20VC: If You Do Not Like VCs, You Have Not Worked With a Good One, How Andreesen Have Added The Same Level of Value As A Co-Founder, Why Market Is The First Thing To Consider When Angel Investing & Why Series A Is A Hiring Decision with Roger Dickey, Foun

Eoghan McCabe is the Co-Founder and CEO @ Intercom, one of the largest private software companies in the valley with hundreds of millions in revenue and thousands of customers. To date, Eoghan has raised over $238M from Index, Kleiner Perkins, ICONIQ, GV, Bessemer and more incredible firms. Intercom's goal is to reinvent customer service with AI agents replacing human agents over the next 10 years. 10 Questions with One of the Largest Private Company CEO's: AI Investing: Why will most AI investments not do better than the S&P 500? Building SaaS Tools with AI: Why is it crazy for companies to follow Klarna and use AI to build their own tools? Going Public: Why is Bill Gurley wrong that more later stage companies should go public? Why did Intercom shelve plans to go public in 2022? Early-Stage is F*******: Why is the early-stage venture ecosystem as an asset class f******? Founder Mode: Why does Eoghan believe all of the best founders are unbalanced? What is the difference between Founder vs Manager mode? Political Voice: Why did Eoghan decide he had to voice his political opinions now? The Danger of Harris: Why does Eoghan believe a Harris administration would rob the US of immense freedom, democracy and civil liberty? Why Vote Trump: Why does Eoghan believe that Trump will regain immense freedom for the sovereign individual? Freedom of Speech: How does Eoghan determine right vs wrong when freedom of speech leads to harm and injustice? Middle East and Nuclear War: Why does Eoghan believe that nuclear war is much closer than we think? Will we see the Middle East descend into war?

11 Okt 202446min

Jeff Wang is the Managing Partner of Sequoia Capital Global Equities (SCGE), a public/private crossover investment firm with investments spanning from late-stage private companies to public companies. As Managing Partner, Jeff has primarily focused on public growth technology companies but has also invested $3 billion in private companies including Bytedance, SpaceX, and Stripe. Prior SCGE private investments that have since gone public include Airbnb, Doordash, MongoDB, Nubank, and Snowflake. Before joining SCGE in 2010, Jeff also worked at TPG Capital and Silver Lake Partners where he focused on investments in technology buyouts. 10 Questions with the Leader of Sequoia's $9BN Global Equities Fund: 1. Crossover Fund Opportunity: Why are crossover funds more attractive today than ever? Have the tourists gone? 2. Public Market Opportunity: Why is the opportunity in the public markets, not the private markets today? 3. IPO Markets: When will IPO markets open? What will cause them to open? 4. Breaking Hedge Fund Rules: What are the biggest ways that Sequoia break the traditional rules of hedge funds? 5. Google: Why does Jeff believe that Google's cash cow of search is under threat? 6. Meta: Why does Jeff believe Meta will be the biggest competitor to Google? 7. NVIDIA: Why is NVIDIA's price today reasonable? What is the bull and bear case? 8. China: Is there a recovery for China? How do Sequoia play China in this market? 9. AI in Public Markets: How are Sequoia playing the AI game in the public markets? 10. Investing Lessons: What have been Jeff's biggest investing lessons from Mike Moritz, Doug Leone and Roelof Botha?

9 Okt 20241h 12min

Eiso Kant is the Co-Founder and CTO of Poolside.ai, building next-generation AI for software engineering. Just last week, Poolside announced their $500M Series B valuing the company at $3BN. Prior to Poolside, Eiso founded Athenian, a data-enabled engineering platform. Before that, he built source{d} - the world's first company dedicated to applying AI to code and software. 1. Raising $600M to Compete in the AGI Race: What is Poolside? How does Poolside differentiate from other general-purpose LLMs? How much of Poolside's latest raise will be spent on compute? How does Eiso feel about large corporates being a large part of startup LLM provider's funding rounds? Why did Poolside choose to only accept investment from Nvidia? Is $600M really enough to compete with the mega war chests of other LLMs? 2. The Big Questions in AI: Will scaling laws continue? Have we reached a stage of diminishing returns in model performance for LLMs? What is the biggest barrier to the continued improvement in model performance; data, algorithms or compute? To what extent will Nvidia's Blackwell chip create a step function improvement in performance? What will OpenAI's GPT5 need to have to be a gamechanger once again? 3. Compute, Chips and Cash: Does Eiso agree with Larry Ellison; "you need $100BN to play the foundation model game"? What does Eiso believe is the minimum entry price? Will we see the continuing monopoly of Nvidia? How does Eiso expect the compute landscape to evolve? Why are Amazon and Google best placed when it comes to reducing cost through their own chip manufacturing? Does Eiso agree with David Cahn @ Sequoia, "you will never train a frontier model on the same data centre twice"? Can the speed of data centre establishment and development keep up with the speed of foundation model development? 4. WTF Happens to The Model Layer: OpenAI and Anthropic… Does Eiso agree we are seeing foundation models become commoditised? What would Eiso do if he were Sam Altman today? Is $6.6BN really enough for OpenAI to compete against Google, Meta etc…? OpenAI at $150BN, Anthropic at $40BN and X.ai at $24BN. Which would Eiso choose to buy and why?

