Afleveringen
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Wyatt Smith, CEO of UpSmith, joins Amir to unpack how agentic AI is transforming the skilled trades industry. From dispatch optimization to human-in-the-loop workflows, Wyatt shares a practical and visionary lens on how AI can solve deep productivity challenges, empower call centers, and proactively generate business opportunities. If you think AI only disrupts digital industries, this episode will make you think again.
🔑 Key Takeaways:
Agentic AI is unlocking productivity by automating repetitive coordination tasks—like technician dispatching—allowing humans to focus on higher-value interactions.
Skilled trades businesses already have rich data but need tools to surface and act on it proactively rather than reactively.
Selling AI into traditional industries requires proof points, tight business cases, and sensitivity to the human element.
AI augments, not replaces—freeing up people to do work they're best suited for, like nuanced customer engagement.
💬 Highlight Quote:
“Advances in technology automate tasks, not people… Machines do what they're best at so humans can do what they're best at.” – Wyatt Smith
⏱️ Timestamped Highlights:
00:38 – Intro to Wyatt Smith and UpSmith's mission in the skilled trades.
02:51 – Why dispatching the wrong tech to the wrong job is a billion-dollar coordination problem.
05:09 – The customer journey in home services—and where productivity breaks down.
08:54 – AI adoption challenges in the trades and how business owners evaluate new tech.
11:15 – Human-AI dynamics: skepticism, latency, and building trust with agentic systems.
13:49 – “AI creates more work”: how automation changes tasks, not headcount.
17:19 – How UpSmith trains agents like new hires with workflows and documentation.
20:31 – Personalization at scale: how agents remember details from 5 years ago.
23:20 – The future of call centers and human-in-the-loop automation.
25:49 – Wyatt’s contact info and closing reflections.
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What separates a successful founder from the rest? In this episode, Harish Abbott—CEO and co-founder of Augment—breaks down how he repeatedly spots opportunity early, builds products customers actually want, and navigates the fast-moving world of AI without falling into the trap of chasing every shiny benchmark.
We explore how Harish’s team shadowed 60 logistics operators before writing a single line of code, why storytelling is a founder's most underutilized superpower, and how to know when it’s time to pivot—even if everything looks good on the surface.
Whether you're scaling your first product or figuring out what not to build, this conversation is packed with real-world insights you can apply today.
🔑 Key Takeaways:
Start with Pain, Not Product: Successful startups begin by deeply understanding real customer pain points, not by jumping into code or chasing tech trends.
Shadowing Over Selling: Harish’s team shadowed 60 logistics operators in the early days of Augment—prioritizing observation over assumptions.
Strong Opinions, Loosely Held: Founders must balance confidence in their vision with humility to pivot when data points to a better path.
AI ≠ The Product: In a world obsessed with benchmarks, remember: AI is a tool. The actual value lies in making things better, cheaper, or faster for users.
⏱ Timestamped Highlights:
00:32 – What Augment does: AI teammates for the logistics industry
02:48 – “Follow one path consistently” – Harish’s approach to serial entrepreneurship
05:57 – The importance of shadowing operators before writing code
11:21 – When is it time to pivot? Why usage data is often more telling than top-line growth
19:23 – Storytelling as a founder’s core job: how to get employees, investors, and customers on board
25:02 – The challenge of AI startup building today: chasing stability over shiny new benchmarks
30:10 – Avoiding the trap of benchmark chasing in AI product development
💬 Quote:
“The best founders are always seeking truth. That truth sometimes tells you to let go of the idea you love.”
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Zijn er afleveringen die ontbreken?
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In this episode of The Tech Trek, Amir speaks with Patrick Leung, CTO of Faro Health, about what it takes to lead an engineering organization through a transformation to become an AI-first company. From redefining the product roadmap to managing cultural and technical shifts, Patrick shares practical insights on team structure, skill development, and delivering AI-enabled features in a regulated domain like clinical trials. This is a must-listen for tech leaders navigating similar transitions.
🧠 Key Takeaways:
AI-First ≠ Just Using AI
Being AI-first means deeply embedding AI into the core product architecture—not just bolting on an LLM. It requires strategy, structure, and long-term thinking.
Build the Right Team Early
The biggest shift for engineering orgs is in people—getting the right AI talent onboard early, rather than doing it all yourself, is critical for momentum.
Upskilling Is Real—but Selective
Not every engineer will pivot to AI, but there’s room for involvement across UX, product, and front-end roles. Cultural fit and willingness to contribute matter more than title.
