The script has been the same for decades: find a co-founder
Investors demanded it.
Accelerators screened for it.
The narrative became so entrenched that founders started pairing up out of obligation, not alignment.
Julian Weisser, founder of SOLO and ODF, has a name for this phenomenon: co-founders of convenience
And he's proving they're not just unnecessary-they're often the reason companies fail.
This week, Julian released 'The State of Solo Founding' report: "Today, solo founding is considered odd. Soon it will be the default. This report features exclusive Carta data alongside commentary from solo founders who have raised over $250M and the investors who backed them."
The comprehensive tracks solo founder rates across thousands of startups, the headline finding is historic: for the first time, over one-third of new startups are solo-founded (That's 36% in 2025, up from under 25% in 2019)
👉 Download the report here: https://solofounders.com/report
👉 Apply to the Solo Founders Program today. A three-month, in-person residency for 6 ambitious solo founders. Next cohort starts Jan. 23, 2026: solofounders.com/program
(00:44) Why the report matters now
(02:17) The data: 24% → 36%, first year over 1-in-3
(04:32) 3 forces: AI, visible wins, collapsing narrative
(06:00) Investor POV
(07:30) Org design insight: cutting the middle layer
(09:47) Download report: http://solofounders.com/report
(11:01) ODF26: half the cohort flipped to solo
(12:33) Inside SOLO
(14:30) Why coworking doesn't work for startups
(16:37) Outcomes: $1M ARR in 2 months & more
(17:19) Follow @solofounding & @joinodf
Where to find Julian Weisser:
X: https://x.com/julianweisser
LinkedIn: https://www.linkedin.com/in/julianweisser
Website: https://weisser.io
Where to find SOLO:
X: https://x.com/solofounding
LinkedIn: https://www.linkedin.com/company/solo-founders
Website: https://solofounders.com
Where to find ODF:
X: https://x.com/joinodf
LinkedIn: https://www.linkedin.com/company/solo-founders
Website: https://joinodf.com
Newsletters:
Texts with Founders: https://textswithfounders.com
Multitudes: https://multitudes.weisser.io
Where to find David Phillips:
X: https://x.com/davj
LinkedIn: linkedin.com/in/davjphillips
Brought to you by: Fondo — All-in-one accounting for startups @ fondo.com
Nate Matherson has spent 10+ years as a founder. He's built companies and even exited. After that first exit, he started angel investing in dozens of companies, then launched a fund.
Numeral was one of his early bets. He sent Numeral's CEO Sam an email. By the end of the day, he was working there as Head of Growth. Now he's helping scale the YC-backed sales tax platform serving over 2,000 customers.
Nate's seen what happens when founders don't think about sales tax. "They actually found out that they owed about a half million dollars in sales tax… the buyer subtracted that off what would have gone to the founders."
When Nate was a founder, he'd log into Stripe and that sales tax dashboard was lit up like a Christmas tree. Numeral does free nexus studies and monitoring — takes five minutes to set up, plugs into Stripe and Rippling, then runs itself.
They launched their SaaS product recently, and their whole concept is set it and forget it. They actually love it when customers don't log in. Some of Nate's new learnings? "When I was a founder, I was always pretty good at marketing. I was just marketing not-so-great products, which made marketing a lot harder." At Numeral, with the right product at the right time, everything clicked.
And he knows: great products make marketing easy. Timing makes it effortless.
Key Topics Covered
Follow Nate Matherson:
X: @NateMatherson
LinkedIn: linkedin.com/in/natematherson
Follow Numeral:
X: @numeral
YouTube: youtube.com/@numeraltax
Website: numeral.com
LinkedIn: linkedin.com/company/numeralhq
FollowDavid Phillips:
LinkedIn: https://www.linkedin.com/in/davjphillips
Brought to you by: Fondo — All-in-one accounting for startups: fondo.com
Jayden Clark didn’t abandon music. He re-scored it for distribution.
After music school, a hedge fund tour, and a B2B SaaS sprint, he launched MOTS—short, sharp episodes designed to be both of the moment and built to last a quarter.
