon Valley Bank’s charter revealed after its collapse * Why “it’s always too early until it’s too late,” how to win over the roughly 25 people who must agree to a change, and why Anthropic’s Long-Term Benefit Trust has become a commercial advantage Watch or listen now across YouTube, Apple Podcasts, Spotify, and X
Subscribe to stay ahead of technology trends. Never miss future editions. Daniel Chait, co-founder and CEO of Greenhouse, joins us to explain why AI has trapped hiring in a “doom loop” where, for the first time he can remember, “neither side is really happy.” He co-founded Greenhouse in 2012 and has built it into one of the world’s leading hiring platforms, used by more than 7,500 companies with a team of over 700. His Dream Job feature lets job seekers flag one application a month as their top choice, and he says those candidates now convert from application to hire at around five times the rate of everyone else. Daniel also shares why 1 to 1.5% of applicants fail an ID check, how North Korean operatives use deepfakes to get through interview rounds, and why he believes starting with an AI interview can remove bias from the most biased stage of hiring. In our in-depth episode, we discuss: * How auto-apply tools and AI résumé filters created the hiring “doom loop,” and why job seekers and employers no longer trust each other * The three-layer “Swiss cheese” model Greenhouse uses to catch fake candidates, and why North Korean infiltrators are so hard to spot once they’re hired * Why an AI interview at the first stage can take racial bias out of résumé screening, and how it cuts around six days from the process * Why Greenhouse’s value has shifted from workflow to data and context, and whether it will come out of this moment as Blockbuster or Netflix * How Daniel decides which bets to place, why “we can do anything, we just can’t do everything,” and what it would mean to hire AI agents through Greenhouse Watch or listen now across YouTube, Apple Podcasts, Spotify, and X
Subscribe to stay ahead of technology trends. Never miss future editions. Micha Kaufman, co-founder and CEO of Fiverr, joins us to explain why anyone who has worked in their profession for more than five years is now “a dinosaur.” He has spent 17 years building Fiverr into a global marketplace connecting millions of freelancers with businesses, and took it public on the New York Stock Exchange in 2019. His internal memo warning staff about AI went viral a year ago, and he says the employees who embraced it are now doing two to three times more than before. Micha also shares why AI has flipped the 80/20 split between human and software work, why an AI that knows everybody “just makes everybody more average,” and why human judgment and accountability will be the biggest moat any professional can have. In our in-depth episode, we discuss: * The asteroid analogy behind Micha’s viral AI memo, and what changed inside Fiverr in the 12 months after he sent it * Why the 20% of work AI can’t do is “infinitely important,” and the risk of outsourcing judgment to machines * Why most AI-generated code is built on poor-quality open source, and what that means for developers whose job was 60–70% copy-pasting * Why Micha wants to stop calling freelancers “freelancers,” and why he believes getting better is each person’s own responsibility * How Micha runs a public company through a period of uncertainty by encouraging impatience, and whether half of Fiverr’s clients could soon be AI agents Watch or listen now across YouTube, Apple Podcasts, Spotify, and X