7 Okt 20241h 10min

Maria Angelidou is a seasoned product leader, having spent close to a decade at Meta where she was VP of Product and General Manager for some of the largest products such as Facebook Groups (2B+ users), Events, Profile, and Search. Before that, Maria led the Facebook App Monetization team, driving billions of dollars in revenue. Today, Maria is the Chief Product & Technology Officer at Personio, an HR tech company with an ambitious mission to unlock the power of people for SMEs. In Today's Episode with Maria Angelidou 1. How to Hire the Best Product Teams: What are the three different archetypes for PMs today? What non-obvious traits does Maria look for in new product hires? How does Maria structure the hiring process? What works? What does not? Does Maria do take home assignments? How has her approach changed here? What is Maria's biggest advice to candidates on both compensation and title? 2. How the Best Product Teams Do Product Reviews: What does every team get wrong in how they do product reviews? What are the four different type of product reviews? How often does Maria do a product review? Who is invited? Who sets the agenda? How is it structured? What makes good vs great product reviews? 3. Europe vs US: How Product Teams Differ: What is the single biggest difference when comparing product teams in the US vs EU? Does Maria agree that the work ethic is less in the EU? Which class of employee would Maria say is more entitled? What could Europe do to be more competitive with the US? What was the biggest surprise to Maria on returning to Europe from the US?

4 Okt 202450min

Bret Taylor is CEO and Co-Founder of Sierra, a conversational AI platform for businesses. Previously, he served as Co-CEO of Salesforce. Prior to Salesforce, Bret founded Quip and was CTO of Facebook. He started his career at Google, where he co-created Google Maps. Bret serves on the board of OpenAI. In Today's Discussion with Bret Taylor: 1. The Biggest Misconceptions About AI Today: Does Bret believe we are in an AI bubble or not? Why does Bret believe it is BS that companies will all use AI to build their own software? What does no one realise about the cost of compute today in a world of AI? 2. Foundation Models: The Fastest Depreciating Asset in History? As a board member of OpenAI, does Bret agree that foundation models are the fastest depreciating asset in history? Will every application be subsumed by foundation models? What will be standalone? How does Bret think about the price dumping we are seeing in the foundation model landscape? Does Bret believe we will continue to see small foundation model companies (Character, Adept, Inflection) be acquired by larger incumbents? 3. The Biggest Opportunity in AI Today: The Death of the Phone + Website: What does Bret believe are the biggest opportunities in the application layer of AI today? Why does Bret put forward the case that we will continue to see the role of the phone reduce in consumer lives? How does AI make that happen? What does Bret mean when he says we are moving from a world of software rules to guardrails? What does AI mean for the future of websites? How does Bret expect consumers to interact with their favourite brands in 10 years? 4. Bret Taylor: Ask Me Anything: Zuck, Leadership, Fundraising: Bret has worked with Zuck, Tobi @ Shopify, Marc Benioff and more, what are his biggest lessons from each of them on great leadership? How did Bret come to choose Peter @ Benchmark to lead his first round? What advice does Bret have to other VCs on how to be a great VC? Bret is on the board of OpenAI, what have been his biggest lessons from OpenAI on what it takes to be a great board member?