His north star isn’t “go viral.” It’s “be clear.”
The insight is disarmingly pragmatic: structure is not the enemy of creativity—it’s the amplifier. Lists compress cognition.
A beginning–build–end gives every clip a runway and a landing.
When a five-replies-deep roast on X unexpectedly detonated, MOTS podcast already had the scaffolding to catch the surge. That’s the signature move: follow a consistent weekly cadence, then publish “emergency episodes” when the culture pops.
The result is a feed that feels alive without feeling random.
Key Topics Covered
Timestamps:
00:20) "neither timely nor timeless"
(00:51) Keeping the music alive
(02:10) SF Music → hedge fund → SaaS → pod
(03:20) Jazz improvisation: a content strategy
(03:42) Building blocks & two-five-one progressions
(04:35) How to make content easily digestible
(04:53) The @theo ratio backstory
(06:46) @sethsetse viral quote-tweet
(07:17) Emergency pods vs. weekly episodes
(07:22) Emergency Pod #1: @bchesky's bench press
(09:42) Where to find @mots_pod
Where to find Jayden Clark:
X: @creatine_cycle
LinkedIn: linkedin.com/in/jayden-clark-75991a1aa
Where to find MOTS Podcast:
X: @mots_pod
YouTube: @motspod
LinkedIn: linkedin.com/company/mots-pod
Where to find Atlas Media Labs:
Website: atlasmedialabs.com
Where to find David Phillips:
LinkedIn: https://www.linkedin.com/in/davjphillips
Brought to you by: Fondo — All-in-one accounting for startups: fondo.com
Sky Yang (CEO) & Neo Lee (CTO) are Co-founders of Imagine AI, an AI-powered content engine that clones B2B founders—replicating their voice, context, and backstory to create scalable personal brands. Before Imagine AI, Sky was elected student body president at UCSD by 32,000 students at age 19, then secured $150 million in state funding for university housing through coalition-building and advocacy in DC, Sacramento and at the UC Board of Regents. He co-founded "Break the Outbreak," a nonprofit that delivered PPE across 18 states and 53 cities during COVID, earning commendations from Senator Dianne Feinstein and Congressman Eric Swalwell. Neo transferred from UCSD to Berkeley, then dropped out to build. He met Sky freshman year at a beach event—asking "Are you Skygodkingdom?"—before they went skydiving together and Neo cut Sky's hair in the woods after COVID.
Their catalyst was realizing founders were building in public on X but deals were happening on LinkedIn. After meeting advisor Gustaf, they pivoted distribution strategy to focus on where B2B founders actually live and transact. Sky calls this "content-market fit"—a state where your content hits your target customer every single time, creating scalable, repeatable inbound motion. They were fully booked from their first week post-YC launch, landing Series B customers. One founder messaged urgently, jumped on a 15-minute call, and paid on Stripe immediately. They recruited over Halloween weekend instead of partying. They hosted a yacht party with $10 billion in collective GDP (320 capacity, 750+ on waitlist). Neo's philosophy: "The product is just amplifying what we already are. Just be authentic." Sky's vision references Westworld: "Your agents will interact with each other instead of humans."
Key Topics Covered:
· What Imagine AI is: a chat-first AI clone with high-fidelity persona creation, subject matter expert interviews, and content engineering to hit content-market fit
· From X to LinkedIn: pivoting distribution to where B2B deals actually happen; Gustaf's advice on market selection
· Sky's origin arc: Chengdu → LA → Bay Area → UCSD student body president → $150M state funding advocacy → Break the Outbreak nonprofit
· Neo's journey: UCSD → Berkeley dropout → "Skygodkingdom" beach encounter → haircut in the woods → building startups pre-Imagine AI
· Content-market fit framework: when your content hits your customer every single time—scalable, repeatable motion with high-intent top-of-funnel inbound
· Week-one hypergrowth: fully booked post-YC launch, Series B customers, 15-minute Stripe close during conference, recruiting over Halloween
· Authenticity over algorithm: amplification not fabrication; the product shapes around you, not the other way around
· Building clones that replicate voice, context, backstory, heuristics, and cognition
· The $10B GDPyacht party: 320 founders, 3 DJs, 750 waitlist—building community as cultural moment
· The 'Westworld' thesis: AI agents interacting on your behalf
· Building in public as 2025 narrative: why founders do great work but nobody knows; solving discovery through personal brand at scale
· Design philosophy: one infinite content motion thread vs. scattered posts; AI handles artifacts, humans make strategic decisions
Chapters:
01:21 - The origin story: "Are you Skygodkingdom?"
