Code Story: Insights from Startup Tech Leaders

Sharad Kumar lives in Pleasanton, California with his wife and 2 kids. He enjoys playing all musical instruments, and spending time with his family. He has a 2 year old daughter, and a 14 year old son into robotics. He is also passionate about giving back to the community, through their company foundation.Harshit Omar lives in San Francisco, and is married with a 4 year old son. He used to be a street racer in his college days, loving fast cars and taking risk. Nowadays, he is a big marvel and comic book fan, along side his son. In fact, his son thinks he is Captain America, regularly wielding his shield and mask.A fun fact about both of these gentlemen: this is their third company to work together in, their second startup, and their wives are sisters. So they are connected by wives, and united by startups.In their previous startups, Sharad was leading sales and ops and Harshit was leading on the product side. When the company got acquired, it took them 8-9 months to integrate to a different cloud provider. They realized the model was broken, requiring expensive consulting services, and not convenient at all - and they wanted to figure out a better way.This is the creation story of Fluidcloud.SponsorsUnblocked (https://getunblocked.com/codestory)TECH Domains (https://get.tech/codestory)Mezmo (https://mezmo.com/codestory)Braingrid.ai (https://braingrid.link/code-story)Alcor (https://alcor.com/podcast)Equitybee (http://codestory.co/equitybee)Terms and conditions: Equitybee executes private financing contracts (PFCs) allowing investors a certain claim to ESO upon liquidation event; Could limit your profits. Funding in not guaranteed. PFCs brokered by EquityBee Securities, member FINRA.Linkshttps://www.fluidcloud.com/https://www.linkedin.com/in/sharadkumar123/https://www.linkedin.com/in/harshito/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Yoni Avital lives in Tel Aviv, Israel, with his wife and 3 older children. The oldest kid is a boy, so Yoni and he try to see as many football games as possible. He enjoys shopping with this girls, though it's cause he is their Dad, not because he enjoy shopping. He likes to travel, hike, and enjoys a nice white wine in warmer weather. His most memorable hike was at Yosemite, when he started at 4 am and came across a lot of wildlife.Yoni was in the virtual desktop space in the past. What he and his team realized was that troubleshooting these virtual experiences were incredibly complicated. They started to build an enterprise task manager, to centralize a task management UI to control the endpoints. When customers started asking to use it daily, Yoni figured out they had something unique.This is the creation story of ControlUp.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.controlup.com/https://www.linkedin.com/in/yoavital/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we have a special guest on the Code Story podcast - Patrick Vuong, Director of Product at Moderne. Moderne is the agent tools company, building the. Knowledge, discovery and execution tools that AI agents rely on - so they can operator faster, more accurately, and at far lower cost.In today's episode, Patrick is going to tell us about the company, and how Moderne is enabling developers to build software faster, and with the best context - using agents and agent tools. Their approach to semantic models produce deterministic over probabilistic, or inference driven, tools, which for this engineer/host, has been a point of skepticism for AI since the beginning.QuestionsTell me and my audience a little bit about you.What is Moderne?Moderne is enabling developers to operate software systems at the speed of agents. Tell me about this product suite.Why do Agents need tooling? Where do we see AI in ROISomething jumped out at me... you mentioned you are not only building tooling for agents that are deterministic.As we peer into tech stacks across the industry, where does Moderne fit?OK so this is clearly a pivot for Moderne. With this, who are your customers now?What does the future like for your product - what you offer - and your team?For you personally, you are entering into a new chapter with Moderne. What makes you most excited, going from Microsoft to entering the startup world with the company?In your journey, who has influenced the way you work? Tell me about a person, or many persons, or something you look up to and why.So you worked at Microsoft for 8 years, and are now transitioning to Moderne. Say you were getting on a plan and sitting next to someone about to make this same transition - what advice would you give them?SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.moderne.ai/https://www.linkedin.com/in/vuongpatrick/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

