Founders in Arms

What does it take to build a company in a category where everyone says the idea is dead? In this special live recording from Mercury's San Francisco office, Immad Akhund and Raj Suri sit down with Max Mullen, co-founder and former Chief Product Officer at Instacart, for an honest conversation about the founder journey.

Max shares how Instacart started in 2012 when there was no gig economy, no Uber X, and investors repeatedly told them grocery delivery was a dead idea after Webvan's failure. The conversation explores the controversial early days of building Instacart, why Max believes founder pain tolerance is the biggest moat, and the critical importance of market timing even when you're executing well.

Max opens up about the challenges of being a technical co-founder without deep technical skills, navigating co-founder dynamics, and the reality that many startup outcomes are heavily influenced by timing and luck. The discussion shifts to AI's transformative potential, with Max offering a compelling framework: software engineers are experiencing "the tip of the spear" of AI capabilities today, and this same 10x productivity leap will soon apply to lawyers, doctors, accountants, and every other profession.

He explores what AI-native companies will look like and why the next wave of startups will be built around professionals orchestrating fleets of agents. This episode offers essential insights for founders building in challenging markets, navigating co-founder relationships, timing market opportunities, and understanding where AI is creating the biggest opportunities for new companies.

SaaS companies are down dramatically—Figma is 77% off its peak. In this candid conversation, Immad Akhund (CEO of Mercury) and Raj Suri (co-founder of Lima and Tribe) unpack what's really happening in tech as we head into 2026.

They explore why the SaaS business model is under attack (hint: it's not just AI building software faster), the shift from per-seat pricing to API-driven usage, and why enterprises actually buy SaaS products—spoiler, it's not about the software. The conversation reveals how startups can now stay lean with fewer employees for much longer, with companies like OpenAI reaching $500B valuations with just 4,000 people.

Immad and Raj also dive into their personal experiences with AI agents, discussing what actually works versus the hype, why they're skeptical of consumer AI hardware, and how AI is changing daily productivity for founders. They debate Google's quiet win with the Apple-Gemini deal, why Siri is dead, and whether one AI model controlling all handsets should concern us.

The episode wraps with practical advice on what makes a compelling VC pitch in 2026, why crazy promises still work (even when timelines are wildly optimistic), and how to think about your startup's valuation as a call option rather than current worth. From Elon's humanoid robot bet to the new growth expectations (0 to $5M in 12 months), this conversation offers an honest founder-to-founder take on navigating the current landscape.

Key Topics:

1. Why SaaS companies are struggling and what survives
2. The real reason enterprises buy software (risk offloading, not features)
3. AI agents in practice: what works, what doesn't
4. Google's strategic win with Apple's Gemini integration
5. How to pitch VCs when expectations are 5x higher than before
6. Why crazy promises and long timelines still attract capital
7. The shift to leaner startups and API-first business models

Mehul Nariyawala is the co-founder and President of Matic Robotics, a home robotics company building what he calls “robotics 2.0” — intelligent, vision-first robots designed to actually work in real homes. After early careers at Nest and a prior acquisition by Google, Mehul and his team spent seven years building Matic, challenging the assumptions behind robot vacuums, consumer hardware, and how robotics companies should scale.

In this conversation, Mehul breaks down why robotics is far harder than software, why most home robots quietly fail, and how Matic approached everything differently — from vision-only robotics and in-house manufacturing to avoiding subscriptions, ads, and premature market creation.

What you’ll learn:

• Why robotics is “100× harder than software” — and where most teams underestimate the work
• The difference between automation and true intelligence in home robots
• Why negative-NPS categories can hide massive opportunities
• How Matic beat entrenched incumbents like Roomba by fixing fundamentals, not adding features
• Why vision-only robotics was a risky but necessary bet
• The real reason humanoid robots are still far from consumer-ready
• Lessons from Nest on why some hardware categories stay defensible for decades
• Why creating a new market can be fatal for hardware startups
• How Matic built robots in-house in California instead of outsourcing manufacturing
• The tradeoffs between subscriptions, ownership, and consumer trust
• Why great hardware products must earn word-of-mouth before growth

In this episode, we cover:

