The Tech Trek

In this episode, Amir interviews Jen Kodner, a Talent Partner at Threshold Ventures and DFJ Growth, to discuss best practices and challenges in leadership hiring for startups. They explore the importance of finding the right leadership fit for different growth phases, professionalizing key functions, and balancing the hands-on approach required at early stages. Jen shares insights on the dynamics of player-coach roles, setting appropriate expectations for new hires, and the intricacies of delegating responsibilities from founders to new leaders. The conversation provides valuable advice for founders and those involved in talent acquisition at growing startups.

Highlights:

02:56 Challenges in Leadership Hiring for Startups

03:54 Professionalizing Functions in Early-Stage Companies

04:45 The Role of Sales Leaders in Startups

06:31 Navigating Founder Expectations and Leadership Roles

17:29 Traits of Successful Leadership Hires

Guests:

Jen Kodner is the Talent Partner at Threshold Ventures and DFJ Growth, where she advises portfolio companies on strategies to identify, attract, and retain top talent. Before joining these firms in 2018, Jen was a Talent Partner at Box, where she also led recruiting efforts. With extensive experience in talent acquisition, Jen plays a crucial role in helping companies build world-class teams.

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

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Thank you so much for checking out this episode of The Tech Trek. We would appreciate it if you would take a minute to rate and review us on your favorite podcast player.

Want to learn more about us? Head over at https://www.elevano.com

Have questions or want to cover specific topics with our future guests?

Please message me at https://www.linkedin.com/in/amirbormand (Amir Bormand)

In this episode, Amir Bormand sits down with Joe Emison, CTO and Co-Founder of Branch Insurance, to discuss how modern software development can be made cheaper, faster, and better. Joe shares insights from his book Serverless is a Game Changer and explains how embracing managed services and serverless architectures can lead to greater efficiency and scalability. He also dives into the cultural and organizational shifts required to truly optimize software development for speed and cost while reducing technical debt.

Key Takeaways:

✅ Managed Services = Speed & Efficiency – Leveraging third-party managed services allows teams to develop and scale faster while reducing maintenance burdens.

✅ Code is a Liability, Not an Asset – The more code you maintain, the more complex your system becomes. Focus only on writing code that directly differentiates your business.

✅ Continuing Education is Critical – Software development evolves rapidly, yet many CTOs and engineering leaders fail to keep up with new technologies.

✅ Breaking the Myth of IP in Code – Not all in-house software is valuable intellectual property. If a managed service can replace custom code, it often should.

✅ The Power of High-Velocity Development – Companies that iterate daily rather than monthly will always outpace their competition.

✅ DORA Metrics are Essential – If your team isn’t shipping multiple times a week, you need to rethink your development processes

✅ CTOs Must Stay Hands-On or Stay Informed – Leaders who lose touch with modern development practices risk making costly, outdated decisions.

Timestamped Highlights:

⏱ [00:02:00] – The evolution of software development: How managed services like Twilio have simplified engineering.

⏱ [00:05:00] – How Branch Insurance built a full-stack regulated insurance company with 1/30th of the engineering headcount of its competitors.

⏱ [00:08:00] – Why software leaders struggle with continuous education and how it leads to outdated development practices

⏱ [00:13:00] – The danger of engineering leaders making high-impact decisions without technical awareness.

⏱ [00:16:00] – The reality of technical debt and why sometimes rewriting from scratch is the best solution.

⏱ [00:21:00] – The biggest mistake companies make: Treating all code as valuable instead of focusing on high-impact differentiators.

⏱ [00:26:00] – The Shopify analogy: Why most applications contain large portions of non-differentiated, commodity code

⏱ [00:27:00] – Joe’s final thoughts: Optimize for business impact, not code complexity.

Quote from the Episode:

"The value of a business isn’t the amount of code it writes; it’s the experience it creates and the customers it serves. The less custom code you need, the better." – Joe Emison

Resources & Links:

📖 Joe’s Book: Serverless is a Game Changer

🔗 Follow Joe Emison: https://www.linkedin.com/in/joemastersemison

💡 Enjoyed the episode? Like, subscribe, and share with your network! Leave a comment or review to let us know your thoughts.

