BIG IDEAS BY NEW ECONOMIES

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Josh Elman has shaped products at some of the biggest consumer platforms in tech. He helped lead product at LinkedIn, Facebook, and Twitter, invested in startups at Greylock, and took senior operating roles at Robinhood and Apple. Now a Partner at Andreessen Horowitz, he joins us for his first external podcast interview since joining the firm.
In our in-depth conversation, we discuss:
* Why anyone can clone a product’s features within days, but nobody can clone where a founder is actually headed next
* Why we haven’t seen many new consumer social networking sites
* The new era for voice
* Is trust the new moat and what does it actually mean?
* The pricing challenge for today’s startups
* Is S.F still the best place to launch and grow a startup?
Watch or listen now across YouTube, Apple Podcasts, Spotify, and X

Download the transcript 👇
Timestamps
(0:00) Meet Josh Elman(2:40) Why Josh Is Back in Investing Mode(4:19) The New Consumer Experiences(6:00) Where in the Journey Are We?(8:00) What Comes Next for Consumers?(10:58) Is Trust the New Moat?(11:40) The New Way to Search(13:20) Experiences That Haven't Emerged Yet(15:01) Trends Josh Is Excited About(19:08) Whatnot(21:05) AI Microdramas(26:43) Why Is Social So Hard?(32:20) Multi-Agent Communication(36:19) New Platforms With Distribution(38:27) The New Era for Voice(43:01) The Pricing Challenge(46:47) What Excites Investors Today(49:14) How Network Effects Have Changed(51:36) Idea to Clone: Days(52:39) Why the U.S. Wins at Consumer(54:34) Is SF Still the Best Place to Start a Company?(55:43) Josh's Favorite Company(57:35) Lessons from Ev Williams
Lessons from this episode with Josh
The cycle of adoption
One person built a category-defining agentic tool almost entirely on his own, working out of his apartment. Josh uses it to mark the moment agentic AI went from theory to something people could actually feel the difference of, and why that shift is what’s now pulling the entire industry into this new wave.
Multi-agent communication (agents planning your Friday night)
Josh’s most vivid vision in the episode: agents quietly talking to each other on your behalf, turning a private thought such as, wanting to see a movie into a real plan with friends before you even have to ask.
Why building consumer social is very hard
We know building consumer startups is super difficult. Josh does a relatable comparison of why Discord, Musical.ly, and Instagram all won by solving completely different problems, not by competing head-on. He describes the potential opportunity as, we need something that feels genuinely new, not another variant of what’s already out there.
What excites investors today
Josh lays out his four-part framework for what makes a great consumer product: clear value on first use, an easy substitution for existing behavior, organic word of mouth, and long-term retention.
The new era for voice
The take on why voice will never fully replace typing, and where it actually shines: in the car, prepping for a podcast, or rehearsing a hard conversation before having it for real.
The pricing challenge
We break down the tension building under consumer AI: free, subsidized tools are colliding with the real cost of inference. Josh traces it back to his first week at LinkedIn, physically moving servers, to show how infrastructure costs have shifted from fixed to variable.
Where to find and connect with us
Follow Ollie on X: https://x.com/ollieforsythFollow Josh on X: https://x.com/joshelmanVisit Andreessen Horowitz: https://a16z.comOur partner for today's episode is Harmonic - your go-to startup database: https://harmonic.ai
Previous episodes include
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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 👉
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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 👉
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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
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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 👉
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