"Our AI doesn't replace underwriters. It does the boring work so they can make the decisions."

I talk to Danny Tang, founder of Tradata, about why the non-qualified mortgage market is the underserved $239 billion slice of US mortgages, and what it takes to build AI for an industry that demands 100% accuracy. Danny grew up in Hong Kong, spent four years in the financial industry there, and moved to San Francisco to build mortgage tech that runs on-prem instead of in the cloud.

Tradata interviewed 60+ underwriters before writing a line of product code. The goal: take the 1+ hour per file underwriters spend reading 400-page bank statements and turn it into minutes, without ever leaking data outside the lender's environment.

In this episode:

- The $239B Non-QM Wedge: Why a $239 billion segment (9% of US mortgages today) is set to become 30%+ of the market over the next decade.

- The 100% Accuracy Bar: Why regulated lenders can't use general-purpose LLMs, and what it takes to clear that bar without buyback risk.

- On-Prem Over Cloud: Why Tradata runs locally on customer infrastructure, and why finance is moving in the opposite direction of every other industry.

- Document Hell: The 400-page bank statements, tax returns, and PNLs underwriters wade through, and the 1+ hour per file that disappears with AI.

- Why Now: Gig workers, creators, and entrepreneurs need homes but don't qualify for traditional mortgages, and the trend is only accelerating.

- The Lender Tech Gap: Why mortgage giants like A&D are building in-house AI while small and medium lenders fall behind, and the market consolidation that follows.

- AI Augments, Doesn't Replace: Why underwriters fear AI tools that promise to replace them, and what changes when the AI does the boring work instead.

- From Hong Kong Finance to SF Startup: Danny's path from the reinsurance group in Hong Kong to building mortgage tech in San Francisco.

🎧 Full episode on all podcast platforms

💬 Should regulated industries stay on-prem, or move to cloud-native AI? Let us know in the comments!

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#DN #Mortgage #FinTech #AIinFinance #DannyTang #Tradata #Startups #NonQM #PrivateAI #SaaS

Timestamps:

0:00 Intro

0:18 From Hong Kong finance to founding Tradata in San Francisco

2:30 The document-processing pain in non-QM underwriting

4:40 The $239B non-QM market and why it's growing

7:00 Building for 100% accuracy in a regulated industry

7:44 Private on-prem AI vs cloud-native software

9:30 The underwriter workflow Tradata replaces

12:00 Why non-QM specifically (gig workers, creators, real estate)

15:00 Self-teaching code on document processing side projects

20:00 The lender tech gap: giants vs small lenders

24:00 Solving problems no one cares about

27:30 Growing up on Rich Dad Poor Dad, Ray Dalio, Warren Buffett

"Two people reading the same book get completely different action steps."

I talk to Shruta Satam, co-founder of Pustak, about the knowing-doing gap — why most of what we read never makes it into our lives — and how Pustak personalizes action steps from every book to the reader's actual goals. Shruta spent 18+ years in risk management consulting at Deloitte and PwC across the US and Australia before leaving to build Pustak with her technical co-founder.

We get into why summaries alone aren't enough, what the Pustak Coach actually does, the localization push for India, and the marketing realization most first-time founders learn the hard way.

In this episode:

- The Knowing-Doing Gap: Why less than 10% of what you read translates into actual behavior change.

- Personalized Action Steps: How two readers of the same book get completely different recommendations from Pustak's engine.

- Beyond Book Summaries: Why most reading apps stop at summarizing, and what closing the loop actually requires.

- The Pustak Coach: The habit tracker that turns "I read this" into "I'm doing this."

- 1,000+ Curated Books: Why she chose hand-picked esoteric books over bestseller volume.

- Localization for India: The market entry strategy and the regional-language translation push.

- From Consulting to Startup: The risk frameworks that translate, and the ones you have to leave behind.

- The Marketing Surprise: Why great products often sit unknown, and the lesson every first-time founder hits.

🎧 Full episode on all podcast platforms

💬 Do book summary apps actually move the needle on behavior change, or do they just feel productive? Let us know in the comments!

🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #Pustak #SelfHelp #ProductivityApps #ShrutaSatam #StartupJourney #ContinuousLearning #AIPersonalization #BookSummaries #Startups

Timestamps:

0:00 Intro

0:37 From 18 years at Deloitte and PwC to founding Pustak

2:57 The knowing-doing gap (less than 10% applied)

5:32 Personalization and per-reader action steps

7:04 Why retention is the biggest hurdle

8:18 How AI powers customization for each user

11:17 Working with her technical co-founder

12:39 The future of AI-powered learning

14:31 The roadmap: app launch and India localization

15:49 Competitors: Blinkist, Headway, and what's different

17:15 Curated books vs reading in full

22:30 Startup risk vs corporate risk management

24:26 What consulting teaches you about building products

30:50 The Pustak Coach habit tracker in detail

34:10 The marketing realization most founders hit

"I'm a good builder. I'm not a good seller."

I talk to Alejandro Zielinsky, founder of Bento, about building an Apple-style personal finance app as a solo iOS developer, why every budgeting app on the market is too rigid, and the distribution gap most builders never close. Alejandro spent ten years building iOS apps in dev shops and agencies, briefly worked at Ubisoft, and after his last crypto startup shut down, took a career break to ship Bento on his own.

We get into the modular widget system, the AI assistant Benny that reads your finances without ever writing to them, the moment OpenAI announced its own personal finance integration three hours before he launched, and the security gap most "vibe coders" miss.

In this episode:

- Bento, Built Like Apple Made It: Why he aimed for a Johnny Ive style personal finance app and what that meant for the design.

- Modular Dashboards: Why budgeting apps are too rigid, and how widget-based finance changes what you can track.

- Benny, The AI Money Assistant: How an intent-based agent reads your data, suggests changes, and never makes one without your approval.

- The OpenAI Sherlock Moment: Three hours before launch, OpenAI announced the exact thing he was launching.

- Why Vibe Coders Leak Secrets: The security gap most founders building with AI miss, and the GitHub tokens that get leaked every week.

- The Builder-Seller Gap: Why being a great builder makes you a worse marketer, and what to do about it.

- Games to Apps to Money: Why building games makes regular apps feel easy, and how that shaped Bento.

- Senior Devs With Agents: Why a 10x developer with Claude Code is closer to 100x, and what that means for hiring.

🎧 Full episode on all podcast platforms

💬 Should personal finance apps be modular like Bento, or prescribed like Monarch and YNAB? Let us know in the comments!

🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #Bento #PersonalFinance #iOSApps #AIAgents #SoloFounder #VibeCoding #ConsumerApps #Startups #AlejandroZielinsky

Timestamps:

0:00 Intro

0:26 The intercultural backstory and from games to iOS

2:16 What game dev teaches you about building apps

3:23 World models, agents and reinforcement learning

6:57 Claude Code and co-work tools in his workflow

8:21 The origin of Bento and the case against rigid budgeting apps

10:00 Building "if Apple made a finance app"

12:01 Three hours before launch, OpenAI Sherlocks him

14:08 Marketing channels for consumer apps (TikTok wins)

15:49 Modular dashboards: tracking a wedding, a trip, anything

18:13 Benny the AI assistant: intents, tools, user review gates

22:45 Plaid, privacy and the trust problem for solo developers

27:25 Iterating Benny across GPT model versions

30:11 Letterbox, PoliVita and the builder-seller trap

33:57 Advice for first-time app builders + the vibe coder security gap

"You can't delegate strategy to agents. You can't delegate human relationships to agents."

I talk to Davida Ginter, founder of Ilu, about building AI workers for the 90% of business owners who don't want to prompt. Davida started as a journalist, ran a services company on burnout prevention, wrote a book on it, and is now on her third startup, a platform that lets non-technical founders describe their business in plain language and have Ilu build the agents and workflows for them.

We get into the three shifts she's betting on (lean teams running with 50 agents, AI-augmented roles inside companies, and rethinking work instead of just automating it), why the junior role disappears in software too, and what AI still can't take off a founder's plate.

In this episode:

- The Non-Technical AI Workforce: Why Ilu builds agents from a business owner's context and goals instead of prompts.

- You Can't Delegate Strategy: What AI can and can't take off a founder's plate, and where humans still anchor the company.

- Lean Teams of 50 Agents: The 3-to-10-person company with a staff of agents, and the three shifts she's betting on.

- Why Burnout Has Nothing to Do With Hours: The real predictor isn't your calendar, it's whether you have the resources to do the work.

- "If Claude Is Your Junior": Why the junior role disappears in software too, and what training has to look like next.