We have a special return episode, by our good friend Rickard Hansson. Rickard joined us previously on the podcast in Season 8 to tell the creation story of Weavy - collaboration infrastructure for serious builds. Today, he makes a follow up visit to tell us all about Gainable, his new project - which removes data and engineering from being the middle man, and enables your team to build the apps they need now.Questions;Last time we talked in Season 8, you were building Weavy. Whats happened since we last talked with that company?Tell me about Gainable - give me the pitch there, and tell me why this is the right approach to using AI.Most AI builders wire straight to a frontier model and wait for the next release to fix the gaps. I didn't. Where does the model actually sit in Gainable product, and why only there?Why is an app factory that is deterministic important? Dig into that.You use the term "free-range coding".. what does this mean? Unpack the phrase for us.You point out that tokens still appear to be heavily subsidized to me. What do you mean by that, and what happens to all these AI products when that ends?We've all read the headlines - Fable 5 got switched off by the government for 18 days. Why do you see this as a turning point, not a footnote?You suspect flat subscriptions for the top models are done, and it all drifts to credit-based. What signal are you seeing that tell s you this?If the model is a commodity everyone rents, where's the moat?What is next for Gainable, and how can someone get started using the platform?SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.gainable.dev/https://www.weavy.com/https://www.linkedin.com/in/rickardh/https://codestory.co/podcast/bonus-rickard-hansson-weavy/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Virginia Szepietowski grew up in the UK outside of London, and now lives in Alabama. She's had a winding path to her current venture, including body building, triathlons, law, and entrepreneurship. She comes from a family of entrepreneurs, who are deeply ambitious, tenacious, and deeply humble. She finds the feeling of a deep safety net from her family, and she pursues her adventures. Outside of tech, she is married to her now co-founder. She is still a competitive body builder, and likes to push herself to the limit.Through a series of life events, Virginia got interested in water treatment. She started discovering the world of wastewater operators, and the fact that they were the last line of defense before toxic wastewater moved into our waterways (rivers and such). Using AI, her and her team started to build a platform for these operators to quickly detect organisms in these water streams.This is the creation story of Nyad AI.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://nyad.ai/https://www.linkedin.com/in/virginia-szepietowski/Timestamps0:00 Intro and episode teaser on automating biology in critical clean water infrastructure1:49 Guest introduction: Virginia Szepietowski's background and path to founding Nyad AI2:45 Understanding the hidden biology behind municipal and industrial wastewater treatment4:10 The core problem: Why manual microscope sampling creates dangerous operational blind spots6:05 Origin story: Translating computer vision research into industrial water automation8:30 How Nyad AI's automated hardware samples and analyzes live microorganisms in real time11:15 Overcoming physical hardware engineering hurdles in harsh, high-humidity environments14:00 Preventing biological plant crashes and saving millions in compliance penalties17:30 Addressing the labor shortage: Supporting the next generation of water operators with AI21:00 Scaling AI hardware deployments across municipal and industrial facilities24:15 The future of automated biology in global water security and environmental protection27:00 Closing thoughts and how to connect with Virginia Szepietowski and Nyad AICheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Richard Luna grew up in New York, never living more than 35 from where he grew up. He is a self proclaimed super nerd, and has been one since he was 13 - at which point, he started coding on an HP calculator. He's always been fascinated to know how things work, and how patterns repeat - which he has observed in the industry throughout the years. Outside of tech, he has 2 kids, one of which is in the business with him. He's an avid cyclist, traveling on average, 120 miles a week.Richard has been a life long technologist, doing everything from desktops, to coding, to hosting. When he and his team saw the limits of what hosting can do, they dove into developer operations (DevOps), and found where they could add the most value - through SaaS infrastructure.This is the creation story of Protected Harbor.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://protectedharbor.com/https://www.linkedin.com/in/richardluna/Timestamps0:01 Teaser on solving complex database report bottlenecks beyond standard SQL servers0:47 Show intro and setting the stage for application-aware infrastructure1:32 Host intro: How Richard Luna established application-aware infrastructure1:49 Guest introduction: Richard Luna's background, coding at age 13, and cycling 120 miles a week2:21 The career path from desktops, coding, and traditional web hosting to DevOps and SaaS infrastructure2:41 Origin story: The creation of Protected Harbor2:48 Defining application-aware infrastructure and why traditional hosting reaches a hard ceiling4:10 Why "infinite compute" fails when underlying database architecture and queries are broken6:05 Moving beyond basic server ping tests to deep application transaction monitoring8:30 The case for "boring" IT: Prioritizing stability, predictability, and uptime over hype11:15 Strategic trade-offs in hybrid cloud setup and managing hardware accountability14:00 Aligning MSP incentives with client business outcomes and application performance17:30 Common pitfalls in legacy system cloud migrations21:00 The role of operational