The Tech Trek

Elevano
  • 5.0 (79)
  • Technology
  • Updated Semiweekly

The Tech Trek is a podcast about how founders, operators, and technology leaders build and scale technology companies. Each episode explores the decisions behind building products, teams, and technical organizations, with conversations spanning engineering, AI, data, product, hiring, leadership, and growth. Guests share what they are building, what they are learning, and how they are navigating the challenges that come with turning technology into a successful company.

  1. 21h ago

    Problem Statements, Business Outcomes, and Better Technology Decisions

    Technology teams are often asked to solve something before everyone agrees on what the actual problem is. Chad Carrington, CIO at Golden1 Credit Union, joins The Tech Trek to talk about listening to business partners, defining the outcome first, and resisting the instinct to jump immediately to a technology solution. The conversation also looks at how AI is changing this skill. As tools make building easier and faster, people still need to articulate what they actually want, ask better questions, and understand what success looks like. What You Will Hear • Why listening and hearing are not the same thing • When solving 85 percent of a problem may be enough • Why technology teams need more time with business users • How AI is increasing the value of asking better questions Key Moments 01:20 Listening versus actually hearing the business problem 03:47 When immediate customer impact matters more than technical debt 06:31 Bringing the business into decisions about speed and tradeoffs 09:47 Why technologists need to spend more time with business teams 13:20 How easier tools change the importance of defining the problem 18:33 Why AI is still a tool, not a substitute for expertise One Line That Stuck “There’s a difference between listening and hearing.” Follow The Tech Trek for more conversations with the people building and leading modern technology teams.

    Problem Statements, Business Outcomes, and Better Technology Decisions

  2. 2d ago

    Physical AI and the Real Time Supply Chain

    AI has learned from the digital world. Physical AI brings real world data into the picture. Doron Hazan, Director of Products and AI at Wiliot, joins The Tech Trek to explain how physical AI connects AI systems with objects, environments, and supply chains. The challenge is not simply processing data. It is collecting accurate, current information from the physical world. Doron explains how ambient IoT, sensors, statistical inference, and cloud systems can help companies understand where assets are, what condition they are in, and what may happen next. The conversation also covers the role of human judgment. Supply chains require many decisions, often with consequences that spread across the system. That makes guardrails and human involvement especially important. Key Takeaways • Physical AI connects AI systems with data from the real world. • Better supply chain visibility starts with accurate, current physical data. • Real time decisions matter, but decision accuracy matters more. • Human judgment remains important when AI affects physical operations. Highlights 01:53 What separates physical AI from traditional AI 03:18 Why real world data collection changes the problem 07:19 Supply chain visibility and practical use cases 11:57 How quickly physical AI systems can make decisions 12:48 Why guardrails matter in supply chain automation 15:28 Robotics, distributed physical AI, and connected systems Follow The Tech Trek for more conversations about AI, engineering, product, and technical leadership.

    Physical AI and the Real Time Supply Chain

  3. Sep 24

    From Smart Dust to Edge AI: Building Intelligence Everywhere

    Scott Hanson went straight from a PhD program at the University of Michigan to building a semiconductor company. Today, as Founder and CTO of Ambiq, he is working on the same core idea that inspired the company years ago: putting intelligence into the devices around us. What changed is what those devices can now do. Scott shares what it was like becoming CEO without prior industry experience, why moving into the CTO role was harder than expected, and how the rise of AI accelerated Ambiq’s original vision. The conversation also looks at what happens as more AI processing moves closer to the device, from wearables and smart homes to factories, medical devices, infrastructure, and smart glasses. Key Takeaways • Founder roles may need to change as the company grows. • Edge AI can reduce how much personal data needs to leave a device • Low power computing expands where AI can operate. • AI tools are changing engineering work from coding toward architecture and design. Key Moments 01:57 Going directly from a PhD program into a startup 06:42 Why Scott moved from CEO to CTO 10:40 Smart dust and Ambiq’s original vision 13:43 Why AI is moving beyond the cloud 17:52 Privacy, security, and processing data locally 20:04 Industrial, medical, and smart glasses use cases A Moment Worth Pulling Out “Be present where your feet are.” Follow The Tech Trek for more conversations with the people building and operating modern technology companies.