- Don't Automate Broken Processes: Why the next wave is rethinking the work itself, not just automating what was already broken.

- The Agent-Web Gap: Why agents browsing the web like humans is a temporary hack, and what replaces it.

- Where AI Infrastructure Still Breaks: Latency, hallucinations, and the security problem nobody has solved yet.

🎧 Full episode on all podcast platforms

💬 What's the one thing on your plate you'd never hand to an AI agent? Let us know in the comments!

🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #AIAgents #Ilu #DavidaGinter #FounderBurnout #LeanTeams #FutureOfWork #NonTechnicalFounders #Startups #AI

Timestamps:

0:00 Intro

0:29 From journalism to building companies

2:18 Why she wrote a book on founder burnout

4:46 The biggest myth about burnout (it's not the hours)

7:18 The calendar exercise to protect your energy

8:45 What Ilu is and who it's for

10:42 How non-technical owners actually use it

13:32 The shift from prompts to business goals

15:46 Why most builder platforms miss 90% of the market

17:28 Builder involvement vs full autonomy

19:15 The three shifts: lean teams, AI roles, rethinking work

22:41 Why automating broken processes is the wrong move

27:12 If Claude is your junior, how do you get to senior?

28:47 The two-to-three year trajectory

31:15 Where AI infrastructure still breaks (security, agent-web, latency)

32:04 Where someone new to AI should actually start

"If you're a junior, you should go work in an office."

I talk to Adomas, founder of Remotely Talents, about why remote teams are going senior-only in the AI era, and what that does to everyone trying to get their first job. Adomas spent 10 years running a beverage company in Lithuania, sold it, ran e-commerce supplement brands, then built a remote recruitment agency on a "recruiter as a service" model that drops the 20-35% placement fees.

We get into where US companies are actually hiring now, why dev roles collapsed as a share of his placements, and the four-year SEO grind behind most of his leads.

In this episode:

- Recruiter as a Service: Why he ditched 20-35% placement fees for a flat monthly model that stops when the role is filled.

- The LatAm Shift: Why 65-70% of US remote roles now go to Latin America, and why the Philippines wave faded.

- Senior-Only Remote: Why he refuses to place juniors in remote roles, and what that means for how people get experience.

- The Dev Hiring Collapse: Why tech roles fell from 80% of his placements to under 10%, while marketing took over.

- Google Is a Backlinks Network: The four-year organic SEO grind behind most of his leads, and why GPT traffic is following.

- Where Paid Ads Break: $7k burned on Google search, bot-filled X ads, and the channels he'd actually bet on.

- Remote Onboarding: Why remote hires churn when companies skip the work of making them feel part of the team.

- The AI Squeeze: Smaller senior teams, AI-augmented hires, and the coaching academy he just launched for displaced juniors.

🎧 Full episode on all podcast platforms

💬 Should juniors really start in an office, or is remote-first still possible for entry level? Let us know in the comments!

🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #RemoteWork #Hiring #Recruitment #RemotelyTalents #Adomas #LatAm #SEO #AIandJobs #Startups

Timestamps:

0:00 Intro

0:22 What Remotely Talents does: recruiter as a service

1:34 How traditional placement fees work, and why he rejects them

3:05 Is remote hiring actually slowing down?

6:19 What companies get wrong about return-to-office

7:32 The biggest remote onboarding mistakes

11:02 From a beverage company to remote recruitment

14:36 Building the brand on organic traffic over four years

15:16 "Google is a backlinks network": the SEO playbook

18:01 Paid ads: Google search, X, and what actually works

21:20 How AI is reshaping the hiring landscape

24:37 Building funnels solo with AI, and the junior problem

28:55 Which regions are most in demand now

31:04 Why dev roles fell from 80% to under 10%

34:49 The remote hiring process, step by step

"Don't show me a TAM slide. Show me 200 customer discovery calls and 20 people on a waitlist."

I talk to Martin Tobias, founder and managing partner of Incisive Ventures, about why distribution is the only real moat left now that anyone can build software. Martin went from Accenture and Microsoft to founding three companies (taking one public as the last IPO of the dot-com boom) and 250+ angel investments before launching his pre-seed fund.

Martin walks through how he reads a founder in five minutes after 20,000 CEO meetings, why he spends three weeks on a PRD before letting Claude or Replit touch the code, and why the application layer will end up three to five times bigger than AI infrastructure.