Data Engineering is the Unsung Hero
Most AI work today isn’t in model building, but in crafting clean, structured datasets. Investment here pays off exponentially.
⏱️ Timestamped Highlights:
00:00 – What Does It Mean to Be AI-First?
Patrick defines the term and outlines Faro Health’s mission to reduce the cost and timeline of clinical trials.
04:13 – Defining the AI Strategy
How they started with clinical writing as the first application of LLMs and why it was harder than expected.
07:54 – The Role of Change Management
AI introduces massive shifts; managing sponsor expectations and workflows is as important as the tech.
10:28 – Engineering Impact
How the roadmap changed and what it meant for full-stack vs. data science roles.
14:24 – Hiring vs. Upskilling
Why Patrick hired an expert to lead AI efforts and the balance between internal upskilling and external hiring.
16:43 – Competing for AI Talent
How startups can win top AI talent despite the lure of FAANG compensation.
18:58 – Team Culture and Opportunity
Creating space for engineers who want to jump into AI while maintaining alignment on startup needs.
21:07 – Realistic Upskilling Paths
From Coursera to immersive bootcamps—what actually works for engineers wanting to break into AI.
23:11 – If He Could Do It Again
The two things Patrick would do sooner: hire a dedicated AI team and build structured data pipelines earlier.
🔖 Featured Quote:
“If you're serious about becoming an AI company, you need to find someone amazing who's launched real AI products—and build a team around them.”
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In this episode of The Tech Trek, Amir sits down with Sunita Verma, CTO at Character AI and former engineering leader at Google. Sunita shares how she’s transitioned from leading large-scale AI initiatives at Google to building novel experiences in a fast-paced startup environment. She dives into the mindset shift required to prioritize velocity over scale, how to lead AI-native product innovation, and what it means to be a female technical leader in today’s tech ecosystem.
🔑 Key Takeaways:
Shift in Leadership Mindset: At startups, leaders must prioritize velocity and innovation over scale, focusing on getting frictionless, AI-native products to market quickly.
AI Product Loop: Success comes from tightly coupling AI research with product development—shortening the feedback loop to create truly novel user experiences.
Female Technical Leadership: Sunita emphasizes the need for more women in senior engineering roles and shares how calculated risk-taking and mentorship shaped her journey.
Startup Clarity vs. Corporate Comfort: While startups offer focus and purpose, they also require deep ownership and rapid decision-making without the cushion of big-company resources.
💬 Quote:
“Focus brings clarity of purpose... but with that comes the pressure of knowing every decision deeply impacts the company.” — Sunita Verma
⏱️ Timestamped Highlights:
00:00 – Intro: Meet Sunita Verma, CTO at Character AI and former Google engineering leader.
01:52 – Google to Startup: Comparing work at Google with her current role at Character AI.
03:39 – Leadership Shift: Sunita’s take on building AI-native products from scratch.
06:21 – From Scale to Speed: Pivoting from optimization at scale to innovating with velocity.
08:12 – Product & Tech Integration: Creating tight feedback loops between AI research and products
10:01 – Closer to Engineering: Why Sunita enjoys being hands-on and deeply involved in compute management.
12:12 – Focus as a Double-Edged Sword: The simplicity and pressure of startup leadership.
14:00 – Female Engineering Leadership: The need for more women in senior tech roles.
16:02 – Career Advice: Why calculated risk and building a support network are key to long-term success.
19:14 – Leaving Google: Her thought process in taking the leap from a big brand to an emerging category leader.
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In this episode of The Tech Trek, Amir sits down with Emily Long, the CEO and co-founder of Edera, a deep tech startup focused on secure infrastructure. Emily shares her unconventional journey from HR leadership into the world of high-performance computing, infrastructure, and cybersecurity. Together, they explore the realities of leading a technical startup as a non-engineer, the underestimated value of soft skills in building scalable companies, and how trust, learning, and risk-taking shape leadership at every stage.
💡 Key Takeaways:
Soft Skills Scale: Emily challenges the misconception that only hard skills matter in tech leadership, showing how people skills drive team performance and product success.
Learning is a Superpower: Her career evolution was fueled by an unapologetic hunger to learn and willingness to step into discomfort and uncertainty.
The CEO as Conductor: Emily views the CEO role as orchestrating harmony across functions—ensuring each part of the company plays in sync.
Technical ≠ Only Coders: Emily has gained deep technical understanding through proximity, curiosity, and respect—without being an engineer herself.