02:00 - Neo cuts Sky's hair in the woods
02:36 - Sky's journey: Youngest student body president at UCSD
04:20 - Securing $150M in state funding for student housing
06:28 - The nonprofit during COVID
06:40 - How Imagine AI started: solving their own problem
07:15 - Launching on YC and getting booked solid
08:00 - Using their own product for personal branding
09:08 - What is "content-market fit"?
10:08 - The future: AI clones
11:09 - The $10 billion GDP yacht party in SF
12:11 - Where to find Sky, Neo, and Imagine AI
Where to find Sky Yang:
LinkedIn: https://www.linkedin.com/in/skyyang
X: https://x.com/skygodkingdom
Where to find Neo Lee:
LinkedIn: https://www.linkedin.com/in/neo-lky
Where to find Imagine AI:
Website: https://www.imagineai.me
LinkedIn: https://www.linkedin.com/company/ai-imagine
Where to find David Phillips:
LinkedIn: https://www.linkedin.com/in/davjphillips
Brought to you by:Fondo — All-in-one accounting for startups: fondo.com
Rebecca Medina and Jeff Phillips built an AI-powered talent marketplace that's disrupting recruitment with transparent pricing, direct negotiation, and same-day PM hires for SMBs.
Rebecca Medina had the network. She had decades of Big Tech experience. She had the credibility. But when she needed project management help on a client engagement as an independent consultant, none of it mattered.
"Even with my network of project managers, I couldn't find the right person fast enough," Rebecca recalls. "And it created a big problem for the company because we weren't able to scale as quickly as we wanted."
That pain point became Talent Cheetah.
Five years later, Rebecca and her co-founder Jeff Phillips have built an AI-powered talent marketplace connecting pre-vetted project managers with SMBs. They've scaled to 300 PMs across 34 US states. They've even partnered with the Project Management Institute. But the metric that matters most: the Bureau of Labor Statistics says it takes 90 days to hire a technical project manager. Talent Cheetah does it in minutes—with same-day hiring possible.
In this episode, Medina and Phillips break down the recruitment model that turns recruiting on its head: transparent pricing that exposes hidden markups, lower take rates than traditional agencies, direct PM-to-company negotiation, and real-time hiring through AI matching.
Their core unlocks: many traditional staffing firms charge companies a significantly higher rate than what PMs actually earn—often without disclosing the difference to either side; cultural fit matters just as much as credentials (project management exists on a broad spectrum — the skills needed vary widely across industries, company sizes, and stages of growth.); and past execution remains the strongest predictor of future performance. Their 25-point vetting process includes one pivotal test: candidates must be able to produce legitimate professional references—if you can't find even one after years in the field, you're not ready for the platform.
In this conversation, they reveal just how much AI is automating routine PM artifacts (like meeting notes, risk logs, and timelines) while increasing the premium on leadership and communication; how their intentional U.S.-based strategy competes on quality and transparency in an industry racing to the bottom on cost; and how Talent Cheetah is opening doors for underrepresented groups in project management; why fractional engagements (such as part-time PM support for short durations) are suddenly viable when traditional agencies can't deliver them well.
