Deborah Hanus, Co-founder and CEO at Sparrow, joins Amir to unpack the founder journey from academia to building a scaled company. They dig into why leave management is still a messy, high stakes problem, and how Sparrow is turning it into a clean, guided experience for both HR and employees.

Sparrow helps companies provide employee leave across the United States and Canada, and Deborah shares what it really takes to scale a compliance driven business without slowing down. From founder resilience and early stage emotional swings to hiring, onboarding, and culture design, this one is packed with lessons for operators and builders.

Key takeaways

• Academia can be real founder training, especially for building resilience and hearing “no” without losing your edge

• Early stage startups feel brutal because you have too few data points, it is easy to overreact to every win or setback

• Compliance and leave are fundamentally data problems, the right info to the right person at the right time changes everything

• Scaling leadership is mostly communication and alignment, five people and 250 people require totally different systems

• Culture does not stay stable by accident, values must drive hiring, training, rewards, and performance management

Timestamped highlights

00:37 What Sparrow does, and the 300 million dollars in payroll cost savings milestone

01:37 Why academia can prepare you for founding, and how customer pain beats outside skepticism

03:40 The leave compliance mess, and why state by state rules made the problem explode

08:25 The two real ways startups die, and why morale matters as much as cash

12:55 Leading at scale, onboarding, clarity, and the feedback questions that keep teams aligned

19:54 “Scale intentionally” as a culture principle for a company that cannot afford to break things

25:48 Keeping values stable while everything else evolves as the team grows

A line worth sharing

“Companies end when you run out of cash or you run out of morale.”

Pro tips you can steal

• Treat the employee journey like a product journey, from recruiting through promotions and hard moments

• Before a big change, collect questions early so the message lands where people actually are

• After a meeting, ask “What were the main points?” to see what people heard, then tighten your messaging

• Invest in onboarding and goal clarity to prevent teams from drifting into competing priorities

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Max Bruner, Founder and CEO of Anzen, joins Amir Bormand to break down why insurance is quietly one of the biggest data and workflow opportunities in tech right now. They dig into Max’s unconventional path from foreign policy to building an executive liability marketplace, and what it really takes to modernize a slow moving industry with AI.

If you care about building in real world markets, scaling with discipline, and using AI for more than content, this one will sharpen your thinking fast.

Key Takeaways

• Insurance is not flashy, but it is foundational, massive, profitable, and packed with repeatable workflows that software can improve

• The best tech opportunities are often in slow moving industries with lots of data and outdated systems

• Better decision making comes from predicting outcome impact and pressure testing your thinking with a strong community around you

• AI value is clearest when it drives real operations, faster transactions, lower costs, and better service

• Fundraising is a pipeline game now, treat it like sales, build the plan, hit the numbers, run a tight process

Timestamped Highlights

00:42 What Anzen actually does, a one stop marketplace for executive liability quotes across the US

02:29 From Arabic studies and foreign policy to discovering insurance through political risk

08:12 The curiosity engine, how deep research habits shaped his ability to build in new domains

11:23 Decision guardrails, learning from outcomes and using trusted people to keep you efficient

13:12 Why choose insurance, building in industries that make the world work, plus the profit reality

17:29 The startup advantage, modern infrastructure vs incumbent legacy systems, and why catching up takes time

20:36 Raising in today’s market, what changed, what worked, and why the pitch volume matters

A line worth stealing

“Sometimes in tech we miss the application, there are massive industries to go change if we apply technology in the right way.”

Max Bruner

Pro Tips for builders

• Pick markets with repeatable workflows, you can ship measurable value faster

• Spend your time where the outcome impact is high, skip low ROI rabbit holes

• Build a real financial plan before fundraising, then operate close to it

• Run fundraising like a sales process, pipeline, volume, and discipline win

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Stu Solomon, CEO of HUMAN, joins Amir to unpack a blind spot most teams underestimate: a huge share of online activity is not people at all, it is automated traffic. They break down how verification really works at internet scale, why agentic workflows change the rules, and what it will take to build trust when bots transact with bots.

If you have ever wondered how fraud, fake clicks, account abuse, and synthetic behavior get caught in real time, this episode is a clear, practical look behind the curtain.

Key takeaways

• Most of the internet is machine traffic now, the goal is no longer spotting bots, it is separating good machines from bad ones

• Trust is built by combining behavior, infrastructure signals, and identity or credential history into fast decisions at scale

• Agentic systems lower the barrier to entry for attackers, less skilled actors can now create outsized impact

• The hard part is accountability, when a machine acts with your authority, who owns the outcome

• Adoption follows convenience, but visibility matters, if it feels like a black box, people will not trust it

Timestamped highlights

00:33 HUMAN in plain English, making split second decisions about who is human, and whether they are safe

03:59 The trust stack, behavior signals, infrastructure clues, and identity or credential history

10:19 The real shift with AI, lower barriers for attackers, plus the rise of agentic autonomy

14:37 The cake story, an agent completes the task, then surprises you with a 750 dollar bill

17:22 Bots talking to bots, where accountability and liability get messy fast

24:18 Security builds trust, trust unlocks adoption, and society is already closer than it thinks

A line you will remember

“We have always operated on the notion that if you are human, you are good, and if you are a machine, you are bad. That is simply not the case anymore.”

Practical ideas you can use

• Add guardrails when you delegate to tools, especially budgets, limits, and approval steps

• Watch for trust signals, not just identity checks, behavior plus infrastructure plus history beats any single data point

• Design for visibility, show users what the system did and why, so trust can compound over time

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