Redefining Career Paths: She encourages others, especially in HR or non-traditional roles, to question labels and stretch into new domains with courage.
⏱ Timestamped Highlights:
(00:00) Intro to Emily Long and her transition from HR to tech CEO
(00:42) What Edera does: security + infrastructure beneath the Linux kernel
(02:07) Early career: from public accounting to people operations
(03:38) Becoming a founder by learning what others didn’t want to do
(06:10) Why she said “yes” to being CEO — and the orchestra analogy
(09:36) Relationship with CTO and deep respect for engineering
(12:51) The business acumen of HR professionals is underappreciated
(14:22) Breaking the “not technical” stigma and respecting both skill sets
(20:14) Should founders always scale with the company? A nuanced view
(23:25) Would she have jumped into tech sooner? The safety-risk tradeoff
(25:45) Where to connect with Emily: LinkedIn and edera.dev
💬 Quote to Feature:
"Just because you can doesn't mean you should. You’ve got to ask yourself—am I bringing the right energy to the next stage?" – Emily Long
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Arlene Watson, a product and engineering leader in the cybersecurity space with experience at CrowdStrike, ServiceNow, and Tenable, joins the show to unpack the critical challenges facing cybersecurity teams today. We dive into breach realities, the need for proactive defenses, how automation is reshaping security operations, and why AI is both a threat and an essential tool. If you’re building, managing, or securing software in today’s threat landscape, this episode is for you.
🔑 Key Takeaways:
Breaches are a daily reality – Most go unreported, but every breach should raise alarm bells because attackers may be setting the stage for larger, future infiltrations.
Automation is critical – Repetitive, manual tasks in cybersecurity can and should be automated to free up teams for higher-value, offensive strategies.
AI expands the threat and the solution – Generative AI introduces exponential risk, but it's also becoming a core component of advanced cyber defense strategies.
💬 Quote to Highlight:
"The moment someone says they know all the adversaries that will show up tomorrow, we know that’s not the fact. Our job is to chase the unknown and prepare for it." — Arlene Watson
⏱️ Timestamped Highlights:
00:00 – Intro to Arlene Watson and the state of cybersecurity today
00:33 – Why breaches are more common than we think
02:14 – Breaches must always raise alarm bells
05:26 – Understanding the hierarchy of high-value assets
08:23 – Automation trends in product engineering for cybersecurity
11:35 – Why cybersecurity budgets often lag behind priorities
15:04 – How AI is growing the cybersecurity attack surface
18:28 – Can AI help defend against adversarial AI?
21:22 – Prioritizing cybersecurity product development: foundation, automation, and integration
25:10 – Connect with Arlene via LinkedIn
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In this episode, Amir sits down with David Marchick, Dean of the Kogod School of Business at American University, to explore how AI is transforming higher education. From early skepticism to full-scale integration, David shares how his faculty is embracing generative AI—not just as a tool, but as a cornerstone of future-ready learning. The conversation dives into what it means to prepare students for an AI-infused workplace, the ethical dilemmas that arise, and how this technology could either widen or bridge existing academic gaps.
🔑 Key Takeaways:
AI Integration Is No Longer Optional: David emphasizes that resisting AI is like banning calculators—students will use it, so schools must evolve to teach responsible and effective use.
Education Must Mirror the Workplace: From proofreading to prototyping, AI skills are becoming table stakes in modern careers. Schools must prepare students accordingly.
AI as an Equalizer—or Divider: While AI tutoring tools can democratize learning, lack of access at under-resourced schools could deepen educational inequality.
Faculty Need Retraining Too: Teachers are being retrained with help from industry to effectively embed AI into their disciplines—from finance to marketing.
🧠 Quote:
“You won’t be replaced by AI. But you could be replaced by someone who knows how to use AI.” — David Marchick
⏱️ Timestamped Highlights:
00:00 – Introduction to David Marchick and American University’s approach to AI in education
01:15 – Why early academic response was to ban AI—and why that’s changing
03:30 – Shifting from fear to experimentation: How the Kogod faculty embraced AI
06:45 – Balancing original student work with AI assistance
09:00 – Teaching students to question AI and use it responsibly
12:20 – Will AI adoption in education be fast or slow? Marchick predicts years, not decades
14:50 – AI exacerbating the education gap: The equity question
16:15 – Use case: How AI tutors are built and used in quantitative graduate programs
18:45 – Writing, equity, and how AI may lift weaker students without eliminating learning
20:45 – Broader career implications: How AI reshapes job boundaries and skillsets
22:30 – Marketing example: Cutting down design debates with generative tools
24:45 – How to learn more about Kogod’s AI curriculum and initiatives
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In this episode, Amir sits down with Brent Keator, an expert advisor at Primary Venture Partners, to unpack one of the most debated engineering challenges: tech debt versus reengineering. They explore how to define tech debt, when to refactor versus rebuild, the ROI of revisiting old code, and how AI is (and isn't) changing the equation. This is a must-listen for engineering leaders navigating complex technical decisions in fast-moving environments.
