Afleveringen
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In this episode of The Tech Trek, Amir sits down with Abhi Sharma, CEO and Co-Founder of Relyance AI, to unpack the philosophy of "unreasonable hospitality"—a framework for building unforgettable customer and team experiences. From small gestures like a humidifier in the interview room to culture-embedded rituals, Abhi reveals how this principle fuels trust, retention, and performance at every level. If you're building teams or scaling a company, this one is packed with actionable insights.
🔑 Key Takeaways:
Unreasonable hospitality = memorable + maximizing + mentionable. It’s not about going the extra mile—it’s about doing the unexpected in personal, meaningful ways.
Small gestures can drive huge impact. Whether winning deals or recruiting talent, personalized touches create emotional connections that close the loop.
Culture is built through consistent rituals. From Slack channels to awards like “Golden Lion,” Reliance AI embeds their values in routines.
Founders must lead from the front. Embodying cultural values in visible, everyday ways—like flying out for a candidate interview—sets the tone company-wide.
⏱️ Timestamped Highlights:
[01:21] — Defining “unreasonable hospitality” with the 3 M’s: maximizing, memorable, mentionable.
[05:19] — A personalized video tip wins a competitive deal.
[07:40] — A $30 humidifier makes an outsized impact in the interview process.
[09:45] — The 4-part framework to embed hospitality into company culture: Rituals, Empowerment, Feedback, Storytelling.
[14:15] — Balancing perfectionism and personalization in culture values.
[18:27] — Recruiting a new dad: flying in instead of flying him out shows care and commitment.
[21:00] — Why the small stuff carries culture and why consistency matters as a company grows.
💬 Quote to Share:
“If everything gets commoditized and we’re living in the fancy AI world... then the only thing that’s actually going to matter is the element of service—the human touch.” — Abhi Sharma
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In this episode of The Tech Trek, Amir sits down with Sasha Gainullin, CEO of Battleface, to explore how focusing on a small, underserved niche in the travel insurance industry unlocked global opportunity. Sasha shares how Battleface used in-house technology to revolutionize the outdated travel insurance model, expanding from serving adventure travelers to powering major partners through their service platform, Robin Assist. This is a conversation about focus, customer empathy, and tech-driven disruption—valuable for any founder or product leader.
🔑 Key Takeaways
Start Small, Win Big: Battleface began by solving a single problem for niche adventure travelers. That focused approach laid the foundation for global scale.
Tech as a Differentiator: Building the entire platform in-house enabled real-time risk pricing, scalable customization, and operational agility.
Customer Connection Wins: Even as CEO, Sasha remains hands-on with customer service to ensure product relevance—an often-missing link in insurance innovation.
From Product to Platform: The launch of Robin Assist extended Battleface’s reach, now powering services for other travel insurance providers worldwide.
⏱️ Timestamped Highlights
00:49 – What is Battleface? A travel insurance company that customizes micro-products using tech.
02:23 – Why they focused on one underserved segment: journalists, surfers, adventure travelers.
05:35 – The pricing problem solved with real-time tech under Lloyd’s of London guidance.
09:48 – How building in-house tech enabled flexibility, scalability, and global compliance.
12:08 – Competitive advantage: fast iteration, informed by decades of industry experience.
14:33 – GenAI isn't a threat—it's a tool. The focus is on solving customer problems, not chasing trends.
18:54 – How the pandemic revealed broader market applicability and led to Robin Assist.
24:05 – Distribution cost challenges and exposing why traditional insurance often fails customers.
26:07 – Partner insights: why offering relevant, flexible insurance products is the future.
💬 Quote Worth Sharing
"Technology is just a feature. If you lose that touch with the customer, you’ll stumble—and that’s what’s happening in travel insurance today." — Sasha Gainullin
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Zijn er afleveringen die ontbreken?
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In this episode, Amir Bormand sits down with Tony Speller, Division SVP of Technical Operations and Engineering at Comcast, to explore how AI is quietly but powerfully transforming the customer and employee experience at one of the world’s largest media and technology companies. From self-healing network devices to predictive outage detection, Tony walks us through Comcast’s internal innovation playbook—blending in-house AI solutions with strategic partnerships. Whether you’re a technologist, operator, or just someone who's ever rebooted a modem, this episode peels back the curtain on what keeps the digital world running.
