The Tech Trek

Elevano

The Tech Trek explores the intersection of People, Impact, and Technology — how engineering leaders build high-performing teams, deliver real outcomes, and shape the future of innovation. Hosted by Amir Bormand, founder of Elevano, the show features CTOs, VPs of Engineering, and technical leaders sharing candid insights on leadership, scaling, and building technology organizations that last. Each episode uncovers the decisions, lessons, and mindsets that separate good teams from great ones — and the people who make technology move forward.

  1. How AI Is Changing the Way We Talk to Computers

    10시간 전

    How AI Is Changing the Way We Talk to Computers

    Mike Hanson, CTO at Clockwise, joins the show to break down how our relationship with computers is changing as language based systems reshape expectations. We explore why natural storytelling feels so intuitive with today’s AI tools, how context is becoming the new currency of great software, and why narrow AI is often more powerful than the industry hype suggests. This conversation gives tech leaders a grounded look at what is real, what is noise, and what is coming fast. Key Takeaways • Natural storytelling is becoming the default way people communicate with AI, and products must adjust to that shift. • Context is the driving force behind great interaction design and LLM powered systems now surface and use context at a scale traditional UIs never could. • Most real world gains come from narrow AI that solves focused everyday problems, not from broad AGI promises. • Multi agent systems and multiplayer coordination are emerging as the next frontier for enterprise AI. • The biggest risk is not model weakness but user uncertainty about when an answer is trustworthy. Timestamped Highlights 01:21 What Clockwise is building with its scheduling brain and how natural language creates new value 04:13 Why humans default to storytelling and how LLMs finally make that instinct useful 08:00 The rising expectation that software should understand context the way people do 12:13 The shift away from feed centric design and toward multi person coordination in AI systems 17:31 Why narrow AI delivers real value while wide AI often creates anxiety 23:52 A real world example of how AI can remove busy work by orchestrating tasks across tools 26:24 Why we do not need AGI to meaningfully improve everyday productivity A standout thought People have always tried to talk to computers in a natural way. The difference now is that the systems finally understand us well enough to meet us where we already are. Pro Tips • Look for AI that reduces busy work across tools rather than chasing broad capability. • Prioritize context rich interactions in your product planning. It will define user expectations for years to come. • Treat multi person workflows as the next major opportunity. Most teams still rely on manual coordination. Call to action If this episode helped you think differently about where AI is actually useful, follow the show and share it with someone who is building product in this space. And join me on LinkedIn for weekly insights on tech, people, and impact.

    28분
  2. The Truth About Starting Again After a Big Exit

    1일 전

    The Truth About Starting Again After a Big Exit

    Soham Mazumdar, CEO and co founder of Wisdom AI, joins the show to talk about what it really takes to build again after major exits at Facebook and Rubrik. We get into the mindset shift required for a new startup, the danger of relying too much on past playbooks, and how to stay grounded when expectations rise. If you want a real look at repeat founder decision making, this is the conversation to listen to. Key Takeaways • The biggest advantage of being a repeat founder is the ability to attract talent and early believers, but it does not replace the need for fresh thinking. • Pattern matching can help with people decisions but can block you everywhere else if you assume the past will repeat. • Feedback can steer you or mislead you. The real work is separating patterns from outliers and understanding the motivation behind what someone says. • Every new company pulls you back to zero. Past success does not win customers or validate your idea. • Early career operators who want to build should leap sooner than later. Even a failed startup can shape a long career. Timestamped Highlights 02:01 How building tactile and Rubrik shaped his approach to Wisdom AI 04:07 What actually drives someone to found a company after a giant exit 05:52 Why repeat founders must fight the urge to reuse old playbooks 10:06 How to course correct when your first instincts are wrong 13:38 The danger of reacting too fast or too slow to customer feedback 18:02 How expectations shift once you have a track record 24:42 Why Wisdom AI connected with his earliest experiences at Google 25:28 The advice he wishes someone had given him before startup number one A standout line “The world pulls you down to the ground fast. Whatever you think you are, a new company reminds you that none of it matters unless you execute.” Practical advice from the conversation • Do not treat feedback as instructions. Treat it as signal to study. Look for repeated patterns, not one loud voice. • Approach every new company with a clean mind. If your old patterns do not match the new environment, abandon them quickly. • Think of your career as a long arc. Early risks create unexpected doors later. Closing note If the episode gave you something to think about, follow the show and share it with someone who wants a real look at the founder journey. You can also join the community on LinkedIn for more insights and upcoming episodes.