🔑 Key Takeaways:
Tech debt isn't always bad—just misunderstood. Brent reframes it as part of the software evolution, often misjudged in hindsight with unrealistic expectations.
Refactoring isn't an all-or-nothing decision. Brent recommends carving out 30–40% of engineering time for tech debt if possible, and viewing it as iterative maintenance tied to business value.
Reengineering has a cost—evaluate wisely. Use the “better, faster, cheaper” test before replacing tools or platforms, and always account for hidden transition costs.
AI can help but won’t eliminate tech debt. While AI improves productivity, Brent argues it doesn’t change the underlying truth: software is disposable, and architecture still needs discipline.
⏱️ Timestamped Highlights:
00:00 – Intro to Brent Keator and the episode focus: tech debt vs reengineering
01:01 – Defining tech debt across code, products, and organizational habits
02:53 – When reengineering tools goes too far or solves the wrong problem
04:35 – The stigma of tech debt and how to rethink it
08:55 – The cost of revisiting old code and the ROI on fixing the past
11:12 – Why tech debt in engineering is fundamentally different than other domains
12:44 – When to rebuild, how to evaluate tool replacements, and the abstraction advantage
16:23 – Vetting open-source solutions: cost, support, and security risks
18:36 – The emerging role of AI in engineering and why trust and testing still matter
23:20 – Will AI help solve tech debt? Brent’s take on the future of disposable code
24:46 – How to connect with Brent and final thoughts
💬 Quote of the Episode:
“What we write today is going to be gone tomorrow. Whether AI helps or not, we need to get comfortable with that.” – Brent Keator
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In this episode, Amir Bormand sits down with Andy White, CEO of ClosingLock, to talk through his journey from PhD engineer to startup founder. Andy shares the aha moment that launched ClosingLock, a cybersecurity-focused platform protecting real estate transactions, and offers a transparent look at the early struggles of building trust in a skeptical industry. From pitching title companies with Chick-fil-A to learning an entirely new domain from scratch, this is a story about execution, humility, and listening harder than you pitch.
📌 Key Takeaways:
Execution > Ideas: Success came not from having a unique idea, but from executing better than competitors who had millions in funding.
Talk It Out: Andy credits customer conversations—and even explaining problems to a rubber duck—with clarifying and improving his product thinking.
In-Person Matters: Showing up with lunch and listening in-person proved essential in building trust with skeptical title companies.
Start Simple, Iterate Fast: ClosingLock launched with just one feature: securely sharing wiring instructions. Growth came by solving one problem at a time, then listening for the next one.
⏱️ Timestamped Highlights:
[02:10] – Why a PhD wasn’t all that helpful in building a startup.
[04:46] – Andy’s first “startup”—selling mazes in 2nd grade.
[07:20] – The lightbulb moment: real estate wire fraud almost hits home.
[11:15] – It’s not the idea—it’s the execution that matters.
[16:46] – The “rubber duck method” for solving complex problems.
[19:27] – Selling to skeptics: convincing title companies to try something new.
[21:17] – Why email, fax, and phone still dominate real estate—and why that’s a problem.
[25:49] – Would Andy build the same way post-pandemic? (Yes.)
[28:03] – Avoiding the trap of planning too far ahead.
💬 Quote:
"Ideas are cheap. Execution is everything. Everyone saw the problem—very few stuck around to solve it better."
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In this episode of The Tech Trek, Amir Bormand talks with Jason Wells, Head of Engineering at BrowserBase, about building a high-performance culture rooted in trust, emotional intelligence, and psychological safety. Jason shares how his unconventional path—including a six-year break from tech—helped shape a management philosophy that puts human connection at the center of engineering leadership. From dismantling blame culture to fostering self-compassion and authentic feedback loops, Jason offers a powerful framework for anyone looking to lead modern tech teams more intentionally.
💬 Quote:
“The best engineering is done by people who love their jobs. If you want the best output, you need a culture that makes people feel safe, trusted, and empowered.” — Jason Wells
🔑 Key Takeaways:
Trust is the foundation: Jason outlines how “boldly daring to trust” creates psychological safety—key to collaboration, innovation, and long-term performance.
