In this episode, Amir sits down with Meg Henry, Head of People & Talent at Companyon Ventures, to unpack a critical—yet often overlooked—aspect of growing technical teams: onboarding.

Engineering leaders spend weeks hiring top talent, only to fumble the first 90 days. Meg shares a tactical, startup-friendly approach to onboarding that actually helps new hires ramp faster, become productive sooner, and stick around longer. If you’ve ever onboarded a dev by tossing them a laptop and saying "Good luck," this one’s for you.

🗝️ Key Takeaways for Tech Leaders:

Weak onboarding kills productivity. Even A+ hires won’t thrive if they don’t know how to succeed.

You’re losing time, not saving it. A 30-minute onboarding plan can prevent months of confusion.

Hybrid makes things harder. Without structure, async teams sink.

Consistency beats chaos. No two roles are the same, but every new hire should feel supported.

AI can help you scale onboarding. Especially when documentation is scattered across Slack, Notion, and Drive.

🕒 Timestamped Highlights:

[00:02:00] Why startups obsess over hiring—but ignore onboarding

[00:04:30] That awkward new hire phase, and how to design around it

[00:05:45] Hybrid onboarding: Why access > answers

[00:07:15] The two onboarding tracks every company needs: company-wide + role-specific

[00:09:30] Founders want plug-and-play hires—but that doesn’t work without a plan

[00:10:45] "Here’s your map": how tech leads can shortcut the ramp-up curve

[00:13:30] Using ChatGPT to build lightweight onboarding flows? Yes, here’s how

[00:15:45] Spotting weak onboarding when you inherit a team

[00:18:15] Customization vs. consistency: how much is too much?

[00:20:00] Time investment: just 2.5 hours over 3 months

💬 Quote of the Episode:

“Before GPS, you wouldn’t invite someone over and just say, ‘Figure out how to get here.’ Even your most autonomous hires need directions.” — Meg Henry

📬 Connect with Meg:

Meg’s helping early-stage B2B startups scale smarter. Connect with her on LinkedIn (Meg Henry, Companyon Ventures) and ask for her free onboarding template—it’s lightweight, practical, and startup-tested.

In this episode, Carlos Peralta returns to The Tech Trek to dive deep into data culture in the wearable tech space, sharing how WHOOP turns petabytes of real-time biometric data into personalized, actionable insights. We explore the technical complexities behind data ingestion, transformation, and delivery, and how the mission-driven nature of WHOOP influences both their engineering decisions and company culture.

🔑 Key Takeaways

Wearable tech = real-time big data: WHOOP processes petabytes of multimodal data from edge devices to deliver insights to users in near real time.

Data must be actionable, not just abundant: It's not about the quantity of data collected, but how that data is translated into meaningful guidance for users.

ML Ops is central to product success: The data and ML infrastructure team plays a critical role in feature development, roadmap planning, and performance optimization.

Mission fuels motivation: WHOOP’s internal culture is deeply driven by its impact on human performance—employees are often users of the product themselves.

Scalability ≠ just growth: Cost-efficiency, forecasting, and cloud infrastructure readiness are vital to scaling responsibly in a global market.

⏱️ Timestamped Highlights

00:00 – Intro to Carlos & the mission behind WHOOP

02:19 – Data culture at WHOOP vs. traditional companies

04:15 – Scale of data in wearables: petabytes, not megabytes

05:52 – Complexity of ingesting, transforming, and delivering personalized data

08:53 – Striking a balance: Real-time feedback vs. cloud cost efficiency

11:14 – Scaling the platform as the member base expands globally

13:43 – Internal motivation and culture driven by positive impact stories

15:56 – Why data teams are involved early in the product roadmap

17:59 – Carlos’ journey from WHOOP user to WHOOP employee

20:40 – How to connect with Carlos + final thoughts

💬 Quote of the Episode

“You can have petabytes of data, but if you can’t make it queriable, understandable, and actionable—it’s just noise.” — Carlos Peralta

In this episode of The Tech Trek, Amir Bormand sits down with Max Mergenthaler-Canseco, CEO and co-founder of Nixla, to explore the nuanced reality behind startup success. A multi-time founder with experience as both CEO and CTO, Max shares hard-earned lessons from his entrepreneurial journey—including why theoretical knowledge often clashes with real-world execution, how to build a resilient startup team, and the underestimated danger of survivorship bias in startup lore.

