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Code Story: Insights from Startup Tech Leaders

Code Story: Insights from Startup Tech Leaders

By: Noah Labhart - Startup Founder & CTO
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Code Story is a startup podcast for technical founders building and scaling software products.

Each episode features SaaS founders, engineers, and product leaders sharing how they built their product, found product-market fit, and navigated early-stage growth.

We explore:

  • Early engineering decisions and MVP development
  • Landing the first customers
  • Pricing and go-to-market experiments
  • Scaling challenges and infrastructure bottlenecks
  • Hiring the first team
  • Lessons learned from growing a startup

From first commit to first scale, Code Story focuses on the critical transition from building software to building a scalable business.

If you’re a founder, engineer, or product leader interested in SaaS, startups, and scaling technology companies, this podcast breaks down how great products are built — and how they grow.

© 2026 Code Story Career Success Economics Leadership Management & Leadership Politics & Government
Episodes
  • S12 Bonus: The Dashboard Mirage: Why Aggregate Metrics Hide Revenue Leaks and the Rise of Autonomous, Agentic Analytics with Bhaskar Sunkara, Founder & CEO of Bicycle AI

    S12 Bonus: The Dashboard Mirage: Why Aggregate Metrics Hide Revenue Leaks and the Rise of Autonomous, Agentic Analytics with Bhaskar Sunkara, Founder & CEO of Bicycle AI
    Jul 16 2026

    Bhaskar Sunkara grew up in Delhi, India, and moved to the states when he started working. He has lived in San Fransisco for several decades now, and has spent a lot of his professional life building systems (infrastructure, observability and now, analytics). His prior startup, AppDynamics, was eventually acquired by Cisco. In general, he stays curious about how things work, and likes to deconstruct systems to figure out how they work. Outside of tech, he is a big sports fan, enjoying football, baseball, cricket and basketball. In fact, he grew up watching Michael Jordan and the bulls.

    Bhaskar noticed that business teams were drowning in dashboards, and as such, were not sure how to take the next steps in the business. He and his team realized that what people needed was not a retroactive view, but a proactive one - something more akin to a 24x7 analyst.

    This is the creation story of Bicycle AI.

    Sponsors

    • Unblocked
    • TECH Domains
    • Mezmo
    • Braingrid.ai

    Links

    • https://bicycle.ai/
    • https://www.linkedin.com/in/bhaskarsunkara/


    Our Sponsors:
    * Check out Cash App and use my code CASHAPP10 for a great deal: https://cash.app
    * Check out Plaud AI and use my code CODESTORY for a great deal: https://plaud.ai


    Advertising Inquiries: https://redcircle.com/brands

    Privacy & Opt-Out: https://redcircle.com/privacy
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    30 mins
  • The AI Control Loop: The Enterprise AI Accountability Moment – with Shayne Higdon of Wallarm