Blameless culture matters: Mistakes should be opportunities for learning, not shame. This leads to more ownership and less deflection in engineering teams.
Emotional intelligence is a multiplier: Jason shares how his six-year break from tech helped him level up his emotional toolkit—skills he now actively brings into management.
Every engineer is unique: One-size-fits-all management doesn’t work. Jason emphasizes individualized leadership rooted in curiosity, vulnerability, and compassion.
🕒 Timestamped Highlights:
00:00 – Intro & Jason’s background
02:43 – What makes a great engineering culture
04:40 – Why trust and psychological safety are non-negotiable
06:59 – How BrowserBase screens for cultural alignment
10:46 – Building an ideal environment from scratch
12:27 – Jason’s early start: Atari, Oracle, and startups
17:00 – Transition into management and leadership philosophy
20:00 – Leaving tech for six years: self-actualization and purpose
24:00 – Learning emotional intelligence and conflict resolution
28:19 – Creating safe space for engineers with high expectations
31:38 – Preventing burnout while maintaining performance
33:38 – Leadership means knowing your people
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In this episode, Amir Bormand sits down with Kieran Furlong, CEO and co-founder of Realta Fusion, to explore the unique path of a deep tech startup spun out of a university lab. They discuss building a fusion energy company, navigating complex stakeholder relationships with universities and government agencies, and keeping long-term mission-driven teams aligned. From licensing technology to managing a decade-long development cycle, this conversation reveals how Realta Fusion is working to change the world’s energy future.
🔑 Key Takeaways:
Deep tech startups require a different VC playbook: Realta Fusion operates on a decade-long roadmap that demands alignment with investors willing to play the long game.
University spinouts bring both opportunity and friction: Leveraging academic research can be powerful but navigating bureaucracy and IP licensing adds layers of complexity.
Mission-driven leadership is essential: With long timelines and uncertain outcomes, Kieran keeps his team focused through a relentless reminder of their shared purpose—commercial fusion energy.
Energy abundance as a global equalizer: Fusion isn’t just a tech challenge—it’s a moral imperative to bring energy equity to the planet’s future 10 billion people.
🕒 Timestamped Highlights:
00:25 – Intro to Kieran Furlong and Realta Fusion's mission
01:35 – Why Realta is a venture capital outlier: long timelines and deep capital
03:46 – Spinning out of the University of Wisconsin and working with federal energy programs
05:55 – Startup vs university culture clashes and how to navigate them
08:07 – The race to meet fusion milestones by 2035
11:53 – Diplomacy in energy: balancing federal, academic, and private sector dynamics
14:53 – The global case for fusion: climate, equity, and energy abundance
16:05 – How to lead scientists toward a commercial goal without losing curiosity
18:29 – Licensing tech the right way: aligning incentives for long-term success
21:00 – Where to follow Realta Fusion and get involved
💬 Quote:
“You still want the creativity and curiosity of scientists—but you need to keep one eye on the destination: commercial fusion energy.” – Kieran Furlong
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In this episode of The Tech Trek, Amir sits down with Clark Downum, CTO at Redox, to unpack the deeper dynamics between engineering, product, and business stakeholders. From tech debt and project delays to culture, communication gaps, and delivery trade-offs—this conversation is a candid exploration of how technical teams can drive impact without getting stuck in process perfection.
Whether you're a tech leader or aspiring one, this episode offers a fresh lens on ownership, expectation-setting, and delivering what really matters.
🔑 Key Takeaways:
The cost of tuning out business context: Engineers often rush to solution-mode too early—Clark stresses the need for active listening before architecting.
Tech debt is not a dirty word: Clark challenges traditional thinking—some tech debt is strategic, and discussing it in business terms builds clarity.
Product owners need more support: Agile isn't just about shifting scope; engineering teams should help product leaders clarify and prioritize based on impact.
Delivery ≠ Impact: Shipping on time is not enough. Clark urges teams to elevate conversations toward value, trade-offs, and business impact over output.
⏱️ Timestamped Highlights:
00:48 – What Redox does and the scale of its data exchange operations
02:00 – Onboarding engineers in a complex healthcare ecosystem
03:55 – Why stakeholders often only ask about engineering when things go wrong
07:24 – Do engineers stop listening when they start solutioning too early?
10:20 – Rethinking tech debt: What the business doesn’t know actually helps
13:46 – Can we train engineers to prioritize “getting it done” over “doing it right”?
