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Joe Holberg is the Founder & former CEO of Spring, a workplace financial wellness platform that began D2C, pivoted to employer-paid, and became a top-rated U.S. offering for three consecutive years, serving 25,000+ users. He bootstrapped from 2015 to 2018, raised a $1M seed, and sold Spring to Mariner Wealth Advisors in 2023, remaining through early 2025. Before Spring, he taught with AmeriCorps on Chicago’s West Side and built CS education at Google. A first-generation college graduate who once slept in his car to finish school, Joe is now a declared candidate for the 58th Mayor of Chicago.

Holberg’s catalyst was seeing financial confusion across backgrounds—even among peers with professional-class parents. Early Spring had universal interest but low willingness to pay; the unlock was changing the buyer (HR) and making a firm pricing decision: “Pricing isn’t science—it’s a decision.” In this conversation, he discusses building Spring, the B2B pivot, lessons from pricing and sales, and his views on city governance, housing supply, business climate, and tech-literate leadership. This episode presents his perspective and experiences as a founder and candidate.

Key Topics Covered:

• What Spring was: outcomes-oriented financial wellness delivered as a workplace benefit.
• D2C → B2B: universal desire vs. $20/mo friction; employers fund, employees benefit.
• Pricing lessons: fewer options, clearer value, faster decisions.
• Builder arc: bootstrapping (2015–2018), $1M seed, top-rated product, 2023 acquisition; stayed through early 2025.
• Sales scrappiness: writing a book to establish credibility with HR leaders.
• Entering politics: motivations, background across economic circumstances, and emphasis on tech literacy.
• Chicago context (as framed by the guest): population and business trends; collaboration vs. adversarial postures.
• Governance mechanics: mayor/city council dynamics; CPS school board changes; housing supply constraints.
• Campaign posture: outsider experience and how he frames his narrative as a candidate.

Chapters:

(00:36) Spring’s origin — addressing financial education gaps observed across income levels.

(01:43) Early arc — glow-stick hustle; first-gen college; sleeping in the car; AmeriCorps; Google; leaving to build.

(04:21) “Credibility book” — unconventional sales asset for HR conversations.

(06:14) The pivot — strong demand, low D2C conversion; employer-paid model.

(08:43) Building years — 2015 start, 2018 $1M seed, solo grind → top-rated 3 years, 25k+ users; 2023 acquisition; through early 2025.

(12:39) Pricing "aha" — choosing and owning a price to accelerate qualified deals.

(14:37) Why enter politics — empathy across the income spectrum; need for tech-aware governance.

(20:02) Entering the arena — outreach, mentorship, and announcing candidacy.

(24:23) Status quo (guest’s view) — resident/business trends; collaboration with builders.

(27:22) How Chicago governance works — mayor vs. council; CPS board; housing supply.

(30:55) Voter expectations — vision, ideas, results.

(32:32) Closing themes — affordability, fiscal considerations, and civic participation.

Where to find the Joe Holberg:
X: @holbergj
LinkedIn: linkedin.com/in/joeholberg
Website: joeforchicago.com

Where to find David Phillips:
X: @davj
LinkedIn: linkedin.com/in/davjphillips

Disclosure / Non-Endorsement Note:

The views expressed by the guest are their own and do not reflect the views of David J. Phillips, Fondo or the Startup Growth Podcast. Appearance on the podcast does not constitute an endorsement of any candidate, campaign, or policy proposal. This episode is provided for informational purposes only.

Jay Ram is Founder & CEO of Hud, the evaluation and RL platform for AI agents. Hud helps startups build RL environments, run fast reward loops, and plug into any RL backend—so teams can cut costs and push last-mile accuracy once they've hit PMF. Before Hud, Jay left a lucrative quant career, shipped an AI prank-calling app that briefly hit #1 on the App Store (≈500k calls), and decided he wanted harder problems and smarter customers. He's a YC W25 alum; Hud is already used by researchers at foundation labs and is expanding into enterprise environments.