From balancing optimism with statistical failure rates to knowing when to focus on strengths over weaknesses, Max delivers practical wisdom for anyone navigating the startup grind. Whether you're a first-time founder or on your third venture, this conversation will leave you thinking differently about what it really takes to succeed in tech.

🔑 Key Takeaways

Experience is not a blueprint, it's a lens. Max breaks down how startup learnings aren’t always repeatable but instead shape the founder’s decision-making over time.

Passion is the sustainability engine. You have to love what you're building, not just what the market wants—otherwise, you won’t last through the inevitable startup grind.

Founders vs. early employees. Understanding the difference in motivation and expectations is crucial to building and managing a startup team effectively.

Survivorship bias is everywhere. Max cautions against building a startup playbook based only on outlier success stories.

Know your lane. Instead of leveling up all weaknesses, focus on doubling down where your strengths make the biggest impact.

⏱️ Timestamped Highlights

00:44 – What is Nixla?

Max introduces his company, a time series forecasting and anomaly detection startup with deep roots in research.

01:34 – Serial founder life

Max gives a quick snapshot of his startup journey, from NLP experiments to YC-backed fintech.

03:21 – Startup experience ≠ shortcut to success

Why practical experience matters more than theoretical frameworks, and how each startup is its own universe.

07:59 – Playing the startup game because you love it

Max explains why loving the problem you’re solving is essential for long-term survival and sanity.

10:53 – Hiring the right people early

What Max looks for in early-stage team members—and why founders shouldn't expect employees to grind the same way they do.

13:24 – CEO vs. CTO: Vision vs. Execution

A thoughtful breakdown of the distinct roles and responsibilities between CEO and CTO, especially in early-stage companies.

16:27 – Strengths over Weaknesses

Why Max believes in focusing on what you do well, rather than fixing every flaw.

20:25 – The trap of survivorship bias

A fascinating conversation about how the startup ecosystem overemphasizes success stories and ignores the valuable lessons of failure.

How to reach Max

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

💬 Featured Quote

“The only way to keep playing the startup game is to actually enjoy the game.” — Max Mergenthaler-Canseco

In this episode, I sit down with Jason Rogers, CEO & Co-Founder of Invary, to explore an unconventional approach to building a cybersecurity startup—leveraging a tech transfer agreement with the NSA. Jason shares his journey of launching a company around licensed technology, the benefits and challenges that come with it, and why runtime system integrity is becoming a crucial factor in modern security strategies.

We also dive into how AI is changing the cybersecurity landscape, the importance of real-time security validation, and how companies can better protect their systems against evolving threats.

Key Takeaways

🔹 Tech transfer provides a competitive edge – Licensing government-developed technology can offer startups a head start with validated, battle-tested IP.

🔹 Security needs to be proactive, not reactive – Real-time validation of system integrity can prevent breaches before they escalate.

🔹 Collaborative research fuels innovation – Invary works with the NSA and academic institutions to advance security capabilities.

🔹 AI is expanding the attack surface – As AI adoption grows, ensuring system and data integrity will be more critical than ever.

🔹 Zero trust applies to machines too – It’s not enough to verify users—organizations must continuously verify their systems.