    30분
  3. How One Startup Is Cutting the Cost of Borrowing Money

    2일 전

    How One Startup Is Cutting the Cost of Borrowing Money

    In this episode of The Tech Trek, Amir sits down with Sadi Khan, Co-Founder and CEO of Aven, to unpack how technology can make capital fairer for everyone. Sadi explains how Aven is tackling one of the world’s biggest inefficiencies—the trillion-dollar burden of consumer credit card debt—and why the solution lies in reducing the cost of capital through innovation. This is a deep dive into building products that require not just engineering skill, but endurance, conviction, and a long-term mindset. Key Takeaways • Aven’s mission is to cut credit card interest payments in half by rethinking how consumers access and use home equity. • True innovation often comes from solving inefficiency, not chasing market trends. • Complex problems create strong moats when founders are willing to grind through technical and regulatory barriers. • Founders should pick problems worth spending a decade on—pivot less, persist more. • Product success depends on identifying your “axis” and going all-in on being the best at that one thing. Timestamped Highlights 00:40 — How Aven’s hybrid credit card + HELOC model is lowering the cost of borrowing for homeowners 04:10 — The moment Sadi realized the cost of capital was a massive, overlooked problem 12:34 — Why most lenders haven’t solved this yet and how Aven’s approach differs 19:33 — Building what others couldn’t: how persistence and engineering precision led to breakthroughs 23:36 — Choosing execution risk over market risk and what it takes to stay with a problem long enough to solve it 37:47 — Why picking the right “axis” is how great companies build an unshakable moat Memorable Line “The only problems worth working on are the ones worth working on for a very long time.” Call to Action If you enjoyed this episode, follow The Tech Trek for more conversations at the intersection of people, impact, and technology. Subscribe on your favorite platform and share it with someone building bold ideas.

    42분
  4. How Data and Engineering Make the Impossible Real

    3일 전

    How Data and Engineering Make the Impossible Real

    Svetlana Zavelskaya, Head of Software Engineering for Data Platform and Infrastructure at Quanata, joins the show to unpack what it really takes to make the “impossible” possible in tech. From re-architecting a startup codebase to scaling innovation inside an insurance giant, she shares how her team turns complex R&D challenges into production-ready systems. This conversation dives deep into engineering discipline, AI tool adoption, and why the next wave of insurance innovation is powered by data and software. Key Takeaways • Real innovation often means balancing speed with long-term architecture decisions • AI coding tools are valuable for exploration but need governance and clear security guardrails • POCs fail when expectations aren’t aligned, not because the tech doesn’t work • Insurance tech is evolving fast through telematics and context-based data models • Well-structured, well-documented code is still the foundation for scalable innovation Timestamped Highlights 00:33 How telematics is changing the economics of insurance and rewarding better drivers 03:59 Cars as software platforms and what that means for data privacy and innovation 06:02 The growing pains of re-architecting an organically built startup codebase 08:38 Evaluating new AI tools and maintaining data security across teams 11:08 Why most AI POCs never make it to production 16:29 How Quanata’s R&D work feeds into State Farm’s larger technology initiatives 20:40 Safe-driving challenges, behavioral change, and saving lives with data A Thought That Stuck “If we can prevent just 1 percent of drivers in the world from using their phone behind the wheel, imagine how many lives we can save.” Pro Tips • Before starting a POC, define if it’s an experiment or a potential product foundation • Let engineers explore new tools but build frameworks to govern how data and results are handled Call to Action If you enjoy exploring how data, AI, and engineering innovation come together to solve real-world problems, follow The Tech Trek on Apple Podcasts or Spotify and share this episode with a colleague who builds at the edge of what’s possible.