Jay's catalyst was realizing he didn't want to just talk weekends—he wanted to build. He and his co-founders first tackled computer-use evals for labs. Inside that work, the language shifted: labs asking for "evals" really needed environments—places where you design rewards, iterate, and actually improve model behavior. Today, Jay frames Hud as the "Next.js of RL environments": opinionated lifecycle, backend-agnostic training, and infra that returns signal fast. Early on, use a foundation model; post-PMF, train your own with SFT/RL—that's where environments matter. Looking ahead, he sees post-training speciation: domain-tuned models for finance, accounting, creative tooling, and more—because teams will own more of their stack again.

Key Topics Covered:

· What Hud is: tools to set up your agent for RL, define tasks, shape rewards, and plug into RFT/other RL backends.
· From evals to environments: why scores measure but rewards improve—and how iteration loops change outcomes.
· Where it fits: use foundation models early; post-PMF train your own for cost leverage + last-mile gains.
· Design + infra: a new category needs opinionated UX and fast results; why lab researchers use Hud for computer-use evals.
· Market timing: the "DeepSeek moment" pulled RL from hobbyists into enterprise interest in 2025.
· Pre-train vs post-train: scale vs accuracy + domain depth—and why post-training is the real edge.
· Future of work: enterprises will own more of the stack; model speciation by domain.
· Reality check: agents ace toy DBs, struggle in production; modeling real environments is the unlock.
· YC W25 arc: vision matched the original app more than mid-batch; enterprise demand is catching up now.
· Finance stack aside: keep ops boring; focus cycles on shipping product (Fondo shoutout in-episode).

Chapters:

(00:15) Cold open — "We give you all the tools to set up your agent for RL."
(00:59) Intro — Jay Ram, Hud, and the origin story
(01:41) What Hud does — build RL environments; backend-agnostic (OpenAI RFT, Thinking Machines, etc.)
(02:12) Where environments fit — early: foundation models; post-PMF: train for cost + accuracy
(02:50) From quant to builder — leaving Wall Street to make things
(03:30) The prank-calling app — #1 on App Store; ≈500k calls; why the customers weren't it
(04:40) Evals → environments — labs' "eval" asks were really RL environments with rewards
(05:40) Evals vs RL — scores vs rewarded steps; how updates happen
(07:14) Hard parts — opinionated design + infra speed for researchers and teams
(08:08) Before Hud — no toolkit/standards; emerging gymnasium-style efforts vs Hud's opinionated path
(09:25) YC W25 — applying, partners (Aaron & Matt), why YC felt like "actual college"
(11:05) Vision vs timing — market caught up; enterprises now exploring environments
(12:20) Trend — teams rolling their own models post-PMF (SFT/RL)
(13:01) Today's fragmented stack — hosting, inference, data; Hud's role in the loop
(13:48) The "DeepSeek moment" — hobbyist RL → enterprise interest in 2025
(15:57) Future of agents — own the stack, post-training speciation
(18:26) Why end-to-end is hard — production data systems need real environments
(19:29) Forward-deployed labs — domain hires and environments; how Hud plugs into RFT
(20:15) Rapid wrap — it's early; the stack is shifting fast

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Where to find Jay Ram:
X: @jayendra_ram
LinkedIn: www.linkedin.com/in/jay-ram-29003b198/

Where to find Hud:
X: @hud_evals
Website: hud.ai

Where to find David Phillips:
X: @davj
LinkedIn: linkedin.com/in/davjphillips

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Brought to you by:‍

Fondo — All-in-one accounting for startups: fondo.com

Kevin Xu is Founder & CEO of Alpha AI, your “AI money friend” that plugs into real-time markets and your portfolio to explain what just happened—and what matters next—inside a simple chat. Before Alpha, Kevin became a WallStreetBets folk hero as turning $35K in a 401(k) into $10M through high-conviction swing trades. He previously founded Fan Hero (YC S13), worked at Stripe (~#300) and Google/YouTube, and appeared in MSNBC Studios’ Diamond Hands on Peacock.