🔑 Key Takeaways
AI at Scale: Comcast uses AI to manage over 50 million modems with technologies like Octave, optimizing performance and preventing issues before they affect customers.
Self-Healing Networks: With tools like virtualized CMTS, the network can perform 300,000+ upgrades autonomously, solving issues before customers notice.
Field Tech Empowerment: AI tools like RoC and fiber telemetry empower technicians to locate problems faster, saving time and reducing downtime.
Innovation Culture: Comcast builds many AI solutions internally, while also integrating partner technologies for field operations and advanced routing.
Celebrating the Unsung Heroes: Tony highlights the importance of daily team syncs that recognize not only fast fixes, but also problems prevented—a culture of proactive excellence.
⏱ Timestamped Highlights
01:45 – Defining Tony’s role and Comcast’s AI priorities
03:00 – AI for teammates vs. AI for customers
04:12 – How Octave optimizes 50M+ modems with 4,000 data points
05:30 – Virtualized CMTS: Self-healing, automation, and 300K+ autonomous changes
08:20 – Empowering field techs with RoC and fiber telemetry for precise outage detection
11:00 – The rigorous lab-to-field AI testing process
13:44 – Build vs. buy: Comcast’s hybrid innovation model
15:33 – Roadmap pillars: network automation, teammate tools, and customer simplicity
18:24 – The impact of streaming and how it drives network innovation
21:34 – How Tony celebrates behind-the-scenes teams daily
💬 Featured Quote
"We're not just celebrating the fixes—we're celebrating the problems that never happened because of the technology our teams built. That's how we show them their work matters."
Connecting with Comcast: You can keep up with all the innovations and surround sound moments from Comcast’s Center of Excellence by visiting South.Comcast.com.
More about Tony:
Tony Speller is the Senior Vice President of Technical Operations and Engineering at Comcast’s Central Division headquarters in Atlanta. Tony started his long and successful career as a technician for Tele-Communications, Inc. (TCI) in 1989. He has nearly 35 years of industry experience, holding numerous leadership roles across Comcast, including key positions in Pennsylvania, Boston, Western New England, and Houston. Named a “Cable TV Pioneer” in 2018 by the SCTE, Tony has been heavily involved in several charitable organizations, including the United Way, the Urban League, and the Greater Houston Partnership. His work has been recognized with the Urban League of Greater Hartford’s Community Service Award, with the NAMIC Luminary Award, and most recently with the NAMIC Diversity in Technology Award in 2024.
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In this episode, Amir sits down with Nirman Dave, co-founder and CEO of Zams, an enterprise AI platform built to help businesses design and deploy AI agents with ease. They dive into Nirman's founding story—launching during the pandemic, navigating the evolution of the AI ecosystem, and the unique challenges of maintaining customer focus amid shifting trends and rising competition. Nirman also shares lessons from pitching investors, building trust with customers, and the art of product prioritization.
📌 Key Takeaways
Differentiation Through UX: Zams is not just another AI tool—it aims to be the browser for AI, giving enterprises a seamless UI to work with agents.
Customer Over Competition: Success has come from solving real business problems—not chasing trends or investor hype.
Trust Through Design: A 30-second loading delay helped build trust in Zams’ lightning-fast models, proving psychology matters in UX.
Resilient Startup Strategy: Focusing on sustainable growth and user love—not vanity metrics—is what keeps investors coming back.
🕒 Timestamped Highlights
00:40 – What Zams does and how it’s helping enterprises with AI agents
02:14 – Starting a business in college during the pandemic
04:21 – Evolution of AI from AutoML to LLMs and product-market fit
07:15 – Staying customer-centric as terminology and trends change
09:43 – Manufacturing case study: 20 hours/day saved with AI agents
12:25 – Why the “browser moment” for AI is coming
14:33 – Balancing roadmap flexibility with intentional focus
17:34 – Fundraising lessons: sustainable growth beats glamor
24:08 – Listening to customers—but not too literally
26:11 – The 30-second delay that changed customer perception
💬 Memorable Quote
“At the end of the day, businesses care about three things—saving time, saving money, or making money. Everything else is noise.”