17:36 – Agile as a response to imperfect plans, not bad estimates
20:53 – Why scope, time, and quality are business trade-offs, not just engineering ones
22:22 – "The burden is on engineering"—and why that might be the right mindset
24:52 – Final thoughts on collaboration, failure, and owning outcomes
💬 Quote of the Episode:
“Don’t just ask, ‘Is this hard?’ Ask, ‘How hard should I work to make this easy?’ That’s where true collaboration starts.” – Clark Downham
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In this episode of The Tech Trek, Daniel Whatley, co-founder and technical lead at Vividly, shares his journey launching a startup while still a student at MIT. From managing college life during COVID to navigating the CPG industry's digital transformation, Daniel reflects on what it meant to be the youngest in the room, how he grew into executive leadership, and what he wishes he’d known before co-founding a company. A candid look at growth, grit, and the impact of youth in a traditional space.
🔑 Key Takeaways:
Startups in school are possible: Daniel co-founded Vividly while at MIT, proving early-stage entrepreneurship can thrive during college years—even amid COVID.
Tech-first in a non-tech industry: He leveraged his technical expertise to modernize trade spend management in consumer packaged goods.
Being the youngest has its perks: Despite age differences, deep domain knowledge can earn respect and create opportunity.
Hard lessons in leadership: Managing older employees taught Daniel resilience and the importance of learning on the job.
💬 Memorable Quote:
“Don’t give up. If something feels hard, remember you’ve solved a million problems before—this is just the million-and-first.” – Daniel Watley
⏱ Timestamped Highlights:
00:23 – 01:30 — Intro to Daniel and Vividly’s mission in CPG optimization
03:39 – 05:18 — Launching a company as a student and the power of momentum
06:27 – 08:13 — Choosing a startup over corporate offers post-graduation
08:17 – 09:39 — Origin of the business idea from family connections
10:20 – 12:18 — How COVID created unexpected demand for their product
12:35 – 15:14 — Being the youngest in the room and embracing your technical edge
15:17 – 17:57 — What’s changed: scaling, hiring, and engineering maturity
18:32 – 21:34 — Learning management fast: handling tough dynamics with older team members
21:53 – 24:11 — Daniel’s advice to aspiring founders still in school
25:07 – 26:21 — Would he take the job if he could do it again? No regrets
26:21 – 27:32 — Final thoughts and how to connect with Daniel
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In this episode of The Tech Trek, Amir is joined by Jonathan Myron, VP of Engineering at Healthie, to dive into what it really takes to lead engineering teams inside startups. From aligning with founders' visions to building engineering cultures that thrive on autonomy and creativity, Jonathan shares hard-won lessons for engineers stepping into leadership. Whether you're building early-stage or scaling through growth, this episode delivers practical insights on driving value, developing team culture, and shaping your career path.
🔑 Key Takeaways:
Start with empathy for the founder’s vision. Engineering leaders must deeply understand why a company was started to effectively implement and scale that vision.
Leadership is a behavior, not a title. Taking ownership, solving problems, and filling gaps earns trust and influence, especially in startup environments.
Engineering culture thrives on transparency and purpose. Aligning product goals with team values keeps engineers motivated and connected to impact.
Metrics are a story, not a scoreboard. Use developer experience surveys and team feedback—not just velocity or failure rate—to shape team performance meaningfully.
⏱ Timestamped Highlights:
00:00 – Intro to Jonathan and the theme: working with founders in startups
01:48 – Why understanding the founder’s origin story matters for engineering leadership
03:00 – Sussing out alignment during interviews with startup founders
04:15 – Translating founder vision into engineering execution and culture
05:19 – The role of metrics and surveys (like Westrom) in measuring alignment and team health
06:49 – Why engineering is both a scientific and creative pursuit
08:26 – Bridging founder imprint and engineering culture with empathy and clarity
09:53 – Common traits of successful founders and how engineers can support them
11:58 – Driving value by solving problems without waiting for instruction
13:25 – Advice: “Put aside ego. Real leaders don't need titles.”
15:08 – Thriving in ambiguous, high-impact startup environments
16:54 – How to reach Jonathan on LinkedIn for career advice
💬 Standout Quote:
“Leadership is when somebody is a leader, everybody knows it—and you don't need a title for that.” – Jonathan Myron
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What should you really be asking during your interview as a tech leader? And once you land the role, how do you manage expectations, reduce technical debt, and make meaningful impact fast?