Key Topics Covered
The pain point origin: Rebecca's consulting crisis when her network couldn't deliver PM talent fast enough
The 90-day problem: Bureau of Labor Statistics average vs. Talent Cheetah's minutes-to-same-day matching
Exposing the hidden markup: traditional agencies bill $x/hour, pay PMs $x/hour, keep $x secret from both parties
No posting fees: free to post unlimited jobs (vs. ZipRecruiter/Indeed/LinkedIn pay-per-post), no sign-up fees for PMs
The 25-point vetting process: professional references, credential validation, and candidates who wait years
The reference test: some applicants can't find anyone to vouch for them after 12-24 months
Four-year minimum: experience requirement (not just title) focused on herding cats and managing projects
US-based strategy: competing on quality, transparency, and credential familiarity instead of global price competition
PMP vs. experience: why certification proves framework knowledge but not execution capability
Direct negotiation: PMs and companies set rates transparently, eliminating hidden recruiter markups
AI-powered matching: real-time algorithm surfaces top 3 PMs, with 297 more to browse
Cultural fit dynamics: startup PMs vs. Big Tech PMs require different personalities
Expanding beyond PMs: network architects, developers, product managers using same vetting framework
PMI partnership: hiring bonanzas and visibility programs in San Francisco
White glove service: helping first-time contractors negotiate rates and structure engagements
AI's impact on PMing: automating artifacts while amplifying leadership and communication needs
Fractional engagements: 10-hour/week arrangements that traditional agencies can't serve
Transparent pricing model: complete visibility vs. hidden markups, lower take rates than Robert Half/Adecco/Tech Systems
Chapters:
(01:55) Origin story: Talent Cheetah
(03:16) What makes Talent Cheetah different: Speed as the #1 differentiator, same-day hiring possible
(04:05) US-based strategy: competing on quality and credential familiarity
(06:08) Supporting underrepresented groups: veterans (logistics → PM transitions) and women in tech
(07:33) Serving both sides: job search help for PMs, FAANG-quality talent for clients
(08:43) White glove service: flexible involvement based on needs, negotiation help included
(09:16) How it works: 30-second account creation, under-5-minute posting, real-time AI matching
(10:15) Platform scale: 300 PMs across 34 US states, discipline-specific but industry-agnostic
(11:04) The 25-point vetting process: four-year minimum, references, credentials, interviews
(14:09) PMP certification vs. hands-on experience: gold standard plus practical execution
(16:02) Exposing the hidden markup: how traditional agencies work
(17:08) AI's impact on PM work: automating artifacts, amplifying leadership and communication
(20:40) Expanding beyond PMs: network architects, developers, product managers
(23:02) PMI partnership: 'hiring bonanzas' and visibility programs in SF
(25:12) Ideal clients
(26:47) Transparent pricing model: no posting fees for companies, no sign-up fees for PMs
(27:36) Getting started: talentcheetah.com, instant talent matching
(30:48) Internal messaging and AI matching: top 3 matches with direct communication
(32:00) Where to find them on LinkedIn, YouTube, talentcheetah.com
Where to Find
Rebecca Medina:
LinkedIn: https://www.linkedin.com/in/rebeccarm
Website: https://www.talentcheetah.com
Jeff Phillips:
LinkedIn: https://www.linkedin.com/in/jeffreyjphillipspmp
Website: https://www.talentcheetah.com
Talent Cheetah:
X: https://x.com/talentcheetah
LinkedIn: ht...
Julian Weisser is the Founder and CEO of Solo Founders, a three-month residency program in San Francisco where founders live and work together while maintaining full authorship of their companies. He's also the CEO of On Deck Founders (ODF), a program that over seven years and 26 cohorts has helped over 1,000 people start companies that have collectively raised more than $2 billion.
As an angel investor with more than 150 portfolio companies including Levels, Astroforge, and MagicSchool, he's seen patterns in what actually predicts startup success versus what investors claim they're looking for. He writes the Texts with Founders newsletter sharing bite-sized practical wisdom for entrepreneurs and publishes Multitudes, a newsletter exploring founder psychology and startup strategy.
In this episode, Weisser breaks down the denominator delusion: solo-founded companies were more likely to succeed than co-founded ones, but nobody talked about it because when you look at the total number of successful companies, co-founded businesses eclipse solo successes—while hiding how many unsuccessful co-founded companies exist in the denominator.
His core unlocks: two-thirds of startups die from co-founder disputes before reaching product-market fit or running out of money, being solo is far better than 99% of potential co-founders, and authorship (the desire to express yourself and put your vision into the world) matters more than contortionism (twisting your company to match what investors want to see).