(00:00) Introduction to Mehul Naryawala and Matic Robotics

(01:10) Why robotics is dramatically harder than software

(03:00) The failure modes of early robot vacuums

(05:10) Identifying opportunity in negative-NPS markets

(07:45) Automation vs. intelligence in consumer robotics

(10:15) Why vision-only robotics was a foundational bet

(14:00) Lessons from Nest on defensible hardware categories

(17:30) Why Matic avoided creating a new market

(20:45) In-house manufacturing and vertical integration

(24:30) Scaling hardware without inventory risk

(28:10) The long road from demo to product

(32:00) Why humanoid robots are still overhyped

(36:20) Word-of-mouth, product-led growth, and brand trust

(40:15) Subscription fatigue and consumer psychology

(44:30) The future of home robotics and where Matic goes next

Jack Zhang is the co-founder and CEO of Airwallex, a global payments and financial platform valued at $5.5 billion. Founded in Melbourne, Airwallex processes billions in cross-border transactions and serves businesses expanding internationally. Jack shares his journey from starting the company to competing with giants like Stripe, navigating the complexities of global payments infrastructure, and building across multiple regulated markets.

What you'll learn:

1. Why cross-border payments remain broken despite decades of fintech innovation
2. How Airwallex competes against Stripe and other established payment platforms
3. The challenge of building financial infrastructure across multiple countries and regulations
4. Jack's perspective on fair competition versus FUD (fear, uncertainty, doubt) tactics in business
5. Why Airwallex is deploying $1 billion in the US market over the next three years
6. The reality of being a foreign founder building in America during geopolitical tensions
7. How payment infrastructure for global businesses differs from consumer fintech
8. The trade-offs between growth velocity and sustainable business building
9. Jack's philosophy on money, success, and what matters after achieving wealth at 30
10. Why he chose to stay in Melbourne instead of relocating to San Francisco

In this episode, we cover:

(00:00) Introduction to Jack Zhang and Airwallex

(02:34) Early days of Airwallex and the founding story

(05:12) The problem with cross-border payments

(08:45) Competing with Stripe and other payment platforms

(12:18) Building in regulated markets and compliance challenges

(16:23) FUD (fear, uncertainty, doubt) tactics in business competition

(19:13) Raj's experience with FUD at Lyft vs Uber

(22:47) Navigating geopolitical tensions as a Chinese-Australian founder

(25:36) The $1 billion US market investment commitment

(27:41) Product philosophy and fair competition

(31:15) Going upmarket vs staying with SMBs

(35:22) Life choices: Melbourne vs San Francisco

(37:49) Perspective on wealth - "not about the money"

(42:18) The future of payments infrastructure

(45:30) Advice for founders building in competitive markets

Ryan Gariepy is the co-founder and former CTO of Clearpath Robotics and Otto Motors, acquired by Rockwell Automation for $600M+ in 2023. He bootstrapped the company for five years with only $300K in funding, reached profitability in 18 months, and spent 14 years building mobile robotics platforms that became the industry standard for research and industrial automation.

(If you’re looking for inspiration and lessons from other founders, Founders in Arms is hosting a founders roundtable with Rajat Suri, Immad Akhund, and Max Mullen next Wed Jan 14th at Mercury HQ. Discussing war stories and sharing lessons with a group of founders, as part of Founders-in-Arms podcast. Will be food and drinks. Capacity strictly limited at 50 so apply early if you’re interested: https://luma.com/dk97inyk )

What you'll learn:

1. Why robotics is a systems discipline where progress stacks rather than explodes
2. How to bootstrap a hardware company to $10M revenue before raising venture capital
3. Why robotics follows 20-50% sustained growth for decades vs. software's boom-bust cycles
4. The "promise problem" with humanoid robots and why form factor shapes user expectations
5. How manufacturing in Canada (not China) became a strategic advantage for Clearpath
6. Why founders overestimate 2-year progress but underestimate 10-year impact in robotics
7. The real economics of humanoid robots: $20K cost becomes $80K landed price
8. How robotics investment differs from software: less competitive, more defensible
9. Why experience compounds in hardware but expires in software careers
10. Investment criteria for robotics: engineering risk vs. technical risk and go-to-market strategy

In this episode, we cover:

(00:00) Introduction and live event announcement

(03:29) Ryan's background: Clearpath Robotics and Otto Motors

(04:06) Building two brands under one company

(06:29) The 14-year journey: challenges and non-linear growth

(07:11) Bootstrapping robotics when "nobody thought you could make money"

(08:17) Reaching profitability in 18 months with research customers

(10:28) Building robotics platforms for MIT, universities, and research labs

(11:03) Manufacturing in Canada vs. outsourcing to Asia

(15:05) Reconnecting after 20 years: the Waterloo entrepreneurship connection

(16:17) Working at Kiva Systems (now Amazon Robotics)