    27분
  5. The Future of Voice AI: When Machines Start to Sound Human

    11월 6일

    The Future of Voice AI: When Machines Start to Sound Human

    Nikhil Gupta, founder and CTO of Vapi, joins Amir to talk about how voice AI is reshaping the way we connect with businesses. From customer support to healthcare, Nikhil explains how voice agents can bring back the human side of digital interactions. This is a look at where real conversation meets real technology and what happens when machines start to understand us like people do. Key Takeaways • Voice AI creates genuine, human-like engagement instead of the usual scripted support. • The next wave of AI will personalize relationships at scale while protecting privacy. • Full duplex voice models will make conversations flow naturally and feel real. • Businesses will use voice agents to understand customers, not just respond to them. • Our phones and screens may evolve as voice becomes the primary interface. Timestamped Highlights 01:08 — What Vapi does and how it reached 400,000 developers 02:15 — Why voice AI is one of the few areas showing clear ROI 06:09 — How AI can make customer relationships human again 11:18 — Building trust and privacy into voice-based systems 16:48 — Blending text, voice, and context into a single experience 19:05 — Rethinking our devices as voice replaces the screen A moment that stands out “Every person should feel like they can just text their hospital, and it knows exactly who they are, what they need, and when to help.” — Nikhil Gupta Pro Tip Start small. Use voice AI where conversation improves experience or clarity. It’s not about automation; it’s about creating connection. Call to Action Share this episode with someone exploring AI in their business and follow The Tech Trek for more stories about people, impact, and technology.

    25분
  6. Building a Startup Culture Where No One Wants to Leave

    11월 5일

    Building a Startup Culture Where No One Wants to Leave

    Alex Daniels, Founder and CTO at Predoc, joins the show to share how he is building a mission driven healthtech company that is changing how medical data is accessed and used. He opens up about the personal story that inspired Predoc, how he keeps culture authentic while scaling, and what zero turnover really looks like in a startup. From hiring philosophies to equity design to managing context switching, Alex brings a deeply human view of leadership in engineering. Key Takeaways • Building culture starts with personal connection. Founders who share their why help every new hire connect to mission and meaning. • The best hiring filters are values and networks, not just tech stack alignment. • Predoc’s culture formula of high agency, urgency, meritocracy, and transparency keeps turnover at zero. • Equity is not just compensation. It is shared ownership and long term motivation. • Flat structures and super ICs can scale effectively when leaders stay close to the work. Timestamped Highlights [01:30] How a personal loss and a lifelong heart condition inspired Predoc’s mission to fix healthcare data [05:20] Inside Predoc’s culture formula and why it has helped them retain every hire for three years [09:40] Why core values stay constant but merit evolves as the company grows [13:00] Rethinking equity and risk for early startup employees [15:10] How Predoc combats AI assisted interview cheating and keeps hiring authentic [23:45] Building a flat team structure where directors are still super ICs [30:00] Alex’s approach to managing context switching and mental decompression Memorable Line “We cared about what he cared about and why would he care about what we care about if I don’t care about him?” Call to Action If you enjoyed this conversation, follow The Tech Trek for more candid talks with founders and tech leaders shaping the future of engineering and culture. Subscribe on Spotify or Apple Podcasts and join the discussion on LinkedIn.

    33분
  7. Building Infrastructure Startups: Why Everything Takes Longer Than You Think