Kevin’s catalyst was realizing the products he loved—Google, Wikipedia—were built by real people. That sent him to YC, then Stripe for world-class reps, then into the internet’s finance classroom: Reddit. He posted every win and loss, learned in public, and distilled trading into rules like “If it’s good enough to screenshot, it’s good enough to sell.” After building After Hour to socialize trading, he’s now productizing that edge with Alpha AI: a proactive, personable copilot designed to build money confidence for the next million millionaires.

Key Topics Covered:

 • What Alpha AI is: a chat-first AI money friend with market context + your portfolio, proactive “what just happened” nudges, and customizable character.
 • From WSB to product: turning public receipts (35K→10M) into a system—floors, catalysts, concentration, disciplined exits.
 • Earnings humility: why reports are a coin flip; behavior, sizing, and timing are the real edges.
 • Founder arc: Stanford → YC pivot muscle → Stripe discipline → Google scale → After Hour → Alpha AI.
 • Culture shift: finance as entertainment/sport; people don’t need courses—they need context at the right moment.
 • Design over dashboards: one infinite chat thread > scattered tools; AI handles background work, humans make decisions.
 • Missed GME, learned anyway: thesis right, timing wrong—how to keep momentum without hero trades.
 • Distribution & trust: followable identities, real screenshots, timely alerts—how credibility compounds.
 • Building in 2025: attention-maxxing, shipping fast, leaning into new formats (e.g., Sora experiments).
 • Finance stack mindset: keep ops boring—Fondo for the back office, Brex for cash/cards—so you can ship product.

Chapters

 (00:00) Cold open — “I wanted a cool dream”: realizing real people build the internet
 (00:59) Intro — Kevin Xu, Alpha AI, and the origin story
 (01:28) Stanford → YC S13 double-interview; pivot from Alpha Labs to Fan Hero
 (06:11) Stripe (#~300) → Google/YouTube: seriousness vs. internet-native play
 (09:00) WallStreetBets culture: memes, transparency, learning in public
 (12:26) The 401(k) stake: missed HR toggle → $35K starting gun
 (14:53) Early pandemic plays: APT, CODX; the floor + catalyst lens
 (17:33) Chasing pops: cruises, Chewy-era stories, and disciplined exits
 (20:11) The GME almost: all-in October, out in December; lessons on timing
 (23:33) Million-dollar swing days; detachment and the screenshot rule
 (25:10) Big 5 finale → $10M peak; why earnings are coin flips
 (27:15) After Hour: social finance, trust via receipts, real-time notifications
 (30:50) Alpha AI: proactive context, AI friends as the interface
 (32:52) Beyond investing: building money confidence; simple company finance stack

Where to find Kevin Xu:

LinkedIn: https://www.linkedin.com/in/imkevinxu
X: https://x.com/kevinxu
Instagram: https://www.instagram.com/founderkevin

Where to find Alpha AI:

Website: https://alpha.so
X: https://x.com/alpha_ai
Instagram: https://www.instagram.com/chatwithalpha

Where to find David Phillips:
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X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: fondo.com

Daivik Goel is Co-founder & CEO of Shor, a global payroll platform for startups. Traditional EOR providers charge around $7,000 per year to manage an employee earning $20,000 per year. Shor uses automation to reduce costs and embeds payroll actions into Slack and WhatsApp through AI agents, so founders can request tax documents or payment updates without opening another dashboard.

Daivik and co-founder Avi Konduru submitted their YC application at 7:59 PM, one minute before the deadline. After multiple prior rejections, they got an interview, then a follow-up call, then acceptance. They started YC with a crypto payment idea, pivoted five weeks before demo day to global payroll—a problem they'd worked on two years earlier—and shipped contractor payroll within a week. They've since raised funding and are scaling.