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In this episode of The Tech Trek, I sit down with Artem Rodichev, Founder & CEO of Ex-Human, to explore the emerging world of empathetic generative AI. We discuss how today’s LLMs fall short on emotional intelligence and how Ex-Human is building AI that can emotionally connect with users. Artem shares the vision behind their product Botify AI, its real-world applications—from gaming and education to mental health—and the crucial role of guardrails in ensuring safe, ethical AI development.
🔑 Key Takeaways
Current LLMs lack emotional depth. They're designed to solve tasks quickly, not to engage in human-like, emotionally resonant conversations.
Empathetic AI can reduce loneliness. These systems aim to connect with users on an emotional level and offer meaningful companionship.
Real use cases span industries. From gaming and language learning to mental health support and education, empathetic AI has broad applications.
Data-driven improvement. Wattify AI learns through millions of conversations and user feedback, fine-tuning its responses for empathy and memory.
Safety is a must. As AI gets more emotionally intelligent, strong ethical guardrails are essential to prevent misuse.
🕒 Timestamped Highlights
00:34 – What is X-Human? Creating customizable, emotionally intelligent AI characters
02:05 – Why current LLMs feel robotic (task vs. engagement-driven design)
04:38 – Defining “empathetic AI” and how it’s different from classic chatbots
06:06 – Use case: Solving loneliness and building emotional connections
07:50 – Applications in gaming, Discord bots, and immersive NPC experiences
09:40 – Language learning via informal practice with emotionally aware AI
10:50 – Supporting mental health by providing judgment-free companionship
12:25 – How Wattify AI gathers and uses data for emotional accuracy and memory
16:10 – Technical details: short-term vs long-term memory, voice & visual integration
19:23 – The importance of safety, ethics, and guardrails in emotionally intelligent AI
23:06 – The broader opportunity in education, tutoring, and emotional engagement
23:57 – Where to try Wattify AI and connect with Artem
💬 Featured Quote
"Empathetic AI companions don’t just respond—they remember, support, and emotionally connect. That’s what makes them powerful and personal." – Artem Rodichev
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What does it mean to find out what your team is actually good at—and how do you use that insight to grow, scale, and lead effectively?
In this episode, Amir sits down with Pallavi Pal, Head of Product at Grata, to unpack the nuanced art of identifying strengths within product teams. From hiring with purpose to fostering technical and soft skills, Pallavi shares how she built her team from the ground up and established a culture of collaboration and excellence. Whether you’re a product leader, aspiring manager, or simply navigating your growth path in tech, this conversation is packed with frameworks and hard-earned lessons.
✨ Key Takeaways
“Good” is personal and team-specific – Recognize where individual team members naturally lean in and where they need support.
Hiring with intention matters – Building a team from scratch allows leaders to define what “good” looks like for each role early on.
Balancing technical and soft skills is crucial – Successful PMs don’t just understand the product—they empathize with users and collaborate effectively.
Path to people management starts with mentorship – Use mentorship as a low-risk way to identify potential managers.
Culture isn’t just top-down – Product teams should reflect company values while fostering technical curiosity and peer collaboration.
Metrics can’t be mandated – Teams need to co-create their North Star metrics and OKRs to stay engaged and aligned.
⏱️ Timestamped Highlights
[00:20] – Introducing Pallavi and the focus on identifying what your team is great at
[02:05] – Observing behaviors to identify strengths and hesitations
[05:22] – Hiring to match specific skill sets across different product functions
[08:20] – The balance between domain knowledge, technical skills, and soft skills
[12:03] – Identifying future people managers within your team
[16:21] – Building a product culture that aligns with company values but has its own identity
[21:06] – How to define and align around standards and metrics in product
[24:21] – How to connect with Pallavi for follow-up questions
💬 Quote of the Episode
“It’s a lot more art than science. Good is seeing where people lean in—what excites them—and building the team to amplify that.”
– Pallavi Pal
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In this episode, Amir sits down with Zach Barney, Co-founder and CEO of Mobly, the system of record for event marketers. Zach’s story takes us from his early ambitions of joining the NSA to a career-altering injury, a serendipitous fall into sales, and eventually the founding of Mobly. This episode explores not only the career pivots that led Zach to entrepreneurship, but also the mental, financial, and strategic challenges he faced along the way.
If you’ve ever thought about switching paths or launching your own thing — especially from a non-technical background — Zach’s journey is proof that drive, vision, and grit can get you there.