In this episode, Justin Nguyen, Technology Director of Enterprise Data & Analytics at Home Depot, shares hard-won insights from his recent leadership transitions. From assessing team maturity to setting realistic AI expectations, we unpack the tactical and strategic moves leaders need to thrive in the first 180 days of a new role.
💡 Key Takeaways:
Interview the Company Like a Pro: Ask about key initiatives, maturity of the org, and how they attract top talent—not just the role’s scope.
Manage Expectations with Data: Use metrics and storytelling to align stakeholder expectations with technical realities.
Build Trust First: Quick wins, especially those that align with long-term goals, are essential for establishing credibility early.
Data's Real Value is Trust: The true measure of data success is stakeholder trust and consistent usage.
Balance Training vs. Hiring: When evolving your team, identify real skill gaps and be transparent to maintain trust.
⏱️ Timestamped Highlights:
[01:18] – Three things to assess in interviews: org maturity, domain readiness, and team strength
[03:30] – Why the presence of technical/data debt should be expected—not feared
[06:28] – Aligning stakeholder expectations with reality to reduce frustration
[09:27] – The real AI question: what not to do with it
[11:17] – Spotting leadership dynamics during interviews
[14:16] – Measuring your own leadership ROI in the first 90–180 days
[17:19] – Short-term wins that support long-term strategic goals
[19:44] – Measuring success in data through usage and trust
[22:19] – Balancing team upskilling, outside hiring, and consulting
🔖 Quote of the Episode:
“Frustration is the delta between expectations and reality. The greater the gap, the greater the frustration. Your job is to close that gap.” – Justin Nguyen
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In this episode of The Tech Trek, Brendan Grove, CTO and co-founder at PrizeOut, shares how his non-traditional background shaped his leadership style and hiring philosophy. Brendan dives into how being curious, humble, and pattern-aware has helped him scale teams and solve complex problems. He also unpacks how hiring for core traits like learning velocity and ownership can outperform chasing resumes full of surface-level skills. We also discuss tech debt, decision-making frameworks, and the role of engineering excellence in business success.
Whether you're a startup founder, engineering leader, or aspiring technologist, this episode is a reminder that greatness often lies beyond the obvious checklist.
🔑 Key Takeaways:
Hire for Curiosity and Ownership: Brendan values engineers who "give a shit" more than those who just ace technical interviews. Passion, curiosity, and ability to learn fast are force multipliers.
Non-Traditional Backgrounds Offer Valuable Perspective: Brendan's journey from mechanical engineering to CTO helped him build pattern recognition and a strong product-building instinct.
Balance Autonomy and Accountability: Great leaders don’t need to be the expert—they need to empower others while knowing when to step in.
Tech Debt Isn’t the Enemy—Stagnation Is: Tech debt becomes a problem only when it slows you down or introduces risk. Code should be easy to change without fear.
⏱️ Timestamped Highlights:
00:32 – What PrizeOut Does
01:13 – Brendan’s Path from Mechanical Engineering to Tech
02:59 – Humility and Curiosity as Tools for Problem Solving
04:41 – Delegating While Still Leading
06:46 – What Brendan Looks for When Hiring Engineers
09:24 – Hiring Junior vs. Senior: A Strategic Approach to Ramp-Up
11:56 – Giving Raw Talent a Chance: A Success Story
15:08 – Code Quality vs. Business Value: Finding the Right Balance
17:47 – Tech Debt: When It Matters and How to Approach It
💬 Quote:
"You should be able to make small changes without being scared. If you can't, it's not a testing problem—it's a code problem."
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In this episode of The Tech Trek, Amir sits down with Ronak Vyas, Co-Founder and CTO of Lead Bank, to explore how leadership principles remain constant even as the problems — and companies — change. Ronak shares lessons from leading at Yahoo, Square, and now founding a fintech bank, reflecting on how to adjust to new environments, make high-stakes decisions, and transition from engineering leader to startup founder. If you’re a technology professional considering leadership or even starting your own venture, this episode is packed with real-world insights on navigating change, making smart decisions, and staying close to your craft.
🔥 Key Takeaways:
Leadership tools stay constant, but their application must adapt to different company cultures, industries, and scales.
Prioritize understanding the business context before forming strong technical opinions.
Speed of decision-making beats perfection — collect real-world data fast, iterate, and adjust.
As a founder, decision-making carries broader consequences, making a deep business understanding essential beyond technical leadership.
Retaining technical depth is critical as you move into higher leadership roles, especially when founding or joining small companies.
🕰️ Timestamped Highlights:
(00:42) – What Lead Bank does: Combining fintech innovation with banking infrastructure.