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Key Topics Covered:

• What Shor is: global payroll/EOR rebuilt for startups; automation handles ops, AI teammates deliver docs/actions in Slack/WhatsApp.

• From clever to sellable: pivoted inside YC from crypto/fiat rails to payroll where they had access and clear pain.

• Cost math that breaks: why legacy EORs charging ~$7k/yr on a $20k salary fail SMB/unit economics—and how Shor attacks the middle.

• Ship speed as strategy: prior fintech muscle let them launch contractor payroll in one week (KYC/KYB, payouts, tax flows).

• Design →  dashboards: move work to the user (chat interfaces), keep humans making decisions, let AI do the background jobs.

• Distribution as a moat: serve the massive long tail priced out by incumbents; win on affordability + responsiveness.

• YC pragmatism: plain-English interviews beat pitch theater; momentum over mockups.

• Execution after Demo Day: demand first, fundraising next, delivery always—scaling compliance/country coverage without losing speed.

• Founder operating cadence: daily inches over hype cycles; embrace “pivot hell,” but pick battles you can actually win with customers.

• Finance stack mindset: reliability and support matter most when back-office tools fail—opt for vendors who show up.

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Chapters

(00:00) Cold open — the 7:59 PM YC submission
(00:37) Intro — Davik & what Shor is (affordable global payroll)
(02:51) Waterloo → founder mindset and process discipline
(06:05) YC journey and batch dynamics
(08:26) First leap without an idea + early GTM lessons
(11:56) Marketplaces are hard — takeaways that shaped Shor
(14:56) The last-day YC rush & the crypto/fiat idea
(24:49) Pivot hell inside YC → choosing global payroll
(27:28) Shipping contractor payroll in one week + why now (AI/stablecoins)
(29:33) Fundraising wrapped; AI teammates over dashboards; what’s next

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Where to find Daivik Goel:

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Multilink: https://bento.me/daivik
LinkedIn: https://www.linkedin.com/in/daivikg
X: https://x.com/DaivikGoel
Instagram: https://instagram.com/daivikgoel
YouTube: https://m.youtube.com/channel/UCzkRfrCXIrW1v60Wyasgq7Q
Substack: https://daivikgoel.substack.com
TikTok: https://tiktok.com/@daivikgoel

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Where to find Shor:

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Website: https://tryshor.com
X: https://x.com/shor_pay
LinkedIn: https://www.linkedin.com/company/shorpay
Instagram: https://www.instagram.com/shor.pay/
YouTube: https://www.youtube.com/watch?v=OF1m1H0arYY

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Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Cody Schneider is the Founder & CEO of Graphed, an AI agent for marketing analytics. Graphed plugs into common data sources, manages the data warehouse, and lets marketers chat with their data to generate on-demand visuals—“stacked bar of new vs. total users week over week,” “add a line of best fit,” and similar prompts. It’s built to handle scale (Cody mentions onboarding ~25M rows of Facebook data) and to avoid rate limits and sluggish queries by owning the warehousing layer.

In this episode, Cody outlines a practical path from data sprawl to decisions: skip steep BI learning curves and ticket queues; connect sources and ask in plain English for charts and basic analyses. He also talks about how creative volume now functions as targeting—ship lots of concepts, let algorithms find buyers—and positions Graphed as the way to see what’s working without waiting on a data team. For founders and marketers, it’s a clear primer on turning raw rows into faster feedback loops.