Timestamped Highlights

⏳ 00:01 – Introduction to Jason Rogers and Invary’s mission

⏳ 00:49 – How NSA-licensed technology is securing critical systems

⏳ 01:36 – The journey from research-backed tech to startup success

⏳ 02:56 – The challenges and benefits of building a business around licensed IP

⏳ 05:32 – Collaborating with government research teams for innovation

⏳ 09:33 – How engineers adapt to the tech transfer model

⏳ 14:06 – Why runtime integrity is the missing piece in security

⏳ 16:34 – The shift from traditional security models to real-time validation

⏳ 19:27 – AI’s growing attack surface and what it means for security

⏳ 23:28 – Predicting future cybersecurity challenges in an AI-driven world

⏳ 24:00 – How to connect with Jason

Quote from the Episode

“The bad guys collaborate all the time. It’s time for the good guys to do the same.” – Jason Rogers

Connect with Jason Rogers

🔗 Website: Invary.com

🔗 LinkedIn: https://www.linkedin.com/in/jasonlrogers/

Stay Connected with The Tech Trek!

🎧 Like what you heard? Subscribe, rate, and review on your favorite podcast platform!

📩 Have feedback or guest suggestions? Connect with Amir on LinkedIn.

🔔 Follow for more deep dives into technology, security, and innovation.

In this episode, Amir sits down with Kaustav Das to discuss one of the most critical yet challenging aspects of analytics—asking the right questions. They explore how analytics leaders can better navigate conversations with stakeholders, ensuring they gather the correct requirements and deliver actionable insights. The conversation touches on the evolving role of analytics, the impact of generative AI in business intelligence, and how decision-making is shifting toward more conversational data engagement.

Key Takeaways

The Power of Asking the Right Questions: The quality of analytics is only as good as the questions being asked. Stakeholders’ intent must be fully understood before diving into solutions.

Balancing Speed with Thoughtfulness: Quoting Einstein, Kaustav highlights the importance of preparation: “If I were to chop a tree down in an hour, I would spend 55 minutes sharpening my blade.” Rushing to a solution without understanding the problem leads to inefficiencies.

Technology vs. Process: Not all business challenges require a technology-driven solution. Often, simpler process optimizations can be more effective.

Conversational Analytics & AI: Generative AI is shaping analytics by making data interactions more intuitive, but expertise in asking the right questions remains critical.

Roadmapping for Success: The PTP (Present-To-Path) framework helps stakeholders clarify their goals, define a roadmap, and create an execution timeline for analytics projects.

The Art vs. Science of Analytics: Analytics is more of an art than a science. Understanding business goals, managing multiple stakeholders, and iterative questioning are key to driving value.

Timestamped Highlights

[00:00] Introduction to the episode and guest, Kaustav Das.

[01:08] Why asking the right questions is critical in analytics.

[04:58] Do technologists jump to solutions too quickly?

[06:01] The balance between planning and execution in a fast-paced environment.

[07:28] The high failure rate of technology projects—why intent matters.

[10:52] The five “whys” technique and getting to the core of business problems.

[12:24] The future of analytics—can it become more conversational?

[17:03] Measuring ROI in marketing and media analytics.

[20:29] Where to connect with Kaustav Das.

Quote of the Episode

"If I were to chop a tree down in an hour, I would spend 55 minutes sharpening my blade." – Albert Einstein, referenced by Kaustav Das

Connect with Kaustav Das

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

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What happens when you build a business around what you genuinely love? In this episode of The Tech Trek, Amir sits down with Michael Farb, CEO of Boatsetter — the Airbnb of boats — to unpack how passion can be a strategic advantage in tech entrepreneurship.

Michael shares his journey of launching multiple businesses rooted in personal interests, from college sports to global philanthropy to now, outdoor water adventures. Together, they explore what it really takes to turn a personal obsession into a scalable business, how to identify real opportunities in your hobbies, and why solving a specific problem matters more than chasing a massive market.

Whether you're dreaming about launching your own thing or leading product inside a startup, this conversation is packed with insights on product-market fit, customer discovery, and building teams who care as much as you do.

🧠 Key Takeaways

Passion is a superpower: When you’re obsessed with a hobby or space, you naturally develop deep insights others don’t see — and that can unlock serious business potential.