    The AI Control Loop: The Enterprise AI Accountability Moment – with Shayne Higdon of Wallarm
    Jul 15 2026
    Today, we are dropping our final episode in our series The AI Control Loop, How enterprises govern the AI they've already deployed - sponsored by our friends at Wallarm.Wallarm is the AI Control Platform for Enterprise AI, protecting every AI workload, API, and application in production, giving CISOs the governance they need and CIOs the speed they demand. Organizations choose Wallarm for a complete inventory of APIs, AI agents, and AI apps, patented AI/ML-based threat detection and blocking that operates at production traffic speeds.In our final episode, we are joined by Shayne Higdon, Wallarm CEO, who closes the series by examining what the accountability moment demands from enterprise leaders, what a mature AI governance model needs to prove rather than promise, and what the next 12 to 24 months look like for organizations that get this right.QuestionsWhy is now the accountability moment for enterprise AI?What has changed between the early days of AI experimentation and today's enterprise AI deployments that makes accountability such a pressing issue?When we talk about AI accountability, what does that actually mean in practical terms? Are we talking about visibility, auditability, enforcement, ownership—or all of the above?As organizations race to deploy AI, how should CIOs balance the speed of transformation with the responsibility to govern it effectively?Why are traditional governance and security models struggling to keep pace with the way AI is being adopted across the enterprise?Given those challenges, how should boards and executive teams evaluate whether their organizations are truly ready to scale AI safely and responsibly?And once an organization believes it's ready, what does a mature AI governance model actually need to prove - not just promise?From an operational standpoint, how do capabilities like discovery, runtime monitoring, and enforcement come together to create a closed-loop approach to AI accountability?Stepping back and looking across this entire conversation, what's the one mindset shift every enterprise leader needs to make when it comes to AI security and accountability?And finally, as listeners think about what's ahead, what should they expect the future of AI security and accountability to look like over the next 6, 12, or even 24 months?Linkshttps://www.wallarm.com/https://www.linkedin.com/in/shaynehigdon/Full AbstractAbstract: Join Shayne Higdon, Wallarm CEO, for this episode, which closes the series by examining what the accountability moment demands from enterprise leaders, what a mature AI governance model needs to prove rather than promise, and what the next 12 to 24 months look like for organizations that get this right.AI deployment is not waiting for governance to catch up. Across most enterprises, the gap between how fast AI is being adopted and how well it is being governed is widening every quarter. CIOs and CISOs are not debating whether to govern AI. They are trying to figure out how, under real organizational pressure, with tools and frameworks that were built for a different threat model.That pressure is coming from every direction at once. Boards want AI transformation to move fast. Regulators want documented evidence that it is under control. Security teams want runtime visibility and enforcement capabilities that most of their current tools do not provide. And the AI systems themselves are not waiting: they are accessing data, calling external services, and making decisions continuously, in ways that after-the-fact governance cannot meaningfully constrain.This is the accountability moment. Not because the risk is new, but because the consequences of undermanaged AI are now concrete enough to land on a board agenda, an audit report, and a regulatory deadline at the same time. What accountability actually requires in practice is the full AI control loop: knowing what AI is running across the enterprise, seeing what it is doing at runtime, enforcing policy before damage compounds, and generating continuous evidence that the governance is real and not retroactive. Organizations that can demonstrate all four are in a fundamentally different position than those still assembling audit evidence from spreadsheets the week before a review.Our Sponsors:* Check out Cash App and use my code CASHAPP10 for a great deal: https://cash.app* Check out Plaud AI and use my code CODESTORY for a great deal: https://plaud.aiAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy
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    27 mins
  • S12 E27: The Real-Time Scaling Tax: Why High-Volume WebSockets Kill Monolithic Performance and How AnyCable Decoupled the Real-Time Layer with Irina Nazarova, CEO of Evil Martians

    S12 E27: The Real-Time Scaling Tax: Why High-Volume WebSockets Kill Monolithic Performance and How AnyCable Decoupled the Real-Time Layer with Irina Nazarova, CEO of Evil Martians
    Jul 14 2026

    Irina Nazarova grew up in Russia, and has lived in Portugal, Turkey, and now, San Francisco. She got a computer science degree, but felt like an imposter in the dev world. She went on to get an economics degree, and went to work for JP Morgan. Feeling little reward from her work, she read the lean startup and jumped out to build her own, and eventually joined Evil Martians. Outside of tech, she is a person who loves hiking, traveling, and old school film and photography. She enjoys working with old film, where there is high touch, and you have a limited number of takes.

    Irina is the CEO of Evil Martians, a well known design and engineering consultancy. During the time of the company, she and the team noticed that websocket solutions don't guarantee delivery. They decided to build a new solution, one that does guarantee delivery, through automatic recovery of messages during connection issues.

    This is the creation story of AnyCable by Evil Martians.

    Sponsors

    • Unblocked
    • TECH Domains
    • Mezmo
    • Braingrid.ai

    Links

    • https://anycable.io/
    • https://evilmartians.com/
    • https://www.linkedin.com/in/nonconstant/


    Our Sponsors:
    * Check out Cash App and use my code CASHAPP10 for a great deal: https://cash.app
    * Check out Plaud AI and use my code CODESTORY for a great deal: https://plaud.ai


    Advertising Inquiries: https://redcircle.com/brands

    Privacy & Opt-Out: https://redcircle.com/privacy
    Show More Show Less
    38 mins
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