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Key Topics Covered:

• What Graphed is: an AI agent for marketing analytics that connects sources, manages the warehouse, and lets you chat to generate charts and basic analyses. 
• From tickets to answers: why BI queues and tool learning curves slow teams—and how a chat interface shortens time-to-insight.
• Scale as a requirement: handling large datasets (e.g., ~25M rows of ads data) and avoiding rate limits via a managed warehousing layer.
• Roadmap preview: proactive weekly Slack briefs that summarize what changed and why (future functionality).
• Creative = targeting: in 2025 paid acquisition, high-volume creative acts as the audience filter while algorithms find buyers.
• Stacking S-curves: double down on the working channel, then layer the next before growth plateaus.
• Arbitrage windows: underpriced media (e.g., creator CPMs ≈ $2; low-cost local streaming TV CPMs) and why illiquid channels create edge.
• Unit economics discipline: CAC/ARPU/LTV/payback thinking—losing on month one can be rational if LTV justifies it.
• Validation before build: use ads and landing pages to test demand—even before a product exists.
• Founder ops stack: practical setup (e.g., Stripe Atlas, Mercury, Carta, Fondo) to keep focus on product and sales.

Chapters

(00:00) Introduction to Graphed.com
(02:12) Cody's Journey at Rupa Health
(05:36) Growth Strategies and Metrics
(11:19) Paid Advertising Insights
(15:10) Exploring Programmatic TV Advertising
(18:57) The Vision Behind Graphed.com
(21:57) Building a Financial Stack for Startups

Where to find Cody Schneider:

LinkedIn: https://www.linkedin.com/in/codyxschneider

X: https://x.com/codyschneiderxx 

Where to find Graphed:

X: https://x.com/graphed
Website: https://www.graphed.com

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Where to find David Phillips:
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X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Craig Lewis is the Founder & CEO Ogentic AI, builder of Zing—an AI-native enterprise browser that turns intent → action in a secure, workflow-native workspace. Before Ogentic, he founded Gig Wage (750k contractors paid, ~$1B moved, $25M+ raised) and learned payroll inside ADP. That operator muscle fuels Ogentic’s pace: incorporated in June, alpha in July, beta in August. He also serves on the governing board at MassChallenge and angels actively.

In this episode, Craig shares velocity advice like: ship before perfect (feedback > stealth), build pro-human AI (human-in-the-loop), and treat fundraising like sales (expect 19 no’s, optimize investor–founder fit, when it’s right—TTFM). He outlines the back-office stack that keeps your startup in good shape and his board philosophy: offer perspective, not prescriptions. If you’re building enterprise AI—or just want to move in weeks, not quarters—this one’s for you.

Key Topics Covered:

• Ogentic AI focuses on enterprise productivity and automation.
• Building a strong back office is crucial for startups.
• Fundraising is a numbers game; persistence is key.
• Feedback is essential for product development.
• AI will replace some jobs but also create new ones.
• Having a technical co-founder can accelerate growth.
• Navigating the fundraising landscape requires understanding investor fit.
• MassChallenge supports entrepreneurs in solving global challenges.
• The future of work will involve augmenting human capabilities with AI.
• Startups should find their niche in the AI market.

Chapters

(00:00) The Rise of Ogentic AI

(13:37) Building a Strong Back Office

(17:02) Navigating Fundraising Challenges

(19:14) The Role of MassChallenge

(23:12) AI and the Future of Work

(27:40) Fundraising in the AI Era

Where to find Craig J. Lewis:

Linkedin: https://www.linkedin.com/in/mrfutureofwork

X: https://x.com/CraigJamalLewis 

Instagram: https://www.instagram.com/craigjlewis

Where to find Ogentic AI:

 
Website: https://ogenticai.com
LinkedIn: https://www.linkedin.com/company/ogenticai
X: https://x.com/ogenticai
Instagram: https://www.instagram.com/ogenticai

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Where to find David Phillips:
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X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Grace Gong is the Founder & CEO of Smart Venture Media, podcast host, angel investor, and author. She’s interviewed 500+ founders, investors, and operators on her podcasts, then parlayed that network into a high-signal community: curated founder–VC dinners, conferences (including the Smart AI Summit), and rooms where intros turn into customers and checks. The flywheel started during the pandemic with 5 pm Friday Zooms—and evolved into tightly curated IRL events supported by sponsors and operators.