🔑 Key Takeaways:
Pivot Points Can Define You: A severe knee injury and life changes redirected Zach’s path from NSA hopeful to tech founder.
Sales is Entrepreneurship Training: Zach views sales as the most entrepreneurial job short of being a founder — giving him the skills and mindset for startup life.
Solve Real Problems: Mobly was born from Zach’s own pain points in the field — and customer validation made the case.
Execution Over Everything: Despite the harsh fundraising climate, Mobly thrived by focusing on product and market fit.
Founding Doesn’t Require Code: Zach’s non-technical background didn’t stop him — and his story encourages others in the same boat.
⏱️ Timestamped Highlights:
00:20 – Intro to Zach Barney and Mobly — from spreadsheets to sales tech for event marketers.
01:50 – Zach’s drive to control his financial destiny, inspired by his upbringing as the oldest of 8.
03:23 – The “spy-to-startup” journey: NSA offer, Russian fluency, and a career-altering knee injury.
06:15 – How a devastating injury forced Zach to pivot, finding a sales job that set the foundation for his future.
08:29 – Falling in love with sales: the accidental career path that turned into a calling.
10:20 – Constant learning: how podcasts, books, and early-stage exposure prepared him for founding.
12:07 – Making the leap: risks, fears, and financial tradeoffs of starting Mobly with five kids to support.
14:07 – Co-founder chemistry: 30 years of friendship becomes a business partnership
16:20 – Building the MVP without a CTO and the power of scrappy execution.
17:48 – Navigating the economic downturn and fundraising panic attacks in a tough VC market.
20:12 – Why Zach is bullish on execution over economic prediction — and how Mobly is thriving.
💬 Quote to Share:
“Sales is the most entrepreneurial job you can have without being an entrepreneur.” – Zach Barney
🔗 Connect with Zach:
📱 Find him on LinkedIn (just don’t automate your message — he can sniff it out instantly!)
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Join us in this insightful conversation with Eric Valasek as we explore the crucial relationship between CEOs, product teams, and engineering leaders. Eric shares his expertise on managing prioritization, strategic tech debt, and ensuring engineering teams stay focused and insulated amidst business dynamics.
Key Takeaways:
Balance is Crucial: A company's success depends heavily on balancing business goals, product demands, and engineering capabilities.
Strategic Tech Debt: Not all tech debt is harmful. Strategic tech debt can accelerate business growth, but must be managed and planned carefully.
Upskilling for Growth: Investing in your team's skill development can pay long-term dividends, especially when tackling new technology domains.
Transparency vs. Focus: Protecting your team from constant business shifts ("horse trading") is essential to maintain productivity and morale.
Engineering's Voice: In tech-driven companies, the engineering team often carries significant influence. Leaders must balance innovation with practical business outcomes.
Timestamped Highlights:
00:41 - Eric's introduction and overview of engineering-product-business relationships.
01:30 - Balancing the business, product, and engineering "trifecta."
05:01 - Effective strategies for team skill development and training.
07:26 - Adjusting team velocity and maintaining quality during upskilling.
09:44 - Navigating potential dips in quality when adopting new technologies.
11:57 - Strategic considerations when intentionally incurring tech debt.
14:31 - Managing transparency and team insulation from business volatility.
17:40 - The importance and impact of engineering's voice in technology-centric businesses.
Quote:
"You can't have speed and quality with the same size team with new technologies. You need to plan that development cycle carefully—some trade-offs are necessary."
— Eric Valasek, Engineering Leader
Connect with Eric: https://www.linkedin.com/in/evalasek/
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In this episode of The Tech Trek, Amir Bormand sits down with Shang Wang, Co-founder and CTO of CentML, to explore the dynamic landscape of open source AI technologies and how enterprises are rapidly adapting to this growing ecosystem. Shang offers expert insights into why open source solutions are becoming essential in AI development, the advantages in security and privacy, and how CentML strategically contributes to this evolution.
🌟 Key Takeaways:
Open Source Dominance in AI: Open-source technologies have become foundational to AI development, promoting innovation, transparency, and faster problem-solving.
Enterprise Adoption Shift: Enterprises are increasingly embracing open source solutions in AI, driven by the need for greater transparency, data privacy, and community-driven innovation.