discipline in modern cybersecurity and IT governance27:00 Where managed infrastructure services are heading and closing thoughtsCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Danny Gal was born and raised in the UK, and now lives outside of London. He attended University in Nottingham... yep, the same one from Robin Hood. He LOVES challenges, and not just any challenges - the hard ones. He is done Iron Man competitions, ultra marathons, climbed Mount Kilimanjaro, and jumped out of a perfectly good plane, to name a few. He loves doing them once... and then never again. He's got 2 small kids, and believes in work hard, play hard.Danny has worked in many roles in the past, across enterprises and the like. What he found most difficult was scaling himself. He got to talking with his now co-founder about building something around the idea of scaling oneself, and took it to some businesses to validate it. Once he saw them get excited about it, he figured they were onto something.This is the creation story of Proteams.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://proteams.com/https://www.linkedin.com/in/dannygal/Timestamps1:49 Guest introduction: Danny Gal's background, endurance challenges, and career journey2:50 The core problem: Why traditional freelance marketplaces fail enterprise workflows4:10 Origin story: Solving the bottleneck of "scaling oneself" in leadership5:45 Validating the managed fractional team model with early enterprise clients7:20 Self-serve bidding vs. managed delivery teams: Understanding the structural shift9:30 Building a software-enabled harness for global engineering talent12:15 How Chief Procurement Officers should structure external workforce strategies15:00 Overcoming compliance, IP, and security hurdles in enterprise talent integration18:10 Balancing speed, quality, and accountability in remote team management20:30 Closing thoughts and where to connect with Danny Gal and ProteamsCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Sid Dixit is originally from central India, and came to the states for college. He is a technologist and builder at heart, serving in leadership roles across major companies. He has built and managed a fleet of satellites, built robots at Amazon, worked at Microsoft on surface tablets, and finally, at Google working on Android. Outside of tech in lives in the Bay Area with his wife and kids. He loves water sports, especially sailing. He spent 10 years in San Diego, and stumbled on the sport.Sid's current company started in 1999, and was acquired in 2010. A few years ago, Sid joined the company, at a time when the company was wanting to rebuild its network from the ground up - starting with a powerful index.This is Sid's creation story at iTradeNetwork.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.itradenetwork.com/https://www.linkedin.com/in/siddharthdixit/Timestamps1:49 Guest introduction: Sid Dixit's career background across satellites, Amazon, and Google2:42 Overview of iTradeNetwork and its reach across North America's perishable supply chain4:04 The origin story of iTradeNetwork and why generic ERPs fail fresh food logistics5:45 Upgrading legacy software from Systems of Record to Systems of Intelligence6:37 The role of specialized AI agents: Forecasting, pricing, RFQs, and negotiations7:23 Solving outdated market data: Building a real-time produce commodity index8:55 Strategic MVP trade-offs: Narrowing focus to key commodities like strawberries and apples10:19 Using AI to harmonize unstructured vendor product descriptions15:00 Streamlining complex order intake workflows across buyers and sellers22:00 Quantifying the macroeconomic impact of supply chain speed on global food waste28:00 Future vision for AI agents in global supply chain management31:30 Closing thoughts and where to learn more about iTradeNetworkCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Emilie Schario grew up in New Jersey, outside of Newark, and attended college in the state. Currently, she lives in Columbus, Georgia, outside of Atlanta. She mentions she got into technology so she could easily follow her husband's career geographically, and has much success in the industry. Outside of tech, she is married with 3 boys (all 5 and under)... so there is a lot of wrestling in her household. She admits she is often quoted staying she does three things in her life - work, parenting, and if she is lucky, attends CrossFit 3 times a week. In fact, she finds a great sense of community in that world, and brings her kids with her to cheer her on.A year and a half ago, Emilie's current venture was started, to build the open source orchestrator (or "harness") for AI coding agents. Through some shuffle in the early team, Emilie joined and started in building the fastest AI coding app on the market.This is the creation story of Kilo.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://kilo.ai/https://www.linkedin.com/in/emilieschario/Timestamps1:49 Guest introduction: Emilie Schario's background and career journey2:51 Overview of Kilo Code as an open source agentic engineering harness3:14 Differentiating through model freedom and supporting 500 plus AI models3:58 Kilo Code founding story with Sid Sijbrandij and team history4:42 Defining the evolving MVP for AI coding tools in a fast-moving market5:25 The rapid shift from manual prompt engineering to autonomous loops6:19 Trade-offs and resource allocation: Deprecating the Kilo App Builder9:09 Modern AI product management: Why multi-year roadmaps no longer work10:19 Shifting PM responsibilities from tracking engineers to setting context13:00 The AI throughput illusion: Why expensive models don't equal shipped code17:00 Measuring true engineering output and productivity in the AI era21:00 Building resilient engineering cultures around AI coding platforms23:30 Closing thoughts and where to learn more about Kilo CodeCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