In this episode:

- The Distribution Wedge: Why getting your product in front of customers is the only moat left when anyone can build the product.

- Don't Believe Your Own Hype: The $2B market cap on $10M of revenue, and the lesson he took from the dot-com peak.

- The 5-Minute Read: Why 20,000 CEO meetings let him pattern-match a top-10% founder almost instantly.

- Vibe Coding's Data Model Trap: Why he now front-loads a PRD and data model before vibe coding anything past a dashboard.

- The Death of the Junior Dev: Why a portfolio company fired three juniors to hire one senior, and the "how does anyone become senior?" problem.

- SaaS vs Labor: Why a $300B software market is really chasing a $4.5T labor expense.

- The First Five Hires: Why he avoids solo founders and never hires straight from big tech.

- Pot Odds in Pre-Seed: The poker math behind making bets you lose 90% of the time.

🎧 Full episode on all podcast platforms

💬 Is distribution really the only moat left, or does product still win? Let us know in the comments!

🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #PreSeed #VentureCapital #MartinTobias #IncisiveVentures #VibeCoding #B2BSaaS #AngelInvesting #Startups #AI

Timestamps:

0:00 Intro

0:24 From Accenture and Microsoft to founder to VC

4:13 "Don't believe your own hype": $2B cap on $10M revenue

5:20 Backing Google as an LP, DocuSign, and finding his B2B lane

7:36 The biggest mistakes first-time angels make

9:37 Reading a founder in five minutes after 20,000 CEOs

11:55 Why distribution is the only moat now software is cheap

13:36 The deal flow matching problem & InvestorMatch.Pro

15:19 Replit vs Claude Code: 450k lines for $10k

18:21 Why you need a PRD before vibe coding

21:00 The death of the junior developer

24:32 SaaS is $300B, labor is $4.5T

32:18 The first five hires & why he avoids solo founders

38:50 Application layer vs infrastructure layer

45:00 Poker, pot odds & the asymmetry of venture

"Distribution is a nightmare for everybody. But secretly, it's a product problem."

I talk to Jacob Counsell, product designer of 15 years in Silicon Valley tech and founder of LaunchChair.io, about why most vibe-coded apps feel broken after four months, why designers will touch code again after a decade of being told not to, and why founders complaining about distribution usually have a product problem they're afraid to admit.

Jacob breaks down the wedge LaunchChair plays in the vibe-coding space, the spec-aware prompt engine behind it, and why he thinks a team of three with agents now ships what fifty people shipped three years ago.

In this episode:

- Vibe Coding Slop: Why most Lovable and Bolt apps feel broken after four months of building.

- Distribution as Product: Why founders blaming distribution usually have a product problem they're afraid to name.

- The Full-Stack Designer Returns: Why designers will touch a lot more code in the AI era.

- The HCI Overcorrection: How we stopped hiring weirdos from art school and the internet got boring.

- The 5-Person Team Thesis: How a team of three with agents now ships what fifty people shipped three years ago.

- LaunchChair's Wedge: A spec-aware prompt engine that forces functioning features instead of broken Lovable mockups.

- The Silofication Problem: Why big tech ships bugs that sit unfixed for two-plus years.

- Baseline + A/B Testing: Why endless user research before launch is a trap, and what to do instead.

🎧 Full episode on all podcast platforms

💬 Should designers touch code in the AI era? Where do you land? Let us know in the comments!

🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #VibeCoding #ProductDesign #JacobCounsell #LaunchChair #Founders #AI #StartupBuilding #Distribution #Designers

Timestamps:

0:00 Intro

0:29 Why Jacob built LaunchChair: a wedge into the vibe-coding slop problem

2:08 Being technical + design: the full-stack designer advantage

3:30 How AI tools changed product design in the last year

4:30 The HCI overcorrection: why we stopped hiring weirdos from art school

6:38 Distribution is a nightmare — but secretly, it's a product problem

9:00 Agent orchestration for LinkedIn (without becoming a Claude Slop Cannon)

11:55 The full-stack designer is back: designers will touch a lot more code

15:23 Smaller teams, fewer silos: why a team of 3 ships what 50 used to

18:35 When a fast-and-loose team works (and when it doesn't)

22:58 Baseline + A/B testing beats endless user research

24:09 LaunchChair's wedge: spec-aware prompts that build functioning features

28:59 BuildHop and PromptJoy: two side products dogfooded with LaunchChair

33:50 Why most vibe-coded apps look broken (the load-more example)

35:30 Acceptance criteria + remediation prompts: how LaunchChair fixes hallucinations

35:57 The future of design: designers shipping production-ready features

"Why would you give a robot human weaknesses?"