In this episode, Grace outlines a practical approach to community-building: curate for outcomes, not optics (every seat should benefit from every other seat). Her angel filter doubles as her invite list. Online → IRL is the sequence: earn trust digitally, concentrate it offline.  For founders aiming to stand out without burning cash, this is a clear primer on turning audience into deal flow.

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Key Topics Covered:

• Building community has to happen organically.
• Engaging with entrepreneurs can lead to unexpected opportunities.
• Sales and storytelling are crucial skills for success in VC.
• Offering value to others is key to building relationships.
• The people you meet at events can significantly impact your journey.
• Planning events requires meticulous attention to logistics.
• Creating a curated experience enhances networking opportunities.
• AI is transforming the media landscape and how we build companies.
• Networking is essential for both founders and investors.
• Continuous learning and adaptation are vital in the fast-paced tech world.

Chapters

(00:00) Building Community: The Organic Approach
(02:50) Journey into Venture Capital: From Real Estate to VC
(05:44) Insights from Interviews: Lessons Learned in VC
(08:53) Angel Investing: Key Considerations
(11:51) Creating Value: The Importance of Community
(15:02) Event Planning: From Small Gatherings to Large Conferences
(17:59) The Smart AI Summit: Curating Experiences
(20:54) Future of Media: Building with AI
(23:48) Final Thoughts and Online Presence

Where to find Grace Gong & Smart Venture Media:

Linktree: https://linktr.ee/gracegong115

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Where to find David Phillips:
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X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Collin Wallace is a partner at Lobby Capital with 20+ years as an engineer, inventor, operator, and investor. Before Lobby, he was Managing Director of Techstars Silicon Valley, launching the first two Bay Area accelerator programs with JPMorgan and eBay. He founded FanGo (Techstars S10)—acquired by Grubhub in 2011, where he became Head of Innovation (OrderHub + pre-IPO patents)—and later co-founded ZeroStorefront (YC W19), acquired by Thanx in 2022. Collin advises the Roelof Botha & Huifen Chan Innovation Program, co-teaches Startup Garage at Stanford GSB, has run two YC Demo Day Funds, and has invested in 80+ startups (e.g., Payjoy, Landed, Mosaic Voice, Postscript, Vellum).

In this episode, Collin gives founders some great advice: you’re running two businesses (product for customers, equity for investors). Fund math in concentrated portfolios means ~2 of ~20 bets must carry returns; with dilution to ~10% at exit, winners need multi-billion-dollar potential. Sequence your proof: Pre-seed = prove value; Seed = prove people pay (repeatably); Series A = scale what’s already repeatable. Don’t scale misses (the Steph Curry test). And match capital to your vehicle - venture is rocket fuel: perfect for rockets, destructive for "pickup trucks".

Key Topics Covered:

• Running a startup involves selling to customers and investors.
• Different VCs have varying expectations based on fund size and strategy.
• Founders should tailor their pitches to the specific needs of investors.
• Understanding investor dynamics can improve fundraising success.
• Successful founders diverge from conventional thinking in their industries.
• Ambition and hustle are key traits for founders.
• Expectations change significantly after receiving funding.
• Consistency and repeatability are crucial for scaling a startup.
• Community engagement can foster innovation and collaboration.
• The back office is essential but often seen as a distraction.

Chapters

(00:00) Introduction to Colin Wallace and His Journey
(02:14) The Shift in Growth Expectations for Startups
(05:03) Understanding Investor-Fit and Fundraising Dynamics
(11:12) The Importance of Founder Attributes
(17:15) Navigating the VC Landscape and Expectations
(21:03) Post-Funding Realities for Founders
(22:40) Understanding Seed Capital and Series A Expectations
(25:19) The Evolution of Funding: Series B and C
(29:05) Coaching the Next Generation of Founders
(32:09) Building the Back Office: The Unsung Hero
(35:42) Community Building and Inclusive Events

Where to find Collin Wallace:

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Linkedin: https://www.linkedin.com/in/collin-wallace/ 