CentML’s Impact: CentML leverages open source through developing tools and infrastructure that optimize AI model deployment, training, and performance at scale.
Security and Privacy Advantages: Open-source AI solutions provide enterprises with enhanced control over data privacy and security, challenging traditional assumptions that closed-source means more secure.
💬 Notable Quote:
"Open source gives you more control. If there’s a security flaw, you can fix it. If there’s a privacy issue, you can build safeguards. Closed source leaves you hoping nothing goes wrong.” – Shang Wang
⏰ Timestamped Highlights:
00:00: Introduction to Shang Wang and CentML
01:28: Origins of open source AI in academia
03:30: Differences in developing with open vs. closed-source solutions
05:10: Impact of open-source tools on talent development and recruitment
07:16: Predictions on the future of open-source AI
10:05: Deep dive into CentML’s tools and open-source integrations
19:46: Real-world applications of CentML, exemplified through banking
22:57: Addressing misconceptions about open source security
27:42: How to connect with Shang Wang
📞 Connect with Shang Wang:
LinkedIn: https://www.linkedin.com/in/shang-sam-wang-52851489
🎙️ Subscribe, Rate, and Review: Let us know your thoughts and stay updated with future episodes of The Tech Trek!
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In this episode of The Tech Trek, Amir sits down with Andrew Levy, CEO and Co-founder of AirCover.ai, to explore how agentic AI is transforming the sales landscape. Andrew shares how AirCover builds real-time digital assistants that empower sales teams, the role of humans in AI-driven workflows, and how enterprises—both nimble and traditional—are adopting these tools to leap ahead. From change management to trust-building and the rise of “little language models,” this conversation unpacks what it really means to bring AI into the heart of go-to-market strategies.
🔑 Key Takeaways
1. Real-Time AI for Real-World Sales AirCover.ai builds AI agents that operate in real time alongside sales reps, surfacing the right information at the right moment, and helping teams scale more effectively with digital counterparts.
2. Scaling Expertise, Not Replacing Teams Rather than replacing humans, agentic AI amplifies expertise—like turning one sales engineer into six through virtual counterparts, unlocking growth, not cuts.
3. Human-in-the-Loop Is the Bridge Especially in regulated industries, “human-in-the-loop” AI design helps companies automate workflows while maintaining control, transparency, and trust.
4. Model Confidence Matters for Adoption Andrew emphasizes trust-building in AI by surfacing high-confidence data and leveraging behavior signals to continually improve user experience and relevance.
5. Little Language Models Are the Future Expect a shift from massive models to specialized ones—“little language models”—tailored per team or even per individual, making AI more personalized and effective.
⏱️ Timestamped Highlights
00:00 – Meet Andrew Levy
Intro to Andrew and AirCover.ai – building digital agents for live sales calls.
02:21 – The Origin of AirCover
Andrew shares the story behind the idea, influenced by challenges scaling sales enablement at VMware.
06:50 – Spotting the Market Gap
When tech and market timing intersect: how AI-native thinking unlocked new possibilities.
08:53 – Change Management From Day One
Why ease of use and seamless workflow integration were key in early product design.
11:26 – Enterprise AI Adoption Trends
Big companies are leapfrogging past previous tech gaps by going all-in on AI.
13:55 – AI as an Extension, Not a Replacement
How AI fills capability gaps without threatening job loss—and why that’s a key adoption driver.
16:47 – Agentic Workflows in Action
Examples of tasks AI handles autonomously vs. where human oversight is essential.
20:07 – Confidence, Trust, and Adoption
Andrew talks about how AirCover builds trust through transparency, high-confidence responses, and adaptive learning signals.
22:34 – The Shift to Smaller, Smarter Models
A peek into the near future of AI: narrow, task-specific models that are ultra-personalized.
23:24 – Final Thoughts & How to Connect
Andrew’s contact info and closing takeaways from Amir.
💬 Featured Quote
“This isn't about replacing your team with AI—it's about giving them superpowers. Imagine taking your best solution engineer and scaling their expertise across your entire team.”
— Andrew Levy, CEO of AirCover.ai
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Guest: Viraj Narayanan, CEO of Cornerstone AI
🔑 Key Takeaways
Healthcare data is messy by default. It's generated by countless sources with different standards—think EMRs, Apple Watches, and pharmacy systems—making research data fragmented and hard to use.