I talk to Jay Kapoor, co-founder and general partner of VSC Ventures, about the "dirty, dusty, and dangerous" industries that VCs keep skipping over and why he thinks humanoid robots are the wrong bet. Jay started his career at the NFL and Madison Square Garden before spending 11 years investing in seed-stage companies, and now backs founders building AI and robotics for the deskless workers powering $80T of global GDP.

Jay walks through why 90% of US factories still don't have a single robot in 2026, why the death of systems integrators is opening a massive deployment gap, and why the next great founders no longer need a decade in their industry to build in it.

In this episode:

- The DDD Thesis: Why dirty, dusty, and dangerous industries are the most underpriced sector in venture today.

- The 90% Factory Gap: Why 9 out of 10 US factories still don't have a single robot in 2026.

- The Death of Systems Integrators: Who's responsible for actually deploying robots when the consultants disappear.

- Why Humanoids Are a Pipe Dream: The case for purpose-built robotics over Optimus and Figure.

- The 500% Turnover Job: Recycling sorters quit before they find their parking spot, and why automation is the only fix.

- The 4-to-1 Electrician Shortage: Why Jensen Huang says plumbers and electricians are the bottleneck on AI compute.

- Founder-Led Storytelling in VC: Why VSC Ventures runs a 30-person PR agency for portfolio companies.

- Founder-Market Fit Is Dead: Why a decade in an industry is no longer required to build in it.

🎧 Full episode on all podcast platforms

💬 Humanoid robots: pipe dream or future of labor? Let us know in the comments!

🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #Robotics #AI #VC #VSCVentures #DataCenters #Manufacturing #Tradespeople #Startups #Founders

Timestamps:

0:00 Intro

0:35 The DDD thesis: dirty, dusty, dangerous industries explained

4:04 Why labor shortages + generational ownership shifts + AI converge into the opportunity

4:58 From the NFL to backing robots: Jay's path through media into venture

6:52 Building VSC Ventures around founder-led storytelling

9:35 Why founder-CEOs becoming industry champions is the new playbook

12:35 Why most VCs miss DDD opportunities (and how that creates pricing alpha)

16:13 Why fundraises are now won by speed of execution mid-process

19:28 Where capital is still underfunded: implementation, not robots

21:30 The 90% gap: why most US factories still have zero robots

23:39 The data center bottleneck and SoftBank's $40B automation bet

24:22 Why Jay is skeptical about data centers in space

32:42 Humanoid robots: pipe dream or the future of labor?

35:45 Purpose-built vs general-purpose robots in industrial settings

38:45 Where the worst labor shortages will hit next: electricians and plumbers

41:49 Where to find Jay: Twitter, LinkedIn, and the Climb show

"Voice is the last moat."

I talk to Sadok, growth and AI operator and founder of Bloomberry, about why the next defensible thing for solo founders isn't a feature but their authentic voice. Sadok spent the last decade running paid growth at Air Wallex, Pure Storage, Procore and Google before bootstrapping Bloomberry, an end-to-end content distribution system that learns your voice over time and writes in it.

Bloomberry's research has identified 7,000+ cadences, structures, and phrases that AI consistently uses, and Saduk thinks killing those patterns is the difference between content that converts and content that gets scrolled past.

In this episode:

- AI Sentence DNA: The 7,000+ cadences and phrases that flag AI-generated content (and how to strip them out).

- Voice as the Last Moat: Why authentic founder voice is the one thing AI cannot replicate at scale.

- The 1-Comment First Customer: How Sadok's first ever LinkedIn comment, on day 2 of launch, converted into a paying user.

- Bootstrap vs Venture: Why he is deliberately avoiding VC for now, and what burnt-out venture-backed founders are signaling.

- Audience Before Product: Why content distribution should start before the product exists, not after.

- Founder-Led Marketing: Why podcast appearances and personal posting beat scaled outreach for early-stage founders.

- Protect the Mid-Funnel Leak: The unglamorous fix most founders skip while chasing top-of-funnel.