X: https://x.com/pithyprof 

Website: https://lobby.vc/people/collin-wallace/ 

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Where to find Lobby Capital:
Linkedin: https://www.linkedin.com/company/lobby-capital/
X: https://x.com/lobby_vc
Website: https://lobby.vc/

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Where to find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Alessandro Chesser is the founder and CEO of Dynasty, a startup focused on making Qualified Small Business Stock (QSBS) trust stacking accessible to founders. Before launching Dynasty, he led sales at Carta from the early days to roughly $300M in ARR, gaining hands-on insight into equity workflows, 409A dynamics, and how distribution is built around real, recurring needs. Dynasty offers a subscription service—$1,500 per year for up to four family trusts—that includes trust creation, annual administration, and tax return filing, turning a traditionally bespoke, high-cost process into something founders can set up early in their journey.

In this episode, we unpack the mechanics and timing that make—or break—QSBS outcomes. We cover the core tests (acquiring shares before $50M in assets, five-year hold, qualified C-corp status), state-level differences (New York recognizes QSBS; California does not), and why early planning can start both the QSBS and long-term capital gains clocks while avoiding later surprises. 

Chesser talks about trust stacking—gifting shares into multiple family trusts so each may pursue its own QSBS exclusion—and notes practical guardrails and expert advice for dong it right. Beyond the tax planning, Chesser shares go-to-market lessons from Carta and Dynasty: using the network effect (e.g., certificates signed), creating urgency with must-do workflows (like 409A), iterating growth levers monthly, hiring decisively, and using social + creator partnerships instead of traditional cold outbound. The result is clear: tactical advice for founders on when to exercise, when to gift, how to document, and how to avoid the common QSBS pitfalls discussed in the conversation.

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Key topics covered

- QSBS allows startup shareholders to sell up to $15 million tax-free.
- Most startups qualify for QSBS, but there are specific criteria.
- Holding shares for at least five years is crucial for QSBS eligibility.
- The new rules under the big beautiful bill change QSBS eligibility timelines.
- Dynasty helps founders maximize QSBS benefits through trust stacking.
- Early exercise of stock options can prevent alternative minimum tax issues.
- Filing an 83B election is essential for QSBS qualification.
- Social media is a powerful tool for startup growth and marketing.
- Building partnerships with influencers can enhance visibility and credibility.
- The cost of setting up trusts for QSBS is significantly lower with Dynasty.

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In This Episode, We Cover

(00:00) Introduction to QSBS and Its Importance

(06:35) Understanding QSBS Eligibility and Benefits

(13:08) The Role of Dynasty in Maximizing QSBS Benefits

(16:29) Alessandro's Journey and the Birth of Dynasty

(18:36) Growth Strategies and Lessons from Carta

(27:14) Leveraging Social Media for Growth

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Where to Find Alessandro Chesser:

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LinkedIn: https://www.linkedin.com/in/alessandro-chesser-84763748

X: https://x.com/SandroChess

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Where to Find Dynasty:

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Website: https://www.getdynasty.com

LinkedIn: https://linkedin.com/company/getdynasty

X: https://x.com/getdynasty_com

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Where to Find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Jeff ‘Jiho’ Zirlin is a co-founder of Sky Mavis, the team behind Axie Infinity and the Ronin blockchain. At the forefront of Web3's most groundbreaking experiments, Jeff helped transform Axie from a small crypto-native community into a cultural phenomenon that onboarded millions to blockchain technology. With over $4 billion in NFT trading volume - earning a Guinness World Record - Axie didn't just talk about bringing people to crypto; it actually did it. Beyond Axie, Jeff pioneered the Ronin blockchain, which now hosts 70+ games and has proven that purpose-built infrastructure can unlock exponential growth for crypto applications.