In this episode, Amir interviews Rehgan Bleile, Co-Founder and CEO of AlignAI, about her transition from founding a nonprofit organization to leading a for-profit AI company. Rehgan shares insights into the differences between nonprofit and for-profit ventures, the skills required, and the lessons learned. She discusses the origins and mission of Women In Analytics (WIA), a nonprofit aimed at increasing visibility for women and diverse voices in AI and analytics. She details the challenges and strategies involved in scaling both WIA and AlignAI. Rehgan also talks about her passion for entrepreneurship, the importance of intentionality in business, and the evolving role of data science. The episode offers valuable takeaways for aspiring nonprofit founders and startup entrepreneurs.

Highlights

01:40 Women In Analytics: Mission and Recent Conference

03:25 Challenges and Growth of Women In Analytics

10:43 Transitioning to AlignAI: Motivation and Journey

16:38 Skills and Lessons from Nonprofit to For-Profit

19:07 Intentionality and Unique Positioning in Business

Guest:

Rehgan Avon is the Co-Founder and CEO of AlignAI, a company focused on developing tools and strategies to help organizations effectively implement AI and data-driven initiatives. With a background in industrial engineering and a passion for advancing AI education, Rehgan has a strong track record in the tech industry, including founding Women in Analytics, a nonprofit dedicated to increasing visibility and opportunities for women in data science and AI. She is a recognized leader in AI, analytics, and education.

https://www.linkedin.com/in/rehganavon/

https://www.womeninanalytics.com/

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Thank you so much for checking out this episode of The Tech Trek. We would appreciate it if you would take a minute to rate and review us on your favorite podcast player.

Want to learn more about us? Head over at https://www.elevano.com

Have questions or want to cover specific topics with our future guests?

Please message me at https://www.linkedin.com/in/amirbormand (Amir Bormand)

In this episode, Amir sits down with Eli Wachs, Co-Founder and CEO of Footprint, to dive into the real-world challenges of building a startup with long-term intent. From resisting the hype of building fast to making strategic bets with limited data, Eli breaks down how he and his co-founder crafted a one-year roadmap, how they reassessed it, and how they make calls about what comes next. If you're a founder, product leader, or builder navigating roadmap trade-offs, this one’s for you.

🧠 Key Takeaways:

Founding with purpose > founding for hype: Eli challenges the "build fast" startup mentality and advocates for building when the problem is truly worth solving.

One-year clarity: Footprint launched with a tightly scoped one-year plan that drove team formation and product focus.

Betting on the unknown: Not every decision is backed by data—some are smart bets that may take months (or years) to pay off.

Choosing the right customers: Not every early user is a good design partner. Pick customers that will co-build with you, not just use your product.

Diverging co-founder visions can be an asset: Differing long-term views, when managed well, can surface better strategic outcomes.

💬 Quote:

"Entrepreneurs don’t have diversified portfolios. So if you're starting a company, you better be damn sure the problem is worth a decade of your life."

⏱️ Timestamped Highlights:

[00:01:00] Footprint explained: “Stripe for identity”—a modern take on KYC and secure onboarding.

[00:03:00] Why Eli pushed back on the “smart people should start companies” narrative.

[00:05:00] Launching with a clear one-year product roadmap—and why it mattered.

[00:07:00] Building around the founding team’s strengths and sequencing product development accordingly.

[00:09:00] The two big product bets they made—and how one took a year to pay off.

[00:13:00] The emotional and mental weight of making roadmap decisions under uncertainty.

[00:15:00] Why early customers should be intentional picks, not just any logo.

[00:17:00] Finding signal for long-term product ideas through prospect conversations.

[00:20:00] Whiteboard moment: when a co-founder’s product pitch finally clicked and redirected priorities.

[00:22:00] How to evaluate what you're uniquely positioned to build (and what to leave alone).

[00:23:00] Eli's contact info and his open-door policy for helping other builders.