The flippening already happened in ODF 26—over half chose solo. In this conversation, he breaks down why MagicSchool's Adil Khan (a former high school principal with no startup experience) succeeded solo, how "co-founders of convenience" kill companies before they reach potential, what makes the Solo Founders residency feel like having "five co-founders while building your own company," and why mimicking trends accrues value to memes instead of founders.
Key Topics Covered:
Chapters:
Where to find Julian Weisser:
X: https://x.com/julianweisser
LinkedIn: https://www.linkedin.com/in/julianweisser
Website: https://weisser.io
Where to find SOLO:
X: https://x.com/solofounding
LinkedIn: https://www.linkedin.com/company/solo-founders
Website: https://solofounders.com
Where to find ODF:
X: https://x.com/joinodf
LinkedIn: https://www.linkedin.com/company/'odf'
Website: https://joinodf.com
Newsletters:
Texts with Founders: https://textswithfounders.com
Newsletter (Multitudes): https://multitudes.weisser.io
Where to find David Phillips:
X: https://x.com/davj
LinkedIn: linkedin.com/in/davjphillips
Brought to you by:
Fondo — All-in-one accounting for startups: fondo.com
Allen Naliath is the Founder and CEO of Friday, a Chrome extension that integrates AI email management directly into Gmail. Two years ago at Stanford, he struggled with the confidence to ask for what he wanted. So he engineered a solution: a 30-day rejection challenge where he had to hear "no" once per day or start to ask for increasingly audacious requests. The problem: people kept saying yes. He escalated strategically—waiting by a golf cart to ask Sam Altman to sign his laptop, and cold-asking Garry Tan to add him on LinkedIn during a Stanford talk. Garry's response: "Is this a Psyop?" He added him anyway. That connection led to YC. Today, Friday processes emails via predicted action buttons—users press enter repeatedly to archive, reply, or unsubscribe. Allen personally onboards every user to inbox zero in 10 minutes, even with 18,000 unread emails.
Naliath's catalyst was advice from a founder mentor: "If you want to work on startups when you graduate, don't even apply to Apple and Google. If you have no plan B, plan A has to work." His core insight: most people's win condition depends on the other person saying yes. He reframed it so yes and no are both wins—the win condition is in his control just by asking. That philosophy runs through Friday's design: it doesn't put email on full autopilot (which "induces anxiety"), it gets users 99% of the way. Friday started as a hackathon project, evolved into a mobile text assistant, then became a Chrome extension after realizing Gmail integration was faster than building feature parity. The average person spends two hours per day in email; Friday users get through 30 emails in 60 seconds.
Key Topics Covered:
- Rejection challenge: daily "no" requirement, mindset shift from fear to relief
- Win condition reframe: "Yes and no are both wins. The win condition is in my control just by asking."
- Cold approaches: Sam Altman golf cart ambush, Garry Tan LinkedIn add during Stanford talk
- Friday evolution: hackathon project → mobile assistant → Gmail Chrome extension
- Anti-autopilot philosophy: "That induces anxiety. It gets you to 99%—you stay in control."
- Predicted action buttons: archive, reply, unsubscribe—all one-keystroke approvals
- Voice matching: Friday drafts replies that sound like you, including dash preference
- 10-minute inbox zero: personal onboarding using auto-archive rules for old emails
- Chat feature: "Look him up online, find his email in my inbox, draft an intro."
Chapters:
(00:33) The rejection challenge that rewired his confidence
(02:08) Sam Altman signed his laptop
(03:35) Changing you win-condition to be in your control
(04:25) Asking for things that are "hard to get"
(05:20) Meeting Silicon Valley Legends
(06:05) "Is this a Psyop?" - how a cold LinkedIn ask to Garry Tan led to YC
(07:03) Dropping out of Stanford: "If you have no plan B, plan A has to work."
(09:23) Friday DEMO: how enter-enter-enter clears 30 emails in 60 seconds
(13:45) The inbox zero system: snooze what matters, archive the rest, empty daily
(15:13) Why Friday stops at 99%: "Full autopilot induces anxiety—you need control."
