The Tech Trek

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/

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

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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

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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!

In this episode, Amir sits down with Trevor Lee, Co-founder and CEO of Myko AI, to unpack his unconventional leap from the finance world to building a cutting-edge tech company. Trevor shares how he navigated leaving a comfortable corporate job, using an MBA to break into tech, and the iterative process of finding product-market fit, including pivotal moments and lessons learned while bootstrapping and scaling his business.

🔥 Key Takeaways:

Trust Your Gut & Bet on Yourself: Trevor realized early that traditional corporate environments weren't for him. His dissatisfaction pushed him toward entrepreneurship.

Using an MBA as a Pivot Point: While some may dismiss the value of an MBA in tech, Trevor leveraged it to gain exposure, experiment, and network, ultimately identifying his ideal role as a tech founder.

Product-Market Fit is a Journey, Not a Destination: Trevor candidly discusses how his company pivoted multiple times, emphasizing constant customer discovery and iteration.

Bootstrapping Builds Grit: Failing to raise initial capital didn’t stop Trevor; instead, he bootstrapped MyKo, learning key lessons about resilience and resourcefulness.

Sales > Code (Sometimes): As CEO, Trevor unexpectedly found himself deeply involved in sales – a critical part of driving growth even for a technical product.

Location Isn’t Everything: Based in Florida, Trevor highlights how being outside Silicon Valley hasn’t limited his access to capital, mentors, or customers—especially in a post-remote world.

🕒 Timestamped Highlights:

00:28 – Trevor’s background: from finance to founding MyKo

01:36 – The motivation to leave a comfortable corporate job

03:05 – Why Trevor pursued an MBA to break into tech

05:36 – How the idea for Myko originated and evolved during business school

07:56 – Navigating pivots and recognizing when to change direction

09:58 – Aligning a small team during a pivot decision

11:38 – Confidence in the current product and growth focus

12:57 – The story behind bootstrapping vs. early fundraising struggles

14:54 – Shifting roles as CEO: From product to sales leadership

15:28 – Skills Trevor wishes he had focused on earlier (sales & technical chops)

17:02 – How mentors and investors have guided his journey

18:52 – Founding outside a traditional tech hub: Advantages and challenges

20:35 – Trevor’s vision for Myko's future: Hybrid remote growth strategy

21:40 – How to connect with Trevor for advice or collaboration

💡 Memorable Quote:

“You don’t truly appreciate how much chewing glass being a founder is and the level of unsexy, terrible work you have to do all the time.” – Trevor Lee

🎯 Audience Note:

This episode is a must-listen for anyone who is considering making the leap into entrepreneurship, especially those outside traditional tech hubs or without prior technical backgrounds.

💬 Connect with Trevor:

LinkedIn – https://www.linkedin.com/in/trevorlee20

In this episode, Amir is joined by Sachin Nene to explore what it really takes to thrive as a modern CTO. Sachin shares actionable strategies for balancing vision and execution, managing relationships with CEOs and fellow executives, and staying relatable and credible with engineering teams. They dive deep into the challenges of expectation management, engineering metrics, and how AI tools like LLMs are reshaping the future of engineering leadership.

Whether you're already in a leadership role or aspiring to step up, this conversation is packed with practical insights tailored for today’s fast-moving tech landscape.

Key Takeaways:

The CTO as a Strategic Subcontractor: Sachin redefines the CTO role as the "subcontractor" within the C-suite — fully responsible for delivery without burdening non-technical peers with unnecessary details.

Balancing Vision & Execution: Effective CTOs master both managing expectations upwards and maintaining technical credibility downward, acting as the glue between business goals and engineering execution.

Building Trust with Engineering Teams: Staying relatable means understanding current trends (like LLMs), engaging in technical brainstorming, and being able to advocate for the team at any level.

Avoid Over-Optimizing Metrics: Sachin warns against over-indexing on engineering metrics (e.g., DORA metrics) when they risk detaching teams from meaningful business impact.

Future-Proof Engineering Leadership: With AI’s influence growing, CTOs must rethink hiring profiles and team structures, moving toward polyglot engineers who can flex between product, business, and technical hats.