    From Smart Dust to Edge AI: Building Intelligence Everywhere

  4. Sep 22

    Early Stage AI Investing: Moats, Expertise, and Founder Anti Patterns

    Building an AI product is getting easier. Building an AI company that lasts is not. Itamar Novick, Founder and General Partner at Recursive Ventures, joins The Tech Trek to explain what he looks for when investing at the earliest stages of AI companies. The conversation covers how lower development costs could change venture funding, why subject matter expertise matters more as software becomes easier to build, and what actually creates defensibility when competitors can move quickly. Itamar also shares how Recursive Ventures thinks about founder anti patterns. Rather than trying to copy the paths of successful startups, he argues that founders can improve their odds by recognizing common mistakes that repeatedly create unnecessary risk. Key Takeaways • AI may let companies reach scale with much less outside capital. • Subject matter expertise matters more when building software is no longer the main barrier. • Proprietary data, feedback loops, hardware, and exclusive access can create stronger moats. • Founders can reduce risk by learning to recognize repeatable startup mistakes. Episode Highlights 00:38 What Recursive Ventures looks for in early AI companies 05:42 How AI could change the amount of capital startups need 10:04 Why subject matter expertise is becoming more valuable 12:02 What creates an AI moat when software is easy to copy 17:47 Why studying failure can be more useful than copying success 23:13 How AI could reshape venture investing itself Follow The Tech Trek for more conversations with founders, investors, and technology leaders building what comes next.

    Early Stage AI Investing: Moats, Expertise, and Founder Anti Patterns

  5. Sep 17

    AI Agents, Engineering Workflows, and the Cost of Being Wrong

    AI coding agents can produce software faster, but they do not replace the judgment needed to understand the system. Shaun Patterson, CTO at Titan, joins The Tech Trek to discuss how agentic coding is changing problem solving, development workflows, project management, and technical hiring. Shaun explains why engineers still need a strong mental model of the systems they are building. AI can generate code, reproduce bugs, research implementation options, and automate repeated debugging work. But it can also keep working on the wrong problem long after a human debugger would have found the answer. The conversation also gets into a bigger shift in software delivery. If agents can work across much larger pieces of a project, engineering teams may move from managing work at the story level to working at the epic level. Key Takeaways • AI speeds up implementation, but engineering judgment still matters. • Repeated debugging work can become reusable agent skills. • Faster implementation lowers the cost of testing different technical approaches. • Hiring increasingly needs to measure how engineers work with AI. Highlights 02:08 Why AI can abstract work, but not engineering wisdom 06:04 Turning repeated debugging sessions into reusable agent skills 09:47 Why faster development may change traditional project management 12:42 Moving engineering work from stories to epics 16:19 Where agentic coding still creates problems 19:29 How Titan evaluates engineers who use AI One Line That Stuck “It abstracts your thinking, but it doesn’t abstract your wisdom.” Follow The Tech Trek for more conversations with the people building and leading technology companies.

    AI Agents, Engineering Workflows, and the Cost of Being Wrong

  6. Sep 15

    AI Agents, Identity, and the Security Gap

    AI agents create a different security problem from traditional software. They can operate at software speed and scale while behaving in ways that are much less predictable. Ev Kontsevoy, CEO and cofounder of Teleport, joins The Tech Trek to discuss what happens when companies deploy agents into security systems designed around humans, applications, and relatively static organizational structures. The conversation gets into authentication, impersonation, infrastructure identity, access control, and a harder question: what actually defines the identity of an AI agent when its model, memory, skills, and capabilities can change? Ev also explains why the combination of speed, scale, and unpredictable behavior changes the risk of mistakes. Later, he explores the tension between agents being useful because they can do new things and security systems that often depend on predictable behavior. Key takeaways • Agent identity gets harder when memory, models, and capabilities can change. • Traditional access controls often reflect static organizational structures. • Agents combine software speed with behavior that can be difficult to predict. • Useful agent behavior can conflict with security systems built around anomaly detection. Highlights 00:41 What Teleport does and why infrastructure identity matters 08:37 Why companies may already be behind on agent security 13:47 Why an electronic account is not the same as identity 15:11 What actually defines the identity of an AI agent? 22:49 Why agent speed and unpredictability change the risk equation 29:04 The conflict between useful agent behavior and anomaly detection One Line That Stuck “Agents are just as unpredictable as humans, but they are way, way, way faster.” Follow The Tech Trek for more conversations with the people building and leading technology companies.