(17:36) Chat-powered bulk actions: "Look him up online, find his email, draft an intro."
(19:21) Make every day feel like Friday
Where to find Allen Naliath:
X: https://x.com/AllenNaliath
LinkedIn: https://www.linkedin.com/in/allennaliath
Where to find Friday:
Company X: https://x.com/fridaymail
Company Website: https://www.friday.so
Company LinkedIn: https://www.linkedin.com/company/fridaymail
Where to find David Phillips:
X: https://x.com/davj
LinkedIn: linkedin.com/in/davjphillips
Brought to you by:
Fondo — All-in-one accounting for startups: fondo.com
Lindsay Amos is the Founder of Amos Communications, a boutique firm for founder-led marketing and PR. From 2018 to 2024, she ran communications at Y Combinator, where she coached thousands of startups and wrote YC's handbook on startup PR. Before that, she worked in comms at Square and Meta, giving her a 360° view of how stories move from boardrooms to bylines to buyer behavior. Today, she advises founders on landing real news (not ads), building durable founder brands, and operating across a media landscape that's shifted from legacy gatekeepers to creator-led growth channels. She also co-created The To-Do List Summit, a workshop bootcamp teaching early-stage teams the tactical basics of comms, video, events, and community, and she writes a Substack on startup storytelling and strategy.
Amos's catalyst was living both media eras: nine months shepherding a single Wired story about Square moving into a new office versus today's "algorithms plus authenticity" environment. Her core unlocks: lead with the what (then earn the why), tie every pitch to a macro trend your audience already cares about, and default to exclusives over embargoes until you're big enough to run a press gauntlet. New media isn't a replacement for traditional outlets; the best founders run both lanes—because audiences follow people first, products second. In this conversation, she breaks down how to pick the right channel, prep for tough interviews, avoid blacklist behaviors, and time transparency (share the "personal hell" after you've won, to teach—not spiral).
Key Topics Covered:
- What "news" actually is: a hook plus a macro trend your customer already thinks about.
- Founder brand vs. company brand: why audiences follow people first (and how to use it).
- Exclusive > embargo (early): how editors green-light stories and why timing matters.
- Practical media ops: avoid Friday pitches, follow up once, don't text or Signal reporters.
- Content that converts: entertaining, educational, or perspective—never just ads.
- Cinematic launches: when video helps, when it's sizzle; why distribution still wins.
- New media shift: reporters → Substack/podcasts; find where your audience actually is.
- The To-Do List Summit: teaching founder-led marketing when agencies aren't the answer.
Chapters:
Where to find Lindsay Amos:
X: https://x.com/lindsayaamos
LinkedIn: https://www.linkedin.com/in/lindsayamos, https://www.linkedin.com/company/amoscomms
Website: https://www.amoscomms.com
Substack: https://lindsayamos.substack.com
To-Do List Summit: https://x.com/todolistsummit
Where to find David Phillips:
X: https://x.com/davj
LinkedIn: linkedin.com/in/davjphillips
Brought to you by:
Fondo — All-in-one accounting for startups: fondo.com
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:
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
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
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:
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.
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.
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
Where to find Daivik Goel:
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
Where to find Shor:
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
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.
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
Where to find David Phillips:
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:
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
Where to find David Phillips:
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.
Key Topics Covered:
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
Where to find David Phillips:
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:
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:
Linkedin: https://www.linkedin.com/in/collin-wallace/
Website: https://lobby.vc/people/collin-wallace/
Where to find Lobby Capital:
Linkedin: https://www.linkedin.com/company/lobby-capital/
X: https://x.com/lobby_vc
Website: https://lobby.vc/
Where to find David Phillips:
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.
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.
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
Where to Find Alessandro Chesser:
LinkedIn: https://www.linkedin.com/in/alessandro-chesser-84763748
Where to Find Dynasty:
Website: https://www.getdynasty.com
LinkedIn: https://linkedin.com/company/getdynasty
X: https://x.com/getdynasty_com
Where to Find David Phillips:
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:
Where to find...