    11월 4일

    Building Infrastructure Startups: Why Everything Takes Longer Than You Think

    Jordan Tigani, CEO and cofounder of MotherDuck, knows what world class infrastructure looks like. He spent years building Google BigQuery before taking those lessons into the startup world. In this episode, he breaks down why building infrastructure products is fundamentally different from typical SaaS and why founders who don’t understand that difference are in for a painful surprise. What You'll Learn There are no shortcuts in infrastructure. You can’t just wire together existing open source components and call it a product. Real infrastructure requires contributing meaningfully to the state of the art, and that takes time, money, and deeper technical investment than most founders expect. Starting with startups, not enterprises, is often the smarter play. Early stage infrastructure companies should target other startups first because they’re more comfortable with bleeding edge tech, have lower security barriers, and won’t force you to spend three engineers building custom auth instead of your actual product. Scaling down is the new scaling up. Jordan saw pressure at SingleStore to make databases smaller and more efficient, not just bigger. That insight led to MotherDuck, which is built on DuckDB—a database that can run in a car, scale to massive cloud instances, and challenge the coordination overhead of legacy distributed systems. Bottoms up engineering cultures win in infrastructure. At BigQuery, engineers close to customer problems could ship fast and independently. Jordan’s recreating that at MotherDuck by removing layers between engineers and customers, because creative problem solving requires understanding business constraints, not just technical ones. Convincing people you can scale is half the battle. The best proof is customers who look like your next target and can vouch for you. Next best is real data and benchmarks. If you don’t have those yet, lean on implementation support and help prospects test at scale themselves. Early on, sometimes all you have is your word. Timestamped Highlights [01:22] Why infrastructure takes longer to build than typical SaaS products and why there’s no shallow way to do it [06:57] The MVP dilemma: finding product market fit when enterprises demand reliability from day one [11:44] Lessons from BigQuery and SingleStore—what to carry over from big tech and what to leave behind [21:21] The gap in the market that led to MotherDuck: why distributed databases don’t scale down and why that matters now [26:10] Redefining scale: why 100 users on one giant instance isn’t necessarily better than 100 auto scaling individual instances [29:08] The hierarchy of proof: from customer testimonials to benchmarks to trust me, it’ll work A Line to Remember “If you really want to build an infrastructure product, you can’t just string existing components together. You actually have to contribute meaningfully to improving the state of the art.” Stay Connected If this breakdown of infrastructure startups resonated with you, subscribe so you don’t miss future episodes. And if you’re building in this space or thinking about it, connect with Jordan on LinkedIn. He’s committed to paying forward the help he got as a founder.

    33분
  8. Why Enterprise Product Management Is Completely Different

    11월 3일

    Why Enterprise Product Management Is Completely Different

    Ogi Kavazovic, co-founder and CEO of House Rx, joins the show to unpack what most product leaders miss about building for enterprise software. Drawing from two decades in tech, Ogi breaks down how product management shifts when you move from B2C or “B to small B” to true enterprise—what he calls “B to Big B.” He explains why traditional user research frameworks don’t hold up, how buyer research should actually be done through sales and marketing motions, and how to keep engineering teams aligned when the product takes years to build. Key Takeaways • Building for enterprise (B to Big B) requires selling to buyers and users—two very different audiences with distinct needs. • Buyer research is not user research—it happens through early sales decks, vision slides, and iterative storytelling that test how well a concept resonates before code is written. • Pre-selling a “fantasy product” through slides helps validate the market fit and shapes the first version of your product strategy. • Engineering for enterprise software demands simulated iteration—testing features internally long before the MVP is complete. • Vision alignment between product, marketing, and engineering is crucial to avoid two-year build tunnels and ensure team motivation. Timestamped Highlights [03:12] The overlooked divide between B2B and true enterprise—why “B to Big B” changes everything for product teams. [10:47] How buyer research actually works and why it starts with slides, not software. [17:40] The difference between pitching VCs and pitching enterprise buyers—and why they care about totally different things. [22:29] The engineering challenge of building massive enterprise systems and why agile methods fall short. [30:11] How to keep teams motivated and moving forward when the product roadmap spans years. Standout Moment “You can pre-sell a product before it even exists. That sales and marketing artifact—the deck you built to sell your vision—can become the blueprint for your product strategy.” Pro Tips Start with conversations, not code. Use early customer and buyer meetings to validate your story through slides, then hand your engineers a vision they know can sell. Call to Action If you enjoyed this episode, share it with a fellow product leader or founder navigating enterprise challenges. Follow The Tech Trek for more conversations that connect people, impact, and technology.

    33분
모두 보기(569개)

5
최고 5점
74개의 평가

소개

The Tech Trek explores the intersection of People, Impact, and Technology — how engineering leaders build high-performing teams, deliver real outcomes, and shape the future of innovation. Hosted by Amir Bormand, founder of Elevano, the show features CTOs, VPs of Engineering, and technical leaders sharing candid insights on leadership, scaling, and building technology organizations that last. Each episode uncovers the decisions, lessons, and mindsets that separate good teams from great ones — and the people who make technology move forward.

정보

  • 제작진
    Elevano
  • 방송 연도
    2020년 - 2025년
  • 에피소드
    569
  • 등급
    전체 연령 사용가
  • 저작권
    © Elevano
  • 웹사이트 보기
    The Tech Trek

좋아할 만한 다른 항목