AI can clean up the mess. Cornerstone AI applies automation to standardize and improve the fidelity of clinical research data, significantly cutting down manual effort.
Productivity > Replacement. Rather than replacing jobs, AI is helping PhDs and data scientists focus on higher-value tasks, enabling more research and faster discovery.
Standardization is foundational. Without clean, consistent data, the insights drawn—even with AI—are limited or flawed.
Trust is earned. The biggest mindset shift is seeing your own messy data cleaned instantly by AI, not a polished demo set.
Patients win too. Cleaner, faster data means more reliable research, potentially more personalized medicine, and better access to understandable information.
💬 Quote of the Episode
“We’re going to look back in 10 years and think—‘I can’t believe we had PhDs doing that kind of manual data work.’”
— Viraj Narayanan
⏱ Timestamped Highlights
00:00 – Intro to Viraj and Cornerstone AI: Automating healthcare data quality
01:54 – The "plumbing problem" of healthcare data and what no one thinks about
04:48 – Why AI in healthcare often starts with admin—not research
05:35 – Steph Curry and SNOMED: How basketball shows us the need for standardization
08:58 – Wild West of research data: From 2% lift to 40%+ with AI
11:41 – Why research is built on redundancy and how AI rewires the model
14:43 – Change management: From trust to technical buy-in to leadership alignment
18:42 – Will AI take jobs? No—but it will transform what we do with talent
21:03 – What patients will see: Cleaner, faster, more understandable data
23:49 – Where to reach Viraj and final thoughts
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On this episode of The Tech Trek, we're diving deep into the intersection of engineering, product, and business thinking with Vineet Goel — Co-Founder and Chief Product & Technology Officer at Parafin, a fast-growing fintech startup powering small businesses on platforms like DoorDash, Amazon, and Walmart.
We unpack what it really means to build a company where engineers are product thinkers, why bringing in product managers too early can backfire, and how AI is reshaping what it means to write code — and who’s best positioned to thrive in this new world.
Vineet shares how Parafin scaled with just two PMs to 25 engineers, why every engineer shadows customer support calls, and how GenAI might collapse the wall between product and engineering entirely.
Whether you're an engineer, product leader, founder, or just curious where the future of tech orgs is headed — this conversation is packed with insights you won’t want to miss.
🧠 Key Takeaways
Don’t hire PMs too early. Founders should own product-market fit before bringing on a product leader.
Engineers need a business mindset. At Parafin, engineers are ruthlessly customer-focused — many even shadow support calls.
GenAI will change everything. Writing code is becoming a commodity. Future engineers will need to blend product and technical skills.
The product org evolves with scale. Vineet shares when and why Parafin added a Head of Product, and how it shifted org dynamics.
PMs should create leverage, not just roadmaps. When engineers are stretched thin, PMs help teams stay focused and effective.
⏱️ Timestamped Highlights
00:46 – What is Parafin?
A fintech startup empowering small businesses on platforms like Amazon and DoorDash with embedded financial services.
02:35 – Org Design at Parafin
Why they built a structure that’s neither product- nor engineering-led, but customer-obsessed.
05:09 – 25 Engineers, 2 PMs
How a product-minded engineering culture powers massive output and scale.
06:40 – Customer Empathy as Culture
Engineers shadow support calls—and sometimes ship fixes within the hour.
08:50 – When to Hire a Head of Product
What prompted the shift, and how it solved growing pains around complexity and speed.
11:59 – PMs Create Leverage
Bringing in PMs at the right time accelerates decision-making and keeps engineers focused.
14:28 – Dual Hat of CPTO
How Vineet balances strategy, execution, and organizational leadership.
16:34 – GenAI’s Impact on Engineers
Code is getting commoditized. Engineers must evolve—or risk becoming obsolete.
19:14 – What Happens to Product Roadmaps?
AI will speed up delivery—product teams need to dream further ahead, faster.
21:11 – The ‘Shift Left’ of Engineering
Engineers are moving closer to the business—Vineet predicts a product-tech hybrid role will dominate.
💬 Quote Worth Sharing
“Being product and business minded will become a necessity—not a nice to have. Code is becoming a commodity. The future belongs to those who can build and think.”
— Vineet Goel, CPTO at Parafin
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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.
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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
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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
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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.
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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
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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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