(18:10) Why robotics is more exciting now than ever in history

(19:21) Robotics as systems discipline: no single breakthrough technology

(21:22) The overhype cycle and realistic expectations

(22:14) Software explodes then crashes; robotics compounds for decades

(23:36) Why hardware is harder but more mission-driven

(25:27) The talent pool advantage: people irrationally love hardware

(27:30) Physical AI and real-world impact beyond software optimization

(28:07) Humanoid robots: incredible tech, miscalibrated expectations

(32:41) The "promise problem": form factors make promises to users

(34:35) Consumer robotics examples: Matic cleaning robot

(35:59) Asia leading in restaurant and airport robotics deployment

(38:37) Training challenges and precursor technologies needed

(39:20) China's role in robotics and humanoid development

(41:08) Venture capital structures forcing "ridiculous things" in robotics

(42:36) Robotics for entertainment vs. utility as consumer use case

(43:52) Imad's robotics investments: Embark, Gecko Robotics, vertical AVs

(45:23) Why robotics is less competitive than software

(47:21) Operational design domain and technology risk assessment

(48:19) The AV journey: Waymo, Zoox, and the importance of experience

(49:39) Experience compounds in hardware, expires in software

(50:31) Rapid fire: biggest mistake, following gut over charisma

(51:47) Founder inspiration: Rodney Brooks

(52:20) Uncomfortable feedback at Honda co-op job

(53:17) Investment criteria: engineering risk, go-to-market, team understanding

Emmett Shear is the founder and CEO of Softmax, an alignment research company, and previously co-founded and led Twitch as CEO. He was also a Y Combinator partner and briefly served as interim CEO of OpenAI.

What you'll learn:

1. Why AI alignment and AGI are fundamentally the same problem
2. How theory of mind is the critical missing piece in current AI systems
3. Why continuous learning requires self-modeling capabilities
4. The dangerous truth: alignment is a capacity for both great good and great evil
5. Why "aligned AI" really means "aligned to me"—and why that's concerning
6. How societies of smaller AIs will outcompete singleton superintelligences
7. Why AI needs to be integrated with humans, not segregated into AI-only societies
8. The Twitch lesson: people don't want easy, they want good
9. Why 99% of AI startups are building labor-saving tools instead of value-creating products
10. How parenting and AI development mirror each other in surprising ways
11. Why current AI labs are confused about continuous learning
12. Conway's Law applied to AI: you ship your org chart
13. The problem with mode collapse in self-learning systems
14. Why emotions are training signals, not irrational noise
15. Emmett's biggest mistake at Twitch: chasing new products instead of perfecting the core

In this episode, we cover:

(00:00) The dangerous truth about AI alignment

(01:13) Introduction to Softmax and organic alignment

(02:05) What alignment actually means (and why most people are confused)

(03:33) The output: training environments for theory of mind

(05:01) Continuous learning and why it's so hard

(06:25) Multiplayer reasoning training in open-ended environments

(07:14) Aligned to what? The critical question everyone ignores

(08:40) Why alignment is always relative to the aligning being

(11:07) Cooperation vs. competition: training for the real world

(12:56) Is AGI an urgent problem or do we have time?

(13:15) AGI and alignment are the same problem

(15:25) Alignment capacity enables both good and evil

(17:13) The singleton problem and why societies of AIs make sense

(20:41) Building alignment between AIs and humans

(22:09) Why Elon's "biggest cluster" strategy might be wrong

(23:06) AI must be aligned to individual humans, not humanity

(25:03) What does the atomic unit of AI look like?

(28:02) Adding a new kind of person to society

(29:06) Everything will be alive: from spreadsheets to cars

(30:00) From Twitch retirement to Softmax founding

(31:26) Research vs. product engineering at early-stage startups

(32:41) Raising money for AI research in the current era

(34:30) Why Softmax will ship products

(34:50) Ilya's closed-loop research vs. open-loop learning

(36:36) How you do anything is how you do everything

(37:28) The continuous learning problem explained simply

(38:29) Mode collapse: why AIs become stereotypes of themselves

(39:33) The reward problem and why humans need emotions

(40:48) Why LLMs are trained to avoid emotions

(41:52) Watching children learn while building learning AI

(43:04) Advice for first-time AI founders

(45:08) Treat AI as clay to be molded, not a genie granting wishes

(45:50) The Twitch lesson: people want good things, not easy things

(47:22) Why 99% of AI companies are building the wrong thing

(48:16) Rapid fire: biggest career mistake at Twitch

(50:15) Which founders inspire Emmett most

(50:56) The passing fad: AI slop generators

Immad Akhund and Raj Suri reunite for a one-on-one conversation covering the biggest tech shifts of 2025, from Mercury's public launch of Personal Banking to the quieting of AGI doom discussions. This wide-ranging episode explores why self-driving cars may matter more than AGI, how vibe coding is changing software development, and the strategic decisions founders make when everyone else disagrees.