🔗 Connect with Eli:

🐦 X: @EliWachs

💼 LinkedIn: https://www.linkedin.com/in/eliwachs/

In this episode, we dive into the evolution of XOps with Jai Prakash, exploring how a 100-year-old company like Pella Corporation is leveraging DataOps, MLOps, and AI to drive manufacturing innovation. Jai shares how Pella is integrating advanced analytics and AI-driven processes into their operations, creating efficiencies in assembly lines, data management, and workforce upskilling.

Whether you're in tech, manufacturing, or data engineering, this episode offers key insights into digital transformation, automation, and upskilling teams for the future.

🔑 Key Takeaways

Innovation in Legacy Industries: Even a century-old company like Pella is disrupting its own processes with AI, automation, and XOps.

XOps is More Than Just DevOps: Moving from DataOps to MLOps to AIOps is a structured, multi-year process that requires cultural and technical shifts.

AI in Manufacturing: From sensor-based quality control to AI-driven assembly line training, technology is reshaping how products are built.

Upskilling is Key: As automation increases, companies must train employees for future tech roles rather than just hiring externally.

Building a Center of Excellence: A shared services model helps streamline data operations and governance, ensuring efficient implementation of AI and analytics.

🕒 Timestamped Highlights

⏳ [00:00] – Introduction to Jai Prakash and Pella Corporation

⏳ [01:30] – Why does a window manufacturer need XOps?

⏳ [04:00] – How AI and analytics improve manufacturing efficiency

⏳ [08:30] – The risk of disruption: Learning from Tesla and other industries

⏳ [10:00] – Pella’s XOps journey: From DevOps to AI-driven operations

⏳ [12:00] – The role of DataOps in managing multi-modal manufacturing data

⏳ [15:00] – Upskilling employees for the future of AI and automation

⏳ [18:00] – The challenge of implementing innovation in a legacy company

⏳ [20:00] – Where Pella’s XOps strategy is headed in the next 3-5 years

💡 Quote from the Episode

"We want everyone to be an ambassador of the art of possible. Upskilling is not just an option—it’s a necessity for companies to stay ahead." – Jai Prakash

🔗 Connect with Jai Prakash

💼 LinkedIn: Jai Prakash on LinkedIn: https://www.linkedin.com/in/jaiprakashd/

📢 Enjoyed the episode? Don’t forget to like, subscribe, and leave a comment!

In this episode, Amir Bormand chats with Sarah Guidry, Head of Analytics and Data Science at LendingTree, about the intricacies of organizing work in data science. They explore frameworks for structuring work, stakeholder expectations, balancing quick wins with long-term goals, and how data teams can create space for innovation while delivering high-value results. If you’ve ever struggled with project prioritization, stakeholder buy-in, or maintaining agility in an ever-evolving data landscape, this episode is a must-listen.

Key Takeaways:

• Start with the End in Mind: Planning ahead ensures work is structured effectively and aligns with business needs.

• Stakeholder Alignment is Critical: Managing expectations and keeping stakeholders engaged prevents them from going rogue with their own makeshift solutions.

• Empower Business Users: Giving stakeholders access to structured, small data enables them to answer straightforward questions independently.

• Iterative Delivery Builds Trust: Regular updates help prevent surprises and align data insights with business needs in real-time.

• Don’t Plan to 100% Capacity: Leaving buffer time allows teams to handle ad-hoc requests without disrupting long-term priorities.

• R&D is Vital for Innovation: Dedicated time for exploration—like "Focus Fridays" and hackathons—fuels creativity and keeps the team ahead of the curve.

• Prioritization Frameworks Work: Implementing a "Must Do / Should Do" list creates clarity and helps balance workload distribution.

Timestamped Highlights:

• [00:00:00] Introduction to Sarah Guidry and LendingTree’s role in financial services.

• [00:02:00] What does it mean to organize work in data science?

• [00:04:00] The challenge of stakeholder expectations and delivering value.

• [00:06:00] The evolution of business intelligence and enabling self-service for stakeholders.