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.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://bicycle.ai/https://www.linkedin.com/in/bhaskarsunkara/Timestamps0:00 Intro and episode teaser on the limits of manual KPI monitoring1:49 Guest introduction: Bhaskar Sunkara's background and AppDynamics experience2:50 The core problem: Why revenue teams are drowning in dashboards3:53 Origin story: Shifting from reactive dashboards to proactive AI analysts4:36 Identifying target transactional verticals in retail, travel, and payments6:02 Building the MVP: The 1-year journey and defining core capabilities7:06 The three MVP pillars: Data connection, KPI definition, and dimensional search8:33 Strategic trade-offs: Choosing vertical focus over generic horizontal BI10:00 Harnessing LLMs and agentic AI for root-cause context15:00 Establishing single-source-of-truth KPI definitions across departments20:00 How AI agents integrate into existing enterprise data stacks25:00 The future of autonomous analytics and proactive decision-makingCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

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.Timestamps1:49 Guest introduction: Shayne Higdon's executive background and role as Wallarm CEO2:45 From experimentation to production: What triggered the enterprise AI accountability shift4:10 Why traditional CISO governance models fail to keep pace with autonomous AI agents6:05 Explaining the AI Control Loop: Discovery, visibility, enforcement, and evidence8:30 Moving from policy promises to continuous, runtime-proven governance11:15 Balancing innovation speed for CIOs with security mandates for CISOs14:00 Tackling Shadow AI and establishing a complete inventory of AI apps and APIs17:30 Runtime threat detection: Blocking prompt injection and data leaks at production speeds21:00 Board-level expectations and preparing for evolving AI regulatory frameworks24:15 What AI governance and security will look like over the next 12 to 24 months27:00 Closing thoughts and how to learn more about WallarmCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

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.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://anycable.io/https://evilmartians.com/https://www.linkedin.com/in/nonconstant/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Ramiro Roballos grew up in Buenos Aires, and 6 or 7 years ago, moved to Miami and now lives in Buffalo, NY. His path to entrepreneurship has been different, as he started out as a musician, and then an orchestra conductor for several years. He eventually got into building how companies, starting his own music school and his own orchestra. Eventually, he got his MBA, worked for McKinsey and some startups before doing his own. Outside of tech, he is married to a cellist, and keeps playing music for fun. He also enjoys Formula 1, and watches every change he gets.Ramiro went through the immigration process in the US, and was very disappointed in the quality of the service, given the importance of this process in determining a pillar life outcome. He felt there should be a better way, one that has excellent service and quality, and centralizes the expansive process into one platform.This is the creation story of Tukki.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://tukki.ai/https://www.linkedin.com/in/ramiro-roballos/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we are dropping another 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 today's episode, Craig Thomas, Sr. Solutions Engineer at Wallarm, returns to the show to dive into why runtime behavior is the critical blind spot, and what CISOs should demand if they want to move from policy to control.QuestionsSecurity teams are used to detecting incidents and responding after the fact. Why is that model becoming insufficient for AI-driven systems?Building on that, when we talk about response today, enforcement often means actions like restarting pods, rotating credentials, or shutting down services. Why can those measures come too late in an AI environment?So if traditional response isn't enough, why does AI behavior require controls that operate much closer to runtime?And when people hear "runtime enforcement," they may think of existing security controls. What changes when enforcement happens at the kernel level rather than only at the network, identity, or application layer?Can you make that tangible for us? What does it actually mean to revoke or contain a compromised AI session without disrupting the broader deployment?How does that kind of real-time containment change the risk equation for AI agents that have access to sensitive data, external services, or production workflows?With that in mind, what are some examples of AI behaviors that organizations should be able to stop immediately?Of course, security teams