Jeff 'Jiho' Zirlin:
Skymavis:
Axie
Ronin
David Phillips:
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
Brought to you by:
Fondo — All-in-one accounting for startups: https://tryfondo.com
Parthi Loganathan is the founder and CEO of Letterdrop, a Y Combinator-backed startup that helps B2B companies build pipeline by focusing on the warmest leads and people who are actually in market. Since launching Letterdrop, he's helped companies move beyond saturated email and cold calling tactics to identify prospects who want to talk and send them highly tailored messaging. The platform analyzes public conversations, CRM data, and sales calls to segment buyers and enable personalized outreach without relying on high-volume approaches.
In this episode, we explore the fundamental shift happening in B2B sales as traditional cold outbound becomes less effective and companies invest in higher-effort tactics to stand out. The conversation covers the evolution from Letterdrop's origins as an SEO tool to its current focus on conversation intelligence, driven by market changes from ChatGPT's emergence. Parthi shares insights about the three essential components of effective outbound messaging, why customer conversations represent untapped content goldmines, and his firsthand experience being demoed by an AI sales agent. We also examine his predictions about AGI's timeline and the philosophical question facing all founders: do you build for today's market or tomorrow's technological reality?
Key topics covered:
Where to find Parthi Loganathan:
Linkedin: https://www.linkedin.com/in/parthiloganathan/
Where to find Letterdrop:
Website: https://letterdrop.com/
Linkedin: https://www.linkedin.com/company/letterdrop/
Podcast: https://open.spotify.com/show/43bSCi3FcFaJ28H7qEK59X?si=2f6afe15cea342ea
Where to Find David Phillips:
LinkedIn: https://www.linkedin.com/in/davjphillips/
In This Episode, We Cover
(00:00) Introduction to LetterDrop and Its Mission
(02:52) The Evolution of Outbound Sales Strategies
(06:11) Crafting Effective Outbound Messages
(09:09) Parthi's Journey as a Founder
(12:02) Leveraging Social Conversations for Sales
(14:59) Creating Content from Customer Conversations
(17:55) Back Office Operations for Startups
(20:49) The Role of AI in Sales
(23:38) The Future of Work: AGI and UBI
(26:46) Closing Thoughts and Future Questions
Brought to you by:
Fondo — All-in-one accounting for startups: https://tryfondo.com
In this episode, I sat down with John Paul Mussalli, the co-founder and COO of CareSwift, a Y Combinator-backed startup building AI-powered software to streamline documentation for EMT workers.
JP and his cofounders brings a unique blend of technical expertise and entrepreneurial drive to the healthcare technology space, having previously worked across diverse fields from real estate automation to web development.
Since co-founding CareSwift, he's helped scale the platform to serve over 2,000 EMTs in New York City alone, generating more than 90,000 automated reports. Beyond product development, JP leads go-to-market strategy and is currently pursuing EMT certification himself to deepen his understanding of the industry's challenges.
In this episode, we explore the journey from scrappy prototype to venture-backed startup and the critical lessons learned along the way.
Key topics covered:
Where to find John Paul Mussalli
- Linkedin: https://www.linkedin.com/in/jpmussalli/
- X: https://x.com/jpm1126
Where to find CareSwift:
- Website: https://careswift.ai/
- Linkedin: https://www.linkedin.com/company/careswift/
Where to Find David Phillips:
- X: https://x.com/davj
- LinkedIn: https://www.linkedin.com/in/davjphillips/
In This Episode, We Cover
(00:00) Introduction to CareSwift and Its Founders
(02:54) The Birth of CareSwift: Addressing EMT Challenges
(06:09) Impact of CareSwift on EMT Efficiency
(09:01) Navigating the Startup Journey: Lessons Learned
(09:35) Navigating Startup Structures and Legalities
(12:14) The Journey Through Y Combinator
(15:06) Daily Life as a Founder in Y Combinator
(17:13) Building a Founder Stack: Tools and Resources
(18:57) Future Plans
Brought to you by:
Fondo — All-in-one accounting for startups: https://tryfondo.com