• [00:08:00] Why analytics is like investigative journalism—constant iteration is key.

• [00:10:00] Setting expectations upfront to buy time and align priorities.

• [00:12:00] Balancing speed with sustainability—delivering quick wins without technical debt.

• [00:15:00] Avoiding surprises—how to maintain proactive communication with stakeholders.

• [00:18:00] Managing work effectively through prioritization meetings.

• [00:20:00] Creating space for R&D: Focus Fridays, hackathons, and experimentation.

• [00:23:00] Using a “Must Do / Should Do” framework for clear prioritization.

• [00:24:00] How Sarah's team integrates learning and innovation into their workflow.

• [00:25:00] Closing thoughts and where to reach Sarah Guidry for further discussion.

Quote of the Episode:

"Analytics is investigative journalism—you don’t always know what you’re looking for, but through exploration and iteration, you uncover the most valuable insights." – Sarah Guidry

Connect with Sarah Guidry:

📩 LinkedIn: Sarah Guidry

💡 Enjoyed the episode?

📢 Share it with a colleague who might find it valuable!🎧 Subscribe, leave a review, and let us know your thoughts.

In this episode, Amir chats with Samir Kumar, Co-Founder and General Partner at Touring Capital, about platform shifts in technology and the role of AI in future advancements. Samir shares Touring Capital’s investment philosophy, focusing on series B investments in software-centric companies. He discusses the competitive dynamics between startups and tech giants in the AI space, challenges and opportunities in building AI-driven business models, and the future impact of technologies like the metaverse and blockchain.

Highlights:

- 02:53 Platform Shifts in Technology

- 06:22 AI and the Role of Incumbents

- 10:30 Opportunities and Challenges for Startups

- 18:34 Narrow Focus and Industry-Specific AI

- 25:06 Outcome-Based Pricing and Monetization

Guest:

Samir Kumar is co-founder and General Partner at Touring Capital. Before co-founding Touring, Samir was a Managing Partner at M12 (Microsoft’s Venture Fund), where he led investment activities in horizontal/vertical AI, deep tech, and hardware-enabled software companies. Samir’s notable investments include Applied Intuition, Psi Quantum, Wandelbots, Syntiant, D-Matrix, Regrow, and Netradyne. Samir previously held senior product and strategic business development roles at Qualcomm, Samsung, and Microsoft. He developed a strong passion for AI after delving deep into neural networks a decade ago; this ultimately paved the way for him to become a venture investor. Samir is a graduate of Cornell University.

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

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Thank you so much for checking out this episode of The Tech Trek. We would appreciate it if you would take a minute to rate and review us on your favorite podcast player.

Want to learn more about us? Head over at https://www.elevano.com

Have questions or want to cover specific topics with our future guests?

Please message me at https://www.linkedin.com/in/amirbormand (Amir Bormand)

In this episode, Amir sits down with Sergei Azernikov to discuss how AI and generative AI (GenAI) are transforming the dental industry. Glidewell Dental, a leader in dental lab products, has been at the forefront of AI innovation—leveraging advanced machine learning models to automate design, improve precision, and reduce dental restoration times from weeks to mere hours. Sergei shares how technology has revolutionized not just the manufacturing process but also patient experiences, business efficiency, and the future of dentistry.

Key Takeaways:

AI’s Unexpected Role in Dentistry – From manual craftsmanship to AI-driven automation, the dental industry has undergone a massive shift.

How Generative AI is Reshaping Dental Restoration – Glidewell Dental uses GANs (Generative Adversarial Networks) to create perfectly fitting crowns and implants with minimal human intervention.

From 2 Weeks to 2 Hours – AI-powered digital scanning and cloud-based design enable same-day dental restorations, eliminating long wait times.

The Cloud as a Game-Changer – AWS and cloud computing enable rapid AI model training, seamless data storage, and scalable machine learning applications.

AI’s Business Impact – AI has tripled production efficiency, allowing Glidewell Dental to scale without increasing workforce size.