Timestamped Highlights:

[00:00] Introduction & Overview: Sachin’s journey from Upside CTO to launching fractional CTO services.

[01:00] CTO Relationship with C-suite: Why the CTO operates differently from other executives, and why it’s akin to a subcontracted role.

[03:00] Balancing Business & Technical Leadership: How Sachin keeps one foot in business strategy and one in technical leadership.

[07:00] Staying Relatable to Engineering Teams: Practical ways to stay connected—personal research, whiteboarding sessions, and knowing when to step into the technical weeds.

[10:00] Translating Strategy into Metrics: The difficulty of measuring engineering success without losing sight of broader goals.

[14:00] Dangers of Over-Optimizing Metrics: The risk of becoming overly process-driven and detached from actual business outcomes.

[16:00] Technology-Driven Revenue Opportunities: How a CTO ensures technology investments align with business shifts, particularly in SaaS models.

[19:00] Preparing for the AI Shift: Why LLMs and AI tools require a new type of engineering team and leadership approach.

[22:00] The Shift Left in Engineering: Why tomorrow’s engineers need to think more like product managers and business leaders.

Featured Quote:

"The ideal CTO is the king or queen of expectation management—balancing business impact with technical trust, without getting lost in jargon or micromanagement." — Sachin Nene

Links:

Connect with Sachin on LinkedIn: https://www.linkedin.com/in/sachinnene/

Learn more at sachinnene.com

Call to Action:

👥 Know an engineering leader or tech exec who’d benefit from this guide? Share this episode!

✅ Subscribe, leave a review, and drop a comment—let us know what resonated most!

In this episode of The Tech Trek, Amir Bormand sits down with Nirmal Ranganathan, CTO, Global Public Cloud at Rackspace, to dissect one of the hottest and most crucial topics in today’s tech landscape—trust in AI applications. They explore how enterprises can drive adoption of AI solutions, what key factors are needed to foster trust, and why guardrails, security, and change management play a pivotal role. Whether you're a developer, tech leader, or AI enthusiast, this episode dives deep into the challenges and opportunities shaping the future of AI adoption.

Key Takeaways

• Trust is the Cornerstone: For AI adoption to succeed, users must trust the output. Trust hinges on data quality, security, responsible use, and model transparency.
• Change Management Matters: Adoption in enterprises isn't about trends—it’s about clear processes, education, and user enablement.
• Guardrails Are Non-Negotiable: Especially when AI is exposed to external users, organizations need strong safety checks—think toxicity filters, bias mitigation, and strict data governance.
• Scaling AI = Scaling Costs: Unlike typical systems, scaling AI comes with heavy computational costs. Patterns like caching and model optimization are essential for sustainability.
• Prompt Engineering & Peer Learning: The secret to effective enterprise AI adoption is empowering users to master prompt engineering and fostering peer collaboration.
• Future of Adoption: 2025 might not yet be the year of mass AI production rollout, but the curve is gradually climbing—especially with evolving architectures and better model accuracy.

Timestamped Highlights

• [00:00:00] Introduction to Nirmal Ranganathan & the importance of trust in AI
• [00:01:34] Why adoption is key—and why most tech projects fail due to lack of it
• [00:02:50] Three pillars of successful AI adoption: Trust, Change Management, Functionality
• [00:05:02] The trust barrier: Hallucinations, relevance, and grounding AI responses in enterprise knowledge
• [00:10:01] Why most AI projects are stuck in POCs—and what's preventing full-scale deployment
• [00:11:43] Technical guardrails: Security, scalability challenges, and compliance considerations
• [00:14:56] Cost & infrastructure challenges when scaling AI solutions to millions of users
• [00:17:52] How tech companies differ from enterprises in deploying AI—data privacy, safety checks, user unpredictability
• [00:20:00] The role of prompt engineering, peer learning, and experiential training in ensuring AI adoption success
• [00:22:16] What the future holds for AI adoption—and why the heavy lifting might get easier

Featured Quote "AI adoption compounds all of our existing challenges—and then multiplies them by five or ten times." — Nirmal Ranganathan

Connect with Nirmal

• LinkedIn: https://www.linkedin.com/in/rnirmal/

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