(02:20) – How to adjust to new company cultures and identify first-order problems.
(05:47) – Why leadership skills are constants — and how applying them evolves.
(09:11) – Balancing gathering information with moving fast: an art, not a science.
(13:39) – Why fast, iterative decision-making often beats chasing perfection.
(15:12) – How decision-making changes when you're a co-founder vs an executive.
(17:28) – Staying technically sharp: the importance of retaining depth as you grow.
(21:18) – What Ronak wishes he had more exposure to before becoming a founder.
💬 Memorable Quote:
"Most often, it's better to make a good decision and iterate quickly than to wait for the perfect decision — real-world feedback is your best guide."
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In this episode, Marty Neese, CEO of Verdagy, joins Amir to unpack what it takes to scale a company in one of the most innovative and high-stakes industries—green hydrogen. From managing a purpose-driven culture to embracing failures as a strategic advantage, Marty shares insights on leading ambitious climate tech initiatives while staying grounded in economic reality. Whether you're in tech, energy, or just love solving complex problems, this one's for you.
🔑 Key Takeaways
Purpose as a North Star: Verdagy’s mission—delivering the power of nature—is more than a slogan. It shapes the company’s decision-making, from high-level strategy down to subcomponent cost roadmaps.
Problems Are Treasures: Marty champions a culture where failures are embraced as learning opportunities, inspired by the Toyota Production System.
Motivation Through Impact: When the going gets tough, Verdagy employees reconnect with their impact—literally watching hydrogen being created in real time—to reignite their passion.
CEO Doesn't Mean Solo: Marty opens up about his reliance on investor and customer feedback as his mentorship circle, busting the myth of the lone visionary at the top.
🕒 Timestamped Highlights
[00:40] – What Verdagy does: splitting water to create hydrogen and oxygen.
[01:55] – Why purpose matters more than just a mission statement.
[03:54] – “Problems are treasures”: embracing failure as an asset.
[06:53] – Knowing when a problem isn’t worth solving.
[08:38] – Staying motivated when outcomes are uncertain.
[11:41] – Breaking down purpose into measurable missions.
[14:03] – A look into Verdagy’s quarterly cost roadmap methodology.
[16:29] – Marty’s unexpected mentors: customers and investors.
[18:52] – The future of green hydrogen and fossil parity.
💬 Quote of the Episode
“Every time you encounter a problem, there's treasure to be mined. That mental polarity shift—from failure to learning—is how real innovation happens.” — Marty Neese
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In this episode of The Tech Trek, Amir chats with Rob Williams, co-founder and CTO at Read AI, about what it truly means to be an AI-native company. Rob shares how Read AI uses its own tools internally, how his small but mighty engineering team balances speed and structure, and the evolving role of AI in productivity workflows. Whether you're building AI products or trying to adopt them effectively, this conversation offers a unique peek behind the curtain of a startup navigating the future of work.
💡 Key Takeaways:
AI adoption without intentionality fails. Many companies are experimenting with AI tools, but without clear goals, adoption is often aimless.
“Tech debt” is outdated. Rob prefers specific discussions around scalability, readability, and maintenance over the vague term “tech debt.”
Internal AI usage drives efficiency. Read AI uses its own product to streamline workflows like onboarding, reducing repetitive knowledge transfer.
Small teams thrive on focus. Being a smaller company is an advantage when it comes to agility, focus, and avoiding bureaucracy—especially in AI.
⏱ Timestamped Highlights:
00:35 – What Read AI is and how it differs from big platform players.
02:19 – Why intentionality matters in successful AI adoption.
04:41 – How building AI-native products changes the cost/benefit mindset.
06:28 – Rob’s hot take on the term “tech debt” and why he avoids it.
09:45 – How they divide engineering time between R&D, product, and internal needs.
12:19 – Using AI to eliminate repetitive tasks like onboarding and documentation.
15:34 – How startup culture encourages practical AI tool adoption.
18:08 – Closing the gap between engineers and customer feedback.
20:45 – Competing with tech giants by focusing narrowly and moving efficiently.
🧠 Quote of the Episode:
“If we know something will serve our customers well for the next three to six months, we do it. Anything beyond that is just as likely to be wrong as it is right.” – Rob Williams
If you'd like to see Read AI in action, this link will take you to the transcript their AI produced of the episode: https://app.read.ai/analytics/meetings/01JPJXY1SFAXE509NJ4S5P0W5X?utm_source=Share_CopyLink
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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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