- When to Raise: The $2K to $5K MRR threshold below which VCs will not take a meeting.

🎧 Full episode on all podcast platforms

💬 Bootstrap or raise: where do you land for an early-stage SaaS in 2026? Let us know in the comments!

🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #Bloomberry #AISlop #VoiceMoat #Bootstrapping #FounderLedMarketing #ContentMarketing #PerformanceMarketing #SaaS #Startups

Timestamps:

0:00 Intro

0:18 Killing AI slop: the thesis behind Bloomberry

1:21 What Bloomberry actually does and why ChatGPT can't replace it

4:30 AI Sentence DNA: 7,000+ cadences and phrases that flag AI writing

6:17 Why he's bootstrapping instead of raising VC

7:52 The 1-comment first customer story

9:47 From Fry's Electronics retail floor to growth operator

13:30 When to start with paid ads (Google and Bing, not Facebook)

17:45 What "what sticks" actually means in early iteration

24:13 Why FinTech is the wrong industry for solo founders

27:41 The $2K-$5K MRR threshold for raising venture

31:56 Why B2B beats B2C for monetization

37:19 Building an audience in an AI-saturated world

39:05 Audience first, product second

41:24 Where to find Bloomberry

"If you take the year Airbnb did its seed round... if you invested in every single one of the 2,500 deals that year, and everything went to zero except Airbnb, you'd still return a couple thousand X."
In this episode of DN, Niklas talks to Colin Gardiner, the founder of Yonder VC (a pre-seed fund exclusively focused on marketplaces and network effects) and the former Chief Revenue Officer of Outdoorsy, where he helped scale the business to billions in rentals.

Colin breaks down the absolute hardest challenge in tech: the "chicken or the egg" cold start problem. He explains why founders who buy ads to acquire demand early on are creating a "false positive" for product-market fit, and why building a "SaaS-enabled marketplace" is the ultimate cheat code to onboarding supply. The conversation also dives into the brutal mathematics of Venture Capital, the massive difference between "Market Making" and "Market Taking," and why Colin expects every single founder he invests in today to be completely AI-native.

In this episode:
• The Cold Start Problem: How to successfully launch a 2-sided marketplace from zero using the "SaaS-enabled" playbook (used by OpenTable and Outdoorsy).
• The False Positive of PMF: Why paying for demand and running early ads is the most dangerous trap a marketplace founder can fall into.
• Market Making vs. Market Taking: Why startups that create new markets (Airbnb, Polymarket) reach unicorn status, while commodity markets (Freight) struggle to survive.
• The VC Power Law: The staggering math behind Airbnb's seed round, and why Yonder VC prioritizes a wide "surface area" over trying to pick a single winner.
• The AI Amplifier: How Colin coded his own AI automations to parse through 900+ pitch emails, and why VCs will pass on you if you aren't an AI-first founder.
• Pre-Seed Fundraising in 2024: Why you should delay raising venture capital as long as humanly possible to prevent massive equity dilution.

🎧 Full episode on all podcast platforms
💬 Are you building a SaaS product or a 2-sided marketplace? Let us know in the comments!
🔔 Please like and subscribe! Every subscriber helps our channel grow.

#DN #Marketplaces #StartupFounder #ColinGardiner #YonderVC #VentureCapital #SaaS #NetworkEffects #ColdStartProblem #SiliconValley

Timestamps:
0:00 Intro: Niklas meets Yonder VC founder Colin Gardiner
0:47 Studying the US Labor Market with Janet Yellen to scaling Outdoorsy
4:30 Solving the "Cold Start" problem: How to bootstrap supply
7:38 The biggest mistake founders make: Buying ads to force product-market fit
9:10 The "SaaS-Enabled Marketplace" framework (Outdoorsy, OpenTable, Google)
11:19 Market Making vs. Market Taking: Why commodity marketplaces fail
15:15 The VC Power Law: The insane math behind Airbnb's seed round
17:47 What Yonder VC looks for in pre-seed founders (High agency & stubbornness)
20:17 How AI is fundamentally changing the way VCs underwrite startup investments
23:08 Why AI is a pure amplifier that is widening the skill gap between founders
24:06 The "Retrenchment Phase": Why engineers are focusing on optimizing token costs
25:58 Final advice: Do this before raising a pre-seed marketplace check