What you'll learn:

Why Immad launched Mercury Personal despite investor and team skepticism—and the founder lesson about following conviction

How Mercury Personal brings business-grade financial controls to personal banking (collaboration features, automatic categorization, 3.5% savings rates)

The existential threat facing OpenAI and Anthropic as AI models commoditize and Google leverages distribution advantages

Raj's vibe coding experiment: Building a full-stack app with Postgres backend using just prompts (and why Replit won)

Why Tribe is rejecting the $30/user ad model to build a premium, ad-free group chat platform

The retention metrics showing Tribe's product-market fit (20-40% six-month retention with minimal marketing)

How AI hype shifted from AGI doom conversations to practical commercial applications in 2025

Why self-driving technology (Waymo, Tesla FSD) represents a more immediate transformation than AGI

The best and worst of 2025: renewed tech energy vs. immigration scapegoating and Doge's failure to deliver government efficiency

Why supply constraints (chips, power) signal AI demand is real, not a bubble

In this episode, we cover:

(00:00) AGI conversations cooling down in 2025

(01:50) Mercury Personal launch after year-long waitlist

(02:42) Business-grade controls for personal banking

(04:30) 3.5% savings rates and Treasury/Invest products

(06:15) Following founder conviction despite opposition

(07:33) Balancing product shipping with polish

(08:26) OpenAI's Code Red and focus strategy

(09:23) Google's distribution advantage vs. OpenAI

(10:33) The API commoditization threat to Anthropic

(12:34) Why ad economics dominate the internet

(14:58) Facebook's $30/user vs. subscription models

(17:22) Tribe's progress: retention, AI features, monetization plans

(21:42) Vibe coding experiment: Replit vs. Lovable vs. Wix

(26:31) Why Replit might own the vibe coding market

(28:05) Enterprise use cases for AI-generated apps

(33:26) 2025's best: renewed tech energy and deregulation

(34:51) 2025's worst: immigration scapegoating and Doge's failure

(40:48) Self-driving breakthrough: Waymo and Tesla FSD

(42:31) Why AGI talk has quieted down

(43:43) Supply constraints proving AI demand is real

Noah Glass is the founder and CEO of Olo, an enterprise platform for mobile and online ordering that powers digital commerce for 800+ restaurant brands and nearly 90,000 locations. Founded in 2005, Olo went public in 2021 at a $3.5B valuation and was acquired by Thoma Bravo in 2024—a 20-year journey from scrappy startup to category leader.

What you'll learn:

1. Why Olo's first 10 years required extreme "pain tolerance" waiting for product-market fit
2. The B2C to B2B pivot that transformed their unit economics from burning $15 per customer to earning revenue while scaling
3. How "embrace the suck"—borrowed from the Marine Corps—became the cultural mantra that kept the team going
4. Why going public was about customer confidence and long-term credibility, not exit or liquidity
5. The role of industry advisors in bridging credibility gaps when selling to traditional enterprises
6. How adding delivery-as-a-service (Dispatch) in 2015 unlocked escape velocity and scale advantage
7. The challenges and benefits of operating as a public company in a misunderstood industry
8. Why partnering with Thoma Bravo PE offers better alignment than quarterly public market pressures
9. Noah's philosophy on founder loyalty and the lifelong bonds formed with early team members
10. Why the current "homegrown tech stack" trend in enterprise is a passing fad that misses SaaS fundamentals

In this episode, we cover:

(00:00) Introduction and the "embrace the suck" mentality

(01:03) Early days and the long wait for product-market fit

(05:30) Why YC's "grow fast or quit" advice doesn't apply to every company

(08:06) The deep bonds formed with early team members

(12:14) Deciding between B2B vs B2C business models

(13:34) The B2C beginning and Good Morning America moment

(16:08) The pivot to B2B enterprise software

(20:43) How third-party delivery and DoorDash changed the industry

(23:04) The journey as a public company (2021-2024)