Solving problems > chasing scale: Michael shares how the best businesses often start by solving a very specific problem — even if that solution doesn't scale at first.

Inspiration is everywhere: Whether it’s boats, black cars, or model airplanes, there’s almost always a business idea hiding in what people love to do.

Team alignment is critical: Boatsetter thrives by hiring people who live and breathe outdoor adventure — passion isn't just a founder trait, it's company-wide.

Don’t overthink TAM: Many aspiring founders kill ideas too early worrying about market size. Start small, build value, and the market might grow with you.

⏱️ Timestamps & Highlights

00:00 – Introduction

Michael Farb joins Amir to talk about building businesses around personal passions and how that philosophy led to Boatsetter.

01:00 – What is Boatsetter?

A two-sided marketplace for boat rentals in 700+ global locations. No boating license? No problem.

02:20 – Michael’s Entrepreneurial Journey

From sports recruiting tech to nonprofit fundraising platforms — every business tied back to something he personally cared about.

04:45 – How to See the Business in Your Passion

“If you’re obsessed with a space, you’ll know more than anyone else. That’s your edge.”

08:00 – Advice for Aspiring Passion-Driven Entrepreneurs

Look for friction points in your hobby — that’s where business opportunities are born.

10:50 – Employees with Passion

Boatsetter hires people who love the water. They even get boating credits as part of their benefits.

14:00 – Working with Product Teams as a Passionate CEO

Michael partners closely with product to scale both sides of the marketplace — consumers and boat owners.

16:00 – Would He Ever Build a Business Without Passion?

Short answer: No. The passion + business combo has worked too well to ditch.

19:00 – Do You Need Market Research to Start?

Michael skips the spreadsheets — he talks to real people and builds MVPs to validate problems.

21:30 – “Do Things That Don’t Scale”

The early Boatsetter days were scrappy. Human-powered logistics and manual processes — until the model was proven.

24:40 – How to Connect with Michael

Find him on LinkedIn or visit Boatsetter.com.

💬 Quote to Share

“Don’t get paralyzed trying to figure out how big the market is — just solve a real problem. Everything big started small.” – Michael Farb

Want more stories like this?

Follow, rate, and share The Tech Trek wherever you get your podcasts. Got feedback or guest suggestions? Hit up Amir on LinkedIn or drop a comment.

In this episode, Zachary Hanif, VP of AI, ML, and Data at Twilio, joins Amir to talk about the engine behind B2B AI innovation. From selecting the right tools to navigating the shift from POCs to production, Zachary offers an insider's look at how enterprises can thoughtfully and effectively integrate AI.

We unpack:

The danger of "boiling the ocean" with AI

Why chatbots aren’t always the right starting point

What makes an AI POC actually valuable

And why UX in the age of AI needs systems thinking

💬 “If you come into it with a technology and not a firm understanding of the problem, you're going to solve a problem that isn’t there — and at best, you'll just end up with a great tech demo.” – Zachary Hanif

🔑 Key Takeaways

Start with the use case, not the tool: Jumping in with LLMs without a clear business problem leads to superficial results.

UX in AI is different: You’re not just designing for humans—you're designing for a human-model-human interaction loop.

POCs must build trust: Especially with generative AI, proof-of-concepts must feel reliable and human-like to succeed.

AI increases surface area: Models introduce new attack surfaces and complexities. Security, observability, and model risk management are critical.

Think systems, not screens: LLMs change how users interact with software. This demands broader thinking from designers and PMs.

⏱️ Timestamped Highlights

00:00 – Intro to Zachary Hanif and Twilio's AI mission

02:05 – Why most companies are AI tool users, not tool makers

04:25 – The “chatbot temptation” and why it might not be the best starting point

06:00 – UX lessons from Google’s early search box vs. today’s LLMs

08:30 – Why we’re still early in discovering transformative AI use cases

11:55 – How AI changes what a good POC looks like

14:59 – Should AI UX be its own discipline?