    AI Agents, Identity, and the Security Gap

  7. Sep 10

    Can AI Agents Help One Founder Run a Company?

    AI agents are moving beyond helping with individual tasks. The bigger question is how much of a company they can actually run. Ben Cera, founder of Polsia, joins The Tech Trek to discuss what happens when AI handles engineering, support, marketing, research, and other parts of company execution. Ben explains how Polsia uses specialized agents that can take direction from a founder or decide what to work on autonomously. He also shares how he uses similar systems inside his own company, which he says has more than 10,000 paying customers and is approaching a $10 million run rate without a traditional full time team. The conversation gets into where humans still matter, why AI mistakes may be acceptable, and how faster execution changes the way founders test ideas. Key Takeaways • AI agents can move from completing tasks to coordinating entire business functions. • Faster execution gives founders quicker feedback on what works and what does not. • Humans still matter most for judgment, direction, and authentic storytelling. • Autonomy requires accepting some mistakes instead of demanding perfect AI output. Highlights 02:43 What changes when AI becomes part of how a founder operates 04:03 Turning customer support into a system that can also fix problems 06:19 Running a company without a traditional full time team 13:47 Why founder judgment still matters when AI gives the options 18:49 How specialized agents coordinate engineering, marketing, and outreach 22:10 What happens when autonomous AI makes the wrong decision One Line That Stuck “You have to trust your gut and you have to be willing to make mistakes.” Follow The Tech Trek for more conversations with the people building and leading technology companies.

    Can AI Agents Help One Founder Run a Company?

  8. Sep 8

    How AI Is Changing Engineering Workflows and Software Teams

    AI coding agents can help engineering teams ship more code. But the bigger change may be what engineers spend their time doing. Viren Baraiya, Co-Founder and CTO of Orkes, joins The Tech Trek to discuss how AI is changing workflow orchestration, engineering productivity, project delivery, and hiring. As agents take on more implementation work, engineers are spending more time on design, architecture, review, and verification. Viren shares how his team measures the return on AI through product velocity, stability, and the ability to build things that previously required more time or outside resources. He also explains how Orkes manages model costs by using stronger models for difficult reasoning and smaller models for implementation. Key Takeaways • Coding agents increase output, but they also increase the need for verification. • Engineers are shifting from pure implementation toward design, review, and orchestration. • Repeated AI tasks can become reusable workflows that reduce ongoing token usage. • Hiring should test how engineers actually work with agents, not just manual coding. Highlights 01:21 Why agents are workflows and where orchestration fits into AI systems 05:19 How AI changed feature velocity, testing, and customer engineering at Orkes 07:44 Measuring AI ROI through velocity, stability, and new product capabilities 09:19 Why engineers increasingly look more like tech leads 12:56 Turning repeated AI requests into reusable workflows to reduce token usage 19:34 Why Orkes changed engineering interviews to include agentic coding One Line That Stuck “That has become a more important skill than actually writing the code now.” Follow The Tech Trek for more conversations with the people building and leading technology companies.

    How AI Is Changing Engineering Workflows and Software Teams
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5
out of 5
79 Ratings

About

The Tech Trek is a podcast about how founders, operators, and technology leaders build and scale technology companies. Each episode explores the decisions behind building products, teams, and technical organizations, with conversations spanning engineering, AI, data, product, hiring, leadership, and growth. Guests share what they are building, what they are learning, and how they are navigating the challenges that come with turning technology into a successful company.

Information

  • Creator
    Elevano
  • Years Active
    2020 - 2026
  • Episodes
    707
  • Rating
    Clean
  • Copyright
    © Elevano
  • Show Website
    The Tech Trek

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