(27:49) Why going public signaled long-term stability to enterprise customers

(30:15) Operating under private equity with Thoma Bravo

(36:10) Breaking into enterprise sales with industry advisors

(44:45) The importance of reliability at scale for enterprise

(46:58) Thinking about market size and expansion in vertical software

(48:25) Rapid fire: Which founder inspires you most

(49:01) Uncomfortable feedback on being overly loyal

(50:48) Current trend prediction: Homegrown enterprise software is a fad

Parag Agrawal is the co-founder and CEO of Parallel, building infrastructure for the agentic web. Previously CEO of Twitter, Parag now leads a company architecting how AI agents will interact with the open web at orders of magnitude beyond current human scale. Two years after founding in stealth mode, Parallel recently announced a $100M Series B co-led by Kleiner Perkins and Index Ventures.

What you'll learn:

Why everything built for human web consumption will become irrelevant when agents become the primary users

How Parallel's APIs enable agents to search, fetch, and monitor the web with unprecedented scale and speed

The evolution from simple tool calls to autonomous sub-agents with real decision-making capability

Why the web must transition from "pull" (searching on demand) to "push" (alerting when conditions are met)

The new business models needed to compensate content creators in an agent-driven web

Parag's counterintuitive approach to fundraising: why VC rejections don't sting but customer rejections do

The rational game VCs play that founders misinterpret as genuine enthusiasm

Why Parag believes we're not in an AI bubble—but an overreaction is coming (and it'll be faster than dot-com)

How Parallel built quietly for a year before product-market fit arrived with the agent explosion

The operational philosophy of extreme in-person collaboration that shaped Parallel's early culture

In this episode, we cover:

(00:00) Introduction and Parallel's mission

(01:02) What Parallel's APIs enable for AI agents

(02:43) Practical examples: coding agents, sales automation, research

(04:57) The conviction bet on agents before the market existed

(10:54) New business models for content in the agentic web

(20:22) The $100M Series B fundraise and going public

(23:03) Why Parallel built in stealth with carefully chosen early customers

(24:55) Current scale and product offerings

(30:42) The evolution from tools to sub-agents to push-based web

(33:13) Are we in an AI bubble? Parag's nuanced perspective

(36:34) The mental models behind fundraising vs customer rejections

(38:37) Why VC enthusiasm is rational strategy, not signal

(45:37) Biggest career mistake: delaying Twitter's algorithmic timeline

(48:28) The compounding cost of six-month delays

(50:09) Finding inspiration in "re-founders" like Satya Nadella

(51:54) The most rewarding part: watching customers do unexpected things

(52:43) In-person culture and the transition to remote-friendly

Nicholas Rudder is the co-founder and CEO of Sphere, an AI-powered cross-border tax compliance platform that helps businesses navigate international sales tax, VAT, and GST regulations. After pivoting from a failed EdTech marketplace and losing his technical co-founder, Nicholas just raised $21M in Series A funding from Andreessen Horowitz—a remarkable comeback story that includes selling his first five contracts using only a Figma prototype.

What you'll learn:

1. How Sphere is becoming the "Deel of revenue compliance" for global businesses
2. Why Nicholas pivoted from EdTech after 18 months and what made him choose tax compliance
3. The strategy of selling contracts with a high-fidelity Figma prototype before building the product
4. How to convince investors to back a pivot when your co-founder has left
5. Why businesses struggle with international tax compliance and how AI solves it
6. The importance of hiring an internal recruiter once you raise significant funding
7. Why San Francisco remains the best place to build a startup despite the challenges
8. How YC's network helped navigate a critical health insurance crisis
9. The advantage of being a solo founder when recruiting high-quality founding engineers
10. Why raising from a position of strength creates better fundraising dynamics

In this episode, we cover:

(00:00) Introduction to Nicholas Rudder and Sphere

(01:10) The EdTech marketplace that didn't work

(03:08) Why EdTech is such a difficult market

(09:16) The hard pivot to tax compliance

(10:56) Selling five contracts with a Figma prototype

(13:10) When the co-founder left and twins arrived early

(21:58) Why international tax compliance is broken

(27:10) Sphere's vision as the "Deel of revenue compliance"

(31:34) The unintentional path to Andreessen Horowitz

(38:54) Why VCs all know when you're raising

(41:37) Building Sphere in SF vs. the UK or Australia

(46:23) Immad's advice on hiring internal recruiters

(51:14) Rapid fire: Founder inspirations and lessons learned