18:23 – How to know when a POC is ready for production

22:12 – Dealing with AI’s expanding “surface area” and model drift

25:56 – Why model risk management matters more than ever

In this episode, Amir chats with Bobby Touran, the non-technical CEO and co-founder of Rainbow, an insurance tech company that thrives on strong engineering culture. They dive deep into how non-technical founders can effectively collaborate with technical teams, foster a hybrid office culture, and ensure that engineers are closely aligned with business objectives. Bobby shares how Rainbow maintains a tight feedback loop, how returning to in-office work has shaped their growth, and why AI isn’t necessarily replacing jobs in insurance but transforming them.

🔑 Key Takeaways:

Non-technical founders can be powerful allies to engineering teams by focusing on context, communication, and fostering a collaborative culture.

Being back in the office has served as a key differentiator in attracting engineers who value social interaction and cross-functional communication.

Culture is not static—Bobby emphasizes actively evolving it through regular offsites, tools like Slack Donut, and clear alignment between technical and business teams.

Engineering teams thrive when given real-world context—Rainbow’s practice of dining at insured restaurants is a brilliant example of tying product to user impact.

Transparency and experience matter—Rainbow’s engineering team is senior, engaged in thoughtful discussions on technical debt, and values clear communication around business priorities.

AI is reshaping roles, not removing them—Bobby shares his view that AI will augment rather than replace underwriting and risk assessment functions in insurance.

⏰ Timestamped Highlights:

00:00 – Introduction to Bobby Touran and overview of Rainbow’s mission.

02:10 – Bobby’s approach as a non-technical founder and fostering strong relationships with engineers.

04:43 – Building a healthy engineering org: culture is intentional, not accidental.

07:48 – The importance of engineers understanding the "why" behind product decisions.

10:29 – Why being back in the office twice a week has helped Rainbow’s growth and culture.

15:03 – How engineering and leadership collaborate on roadmap and growth opportunities.

19:03 – Decision-making confidence: balancing business opportunities and engineering cycles.

21:59 – Bobby’s take on AI's role in insurance and how Rainbow is integrating it.

25:43 – Connect with Bobby and explore career opportunities at Rainbow.

💡 Featured Quote:

"The culture is not something that you define and it just is what it is. It’s something you actively work on. It’s always evolving." – Bobby Touran

📢 Connect & Learn More:

Website: useRainbow.com – Check out the About Us page and open engineering roles.

LinkedIn: https://www.linkedin.com/in/bobby-touran-782a6513/

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In this episode, Vijay Sankararaman breaks down how to intentionally build a low-churn, high-impact team culture. Whether you’re a tech leader, manager, or individual contributor aiming to level up your leadership skills, Vijay shares tangible lessons and frameworks to keep your team motivated, productive, and resilient—without sacrificing authenticity.

📚 Lessons & Leadership Takeaways

Lesson 1: Crafting Vision That Sticks

"Am I valued?"

— the question every team member subconsciously asks.

Vijay emphasizes the importance of clarity + buy-in. It’s not enough to have a lofty team vision—you need to ensure each person sees themselves in that vision. Leaders must actively align the team's purpose with individual validation.

Lesson 2: Understanding Intrinsic Motivation

“Enthusiasm is common. Endurance is rare.”

Borrowing from Angela Duckworth, Vijay discusses the challenge of sustaining energy over time. His approach:

• ✔️ Learn each team member's personal definition of growth.
• ✔️ Help light the fire beneath their intrinsic goals—not just professional milestones, but personal fulfillment.

Lesson 3: Building Enduring Trust & Vulnerability

Vijay advocates for psychological safety and social freedom:

• Leaders must create spaces where people can drop their guard, shed ego, and express goals or concerns.
• Authenticity at the leadership level trickles down—trust is the currency that keeps teams aligned.

Lesson 4: Managing Ambiguity with the 80-10-10 Rule

“Not every conversation needs 100% clarity.”