In this episode, we trace the evolution of Web3 gaming from its origins in the CryptoKitties community to today's institutional adoption cycle. The conversation explores how manual onboarding and white-glove user acquisition laid the foundation for viral growth. Jeff shares the pivotal moments that shaped Axie's trajectory: tokenizing experience points, creating the "play-to-earn" model that democratized crypto mining, and the strategic decision to build their own blockchain when existing infrastructure couldn't scale. We also examine the current state of crypto gaming, the shift from retail mania to Wall Street adoption, and why the next wave of innovation might create entirely new cultural mediums rather than just new ways to make money.

Key topics covered:

• The CryptoKitties Mafia: How a December 2017 viral game spawned the founders of Axie, OpenSea, and the modern NFT ecosystem
• Manual onboarding at scale: From personally gifting Axies to Binance angels to hitting 2 million users
• The biological insight: Why CryptoKitties failed (no death = exponential breeding) and how ecosystem balance became Axie's core principle
• 300 users was "#1": How being the largest crypto game with just 300 players became a marriage proposal line - and a growth trajectory
• Tokenizing the game economy: The moment players asked to buy experience points and accidentally invented play-to-earn
• "You can't build your startup on another startup": Why Loom Network's failure forced Sky Mavis to create Ronin blockchain
• The Ronin Effect: Deploying at 30,000 users, scaling to 2 million in six months - and the infrastructure playbook now powering 70+ games
• The Uniswap wealth effect: How every Axie player unexpectedly received $4,000, creating a growth catalyst nobody predicted
• Why gaming onboards better than DeFi: More people game than trade - and nostalgia beats complexity when introducing scary new technology
• From Binance to NYSE: This cycle's institutional meta and why crypto gaming hasn't figured out Wall Street yet
• The new Renaissance: How fractional reserve banking created the actual Renaissance, and why crypto's lasting impact will be cultural, not financial
• Loyalty programs vs. helicopter money: Evolving from infinite money glitches to targeted behavioral incentives
• 70+ economic experiments: From AI-powered tanuki battles to on-chain "Runescape" - why only one or two need to work
• The cypherpunk optimism: Why crypto offers a more definite, grounded vision for the future than AI or robotics

Where to find...

Jeff 'Jiho' Zirlin:

• Instagram: https://www.instagram.com/axieinfinity
• X: https://x.com/Jihoz_Axie
• LinkedIn: https://www.linkedin.com/in/jeffzirlin
  
  

Skymavis:

• Website: https://skymavis.com
• Instagram: https://www.instagram.com/axieinfinity
• X: https://x.com/skymavishq
• LinkedIn: https://www.linkedin.com/company/skymavis

Axie 

• Website: https://axieinfinity.com/
• Instagram: https://www.instagram.com/axieinfinity
• X: https://x.com/AxieInfinity
• LinkedIn: https://www.linkedin.com/company/axieinfinity

Ronin

• Website: https://roninchain.com
• Instagram: https://www.instagram.com/axieinfinity
• X: https://x.com/ronin_network 
• LinkedIn: https://x.com/ronin_network

David Phillips:

• Website: www.fondo.com
• Instagram: https://www.instagram.com/axieinfinity
• X: https://x.com/davj
• LinkedIn: https://www.linkedin.com/in/davjphillips

In This Episode, We Cover

(00:00) From 300 to thousands of Users: The Binance Effect

(17:41) Community-Driven Growth: The Role of Guilds

(18:38) Experimentation as a Growth Strategy

(19:52) Challenges and Advantages in Crypto Growth

(20:03) Learning Through Gaming: Onboarding to Crypto

(21:27) The Uniswap Airdrop: A Catalyst for Growth

(22:18) Onboarding and Scaling in Crypto Gaming

(23:17) The Ronin Network: A Solution for Scalability

(24:40) The Evolution of Ronin and Its Community

(25:10) Expanding the Ronin Ecosystem: New Games and Innovations

(27:02) Economic Experiments in Crypto Gaming

(28:56) The Cultural Renaissance of Crypto

(30:14) Future Innovations in Web3 Gaming

(31:36) Optimism for the Future of Crypto

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