2 Okt 20241h 10min

Donald Tang is the Executive Chairman of SHEIN, with oversight of public affairs, business strategy, corporate development, and finance. Donald began his career at Merrill Lynch & Co. He later joined Bear Stearns & Co. Inc. in Los Angeles as Senior Managing Director of Investment Banking. At Bear Sterns, Donald quickly rose to become the Vice Chairman of the firm, as well as Chairman and President of Bear Stearns International Holdings, Chairman and CEO of Bear Stearns Asia, Ltd, and a member of the board of directors at Bear Stearns & Co. In Today's Episode with Donald Tang We Discuss: 1. How SHEIN Became a Global Giant: As specifically as possible, what did you and the SHEIN team do that enabled you to be one of the fastest-growing companies on the planet? Real-Time Retail: What is this? How is it the core of SHEIN's growth and efficiency? Supply Chain Innovation: How did SHEIN innovate on the supply chain to give them such an advantage over the competition? Price King: How does Donald respond to the statement that SHEIN wins due to price, not quality? Social Media: What social media tactics allowed SHEIN to grow so fast? What did not work? Paid Media: How have SHEIN approached paid marketing? What works? What does not? 2. The Big Questions: IPOs, Impact on Climate and Worker Conditions: IPO: Why does SHEIN want to go public? Is London the right place for the company to go public? Climate: How does Donald respond to the common idea that "SHEIN is bad for the climate" and encourages fast fashion like never before? Tariffs: How does Donald respond to the common question around tariffs and SHEIN benefitting from being under a certain tariff threshold? 3. Marriage, Fatherhood and Happiness: Marriage: What have been Donald's biggest lessons on how to have a successful marriage? Fatherhood: What does being a great father mean to Donald? If he could call himself up the night before his first child was born, what would he advise himself? Happiness: How does Donald think about happiness today? What does everyone get wrong about happiness?

30 Sep 202455min

Jeetu Mahtani was an early member of the HubSpot team. Under his leadership and the sales organization, the business grew its non-US revenue from $3M ARR to close to $1B ARR. After running the International business as the global MD and Sales leader, he then moved to lead the customer success org which expanded to managing 1,500 people in customer success. In Today's Episode with Jeetu Mahtani We Discuss: 1. How to Go International for Startups: What are Jeetu's biggest lessons from Hubspot on what startups can do to make their international expansion a success? What were the biggest mistakes Hubspot made in their international expansion? How should every team in each new location be structured? What should the ramp time and onboarding process look like or each new team and expansion? 2. Scaling Sales from $3M to $1BN in ARR: What did Hubspot do so well to successfully scale to $1BN in international ARR? What were the biggest mistakes Jeetu made in the expansion of Hubspot's sales teams? What are the first things to break in sales teams? How do you handle them? Why does Jeetu hate discounting? Why does Jeetu not like customer references? 3. Scaling Customer Success to 1,500 CS Reps: When should founders make their first customer success hires? What are the biggest mistakes people make in the scaling of CS teams? Why should customer success be incentivised in the same comp plans that sales teams have? How do the best CS teams work with sales and product teams most effectively? 4. Hiring the Best and Ramping Them: What does Jeetu's hiring process look like for all new sales reps? What are the must ask questions for Jeetu in all candidate interviews? How fast do you know when you have made a mistake with a new hire? What is the secret to effective onboarding? What are the biggest mistakes people make in onboarding? 20Sales: Scaling Hubspot from $3M to $1BN in ARR | How to Hire and Ramp Sales Teams | How to Scale Customer Success Successfully | How and When to Go International and Crush It with Jeetu Mahtani

27 Sep 202456min

Eric Vishria is a General Partner @ Benchmark Capital, one of the world's leading venture firms. At Benchmark, Eric has served on over 10 boards including Confluent (CFLT), Amplitude (AMPL), Benchling, Contentful, Cerebras and several other private companies. Prior to joining Benchmark, Eric was the Co‐Founder and CEO of RockMelt, acquired by Yahoo in 2013. In Today's Episode with Eric Vishria We Discuss: 1. How to Make Money Investing in AI Today: How does Eric think through where value will accrue in the stack between chips, models and applications? Why does Eric believe foundation models are the fastest commoditising asset in history? Why does Eric believe that Nvidia will not be the only game in town in the next 3-5 years? 2. How to Invest in AI Application Layer Successfully: How does Eric analyse between a standalone and deep product vs a product that foundation model will commodities and incorporate into their feature set? How does Eric differentiate between the 10 different players all going after customer service, or sales tools or data analyst products etc? How does Eric analyse the quality of revenue of these AI application layer companies? What does he mean when he describes their revenue as "sugar high"? 3. How the Best VC Firm Makes Decisions: What is the decision-making process for all new deals in Benchmark? As specifically as possible, how does the voting process inside Benchmark work? What deal was the most contentious deal that went through? What did the partnership learn? How has the Benchmark decision-making process changed over 10 years? 4. Does AI Break Venture Capital Models: Does the price of AI deals and size of their rounds break the Benchmark model? Will foundation model companies all be acquired by the larger cloud providers? Unless multiples reflate in the public markets, does venture as an asset class have hope? Why does AI make paying ludicrously high prices potentially rational?

25 Sep 20241h 2min