Vijay’s 80-10-10 framework:

• 80% of information → shared openly with the whole team.
• 10% → reserved for focused 1:1 conversations.
• 10% → intentional ambiguity to encourage senior team members to develop resilience and independent thinking.

Lesson 5: Productive Friction & Healthy Chaos

Conflict isn’t the enemy—it’s a tool.
Vijay encourages creating healthy chaos:

• Focus more on asking the right questions than offering immediate solutions.
• Curiosity-driven leadership + active listening ensures issues surface early, and innovations thrive.

🕒 Timestamped Highlights

• 00:00 — Intro to Vijay & episode topic
• 01:59 — Defining “high impact” in tech teams
• 03:11 — Vision clarity & team buy-in strategies
• 05:18 — Aligning personal growth goals with team objectives
• 09:29 — Building trust & psychological safety
• 12:17 — Why productive chaos is essential
• 14:40 — Team collaboration over perfection: Vijay’s puzzle exercise
• 18:32 — Communication strategy: 80-10-10 rule
• 22:00 — Connect with Vijay on LinkedIn

📢 Quote of the Episode

"Enthusiasm is common. Endurance is rare. As leaders, it’s our job to sustain that energy, to light the fire beneath each individual’s intrinsic motivation."

— Vijay Sankararaman

🔗 Connect & Share

Enjoyed this leadership deep dive?
➡️ Share it with someone leading (or aspiring to lead) high-performing tech teams.
➡️ Leave a review, subscribe, and help spread the word on building resilient, motivated teams in tech!

In this episode, Amir sits down with Santhosh Kumar, Head of Data at Trepp, to unpack the evolving world of Data as a Product. Data is no longer just a support function—it’s becoming a core business driver. Santhosh shares how data teams are embracing a product-oriented approach, aligning closely with business goals while mirroring software engineering practices.

If you’ve ever wondered:

How data can be treated like a shippable product

What mindset shifts data teams need

And how collaboration between data, product, and tech teams is evolving

This episode is for you!

🔥 Key Takeaways:

Data as a Product = Data with Purpose:

It’s not just about pipelines and reports—it’s about delivering business value like increased revenue, better user experience, and cost optimization.

Striking a Balance Between Tech & Business:

Santhosh emphasizes that successful data teams blend technical excellence with a strong understanding of business objectives. It’s not one or the other.

Mindset Shift is Crucial:

Data teams must move from being reactive service providers to proactive product thinkers—asking the right questions, prioritizing value, and collaborating closely with stakeholders.

Alignment with Software Engineering Practices:

Data engineering is increasingly mirroring software engineering: roadmaps, product managers, long-term planning, and ownership are becoming key.

The Role of Data Quality & Governance:

In the age of productized data, ensuring accuracy, governance, and discoverability at every stage is non-negotiable.

⏱️ Timestamped Highlights:

[00:00] Introduction to Santhosh Kumar & TREP’s mission in structured finance, CRE, and banking data.

[02:00] What does Data as a Product actually mean? Why it’s more than dashboards and CSVs.

[04:00] Balancing tech and business—where Santhosh’s team fits.

[07:00] Collaboration challenges: aligning with tech teams & self-serving stakeholders.

[09:00] How treating data like a product impacts strategy and mindset shifts.

[12:00] Key differences between data pipelines and software engineering cycles.

[14:00] The role of product managers on data teams.

[16:00] The increasing technical depth of data teams & potential future bifurcation of business vs. technical roles.

[18:00] Roadmap planning: how far ahead data teams are planning, and why.

[19:30] Final thoughts and how to connect with Santhosh on LinkedIn.

💡 Featured Quote:

"We use technology to translate business requirements and maximize value—that's where the magic happens. Data isn't just numbers; it's a product with purpose." – Santhosh Kumar

📣 Enjoyed this episode? Share it with your fellow data practitioners, software engineers, or tech leaders. Let’s get the conversation rolling—especially with CTOs and VPs who need to collaborate tighter with data teams!