Timestamped Highlights:

[00:01:00] - Introducing Sergei Azernikov & Glidewell Dental

[00:03:00] - The early adoption of AI in dentistry—why it made sense

[00:05:00] - AI vs. human technicians: A competition in identifying teeth

[00:07:00] - How Glidewell’s generative AI models automate crown design

[00:10:00] - The digital transformation of dental care: Faster, better-fitting restorations

[00:14:00] - Overcoming data challenges: Storing and structuring 3D dental scans for AI training

[00:18:00] - How cloud computing (AWS) supercharged AI adoption

[00:20:00] - AI’s impact on business: 3X increase in efficiency

[00:22:00] - AI innovation beyond dentistry—what other industries can learn

Quote from the Episode:

"We electrified it, now we’re going to cognize it. AI isn’t just about automation—it’s about introducing intelligence into digital processes to make dentistry smarter, faster, and better for patients." – Sergei Azernikov

Connect with Sergei Azernikov:

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

Enjoyed the episode?

Don’t forget to like, subscribe, and share this episode with someone exploring AI applications in their industry! Drop your thoughts in the comments and let us know what you’d like to hear next.

Beth Falder, AVP of Data Management and Analytics at Nuvance Health, joins Amir to unpack a challenge every tech leader is facing right now: how to stay grounded while everything around you accelerates. From navigating the hype around GenAI to dealing with the slow, foundational work of governance and data cleanup, Beth shares how she chooses where to place bets—and what to ignore. This episode is especially valuable for anyone in tech or data leadership trying to make smart decisions amid pressure, noise, and FOMO.

What You’ll Learn

Why governance isn’t a slowdown—it’s a survival tactic

How to prioritize technical investments when vendors are flooding your inbox

What data debt looks like in healthcare, and why it's finally being addressed

Where GenAI adds real value now—and where it's still too risky

Why low-risk back office use cases are the best starting point in healthcare

Conversation Highlights

[02:10] GenAI meets governance: why clinicians are excited—and why Beth is cautious

[05:45] Vendor noise is deafening: how to stay focused when everyone’s pitching magic

[08:15] “Data debt” is real: why poor structuring from years ago is now haunting teams

[14:05] Budgeting in the age of AI: how to plan for a future that changes monthly

[17:15] The clinical vs. back office dilemma: where GenAI should not go (yet)

[20:30] Real opportunities in clinical notes—and how big cloud providers are helping

Quote of the Episode

“It’s exciting. It’s great to see this much engagement. I haven’t been this important for a while. But we can’t do it all. That’s the frustrating part of the whole conversation.”

Pro Tips from Beth

Start with governance—it builds the credibility needed to push forward new initiatives

Focus on tools or platforms that solve multiple problems across departments

Leverage vendor innovation selectively, especially when tackling data technical debt

Don’t underestimate the value of peer networks in understanding the shifting AI landscape

Choose GenAI use cases with patient safety in mind—back office is the best launchpad

Enjoyed this episode?

Subscribe to the show and share it with someone leading data or AI strategy in healthcare. And if you’ve got a favorite GenAI use case—or a cautionary tale—drop us a note or find Amir on LinkedIn.

In this episode, Amir talks with Nathan Fabian, Managing Director and Head of Talent at WestCap, about the essential qualities of great leaders. They explore the complexities of hiring leadership, assessing unique attributes, and balancing speed with thoroughness in the recruitment process. Nathan shares WestCap's approach, focusing on five key attributes—principles, curiosity, decisiveness, team management, and vision—that predict leadership success. They also discuss culture fit, leveraging networks, and building and retaining a diverse, high-performing leadership team.

Highlights:

Nathan's LinkedIn: https://www.linkedin.com/in/nathanfabian/

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Thank you so much for checking out this episode of The Tech Trek. We would appreciate it if you would take a minute to rate and review us on your favorite podcast player.

Want to learn more about us? Head over at https://www.elevano.com

Have questions or want to cover specific topics with our future guests?

Please message me at https://www.linkedin.com/in/amirbormand (Amir Bormand)