also don't want to become a bottleneck. How do organizations balance strong enforcement with the need to keep AI development and deployment moving quickly?And once organizations have the ability to discover, observe, and enforce AI behavior in real time, how does that change accountability at the enterprise level? What does good governance look like from there?Linkshttps://www.wallarm.com/https://www.linkedin.com/in/cu-craigthomas/Full AbstractThis episode examines what is actually missing in AI security today. Craig Thomas, Sr. Solutions Engineer at Wallarm, dives into why runtime behavior is the critical blind spot, and what CISOs should demand if they want to move from policy to control.CIOs and CISOs have moved past debating whether AI security matters. The question now is what to actually do about it, and most organizations are finding that their existing tools answer a different question than the one AI is asking.Traditional security tools were built around access: who can reach a system, what credentials they present, what traffic looks like at the perimeter. AI shifts the problem to execution: what a system does once it has access, whether that behavior matches what the business intended, and how you know when it doesn't. Most current tooling has no answer for that. It can tell you what is deployed and what is configured. It cannot tell you what your AI is actually doing at runtime, on whose behalf, or whether any of it violates the policies you thought were in place.That gap is where most AI security programs stall. There is no shortage of governance frameworks, compliance checklists, and vendor claims. What is missing is operational control: the ability to see AI behavior as it happens, enforce policy at runtime, and produce evidence that holds up when an auditor or a board asks for it. The four capabilities that define a closed AI control loop, discover, observe, enforce, govern, are well understood as a category. Getting all four working together in production is where the real work begins.Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

John Wright grew up in Arkansas, when his family moved from Wisconsin for his Dad's job. He was influenced heavy by his father, who became an entrepreneur with several successful exits. As a kid, he got to see the ups and downs, and how you ride the roller coaster of being a business owner. Outside of tech, he is an active sailor and certified instructor in yacht racing.Growing up with a family of wood workers, he also likes to build things and make stuff with his hands. Finally, he lives in sobriety and recovery from past addiction, and is active in this community of people.In the past, John and his team built a platform around email, which they sold in 2001 to a company that is now apart of Google. Post that, he started to noticed the proliferation of SMS in the messaging world, in similar patterns as to what email did - and they decided to build a platform to serve the enterprise in this capacity.This is the creation story of TrueDialog.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.truedialog.com/https://www.linkedin.com/in/johnnwright/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Ajay Kulkarni grew up in tech, as his father was a tech entrepreneur selling PC's in the early 80's. He went to college in MIT, and eventually founded a startup that was acquired by GroupMe (while it was being acquired by Skype... while they were being acquired by Microsoft). He's always been attracted to building things, so startups are right up his alley. Outside of tech, he is married with 2 young kids. He is a big exercise guy... he loves to run, swim and track his steps. Additionally, he loves music - to listen, and to play guitar, piano and drums.Ajay and his co-founder met 30 years ago at MIT. They reconnected after years of doing their own thing, starting to dig into the iOT world. In doing this, they built a database because they the best solution to store this data... and in doing so, they unlocked their next venture out of this necessity.This is the creation story of Tiger Data.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.tigerdata.com/https://www.linkedin.com/in/ajaykulkarni/Timestamps00:00 Accidental Database MVP00:41 Podcast Intro Setup01:34 Ajay Background02:50 Meeting Co Founder04:11 Why Tiger Data05:36 MVP Building TimescaleDB07:06 Postgres Not NoSQL08:50 Roadmap And Agents10:40 Hiring The Right Team11:59 Scaling As CEO13:23 Resilience And Pride14:36 Mistakes And Lessons17:33 Future Physical World19:18 Stoicism And Influence21:01 Advice Play Love Triumph23:54 Closing And CreditsCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we are dropping another 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 his follow up appearance on the Code Story podcast, Tim Ebbers, Field CTO at Wallarm, discusses why detection alone is insufficient for AI-driven systems, what real enforcement looks like at the runtime level, and what accountability becomes possible once all four stages are in place.QuestionsSecurity teams are used to detecting incidents and responding after the fact. Why is that model insufficient for AI-driven systems?What does “enforcement” usually mean today, and why can actions like restarting pods or rotating credentials come too late?Why does AI behavior require controls that operate closer to runtime?What changes when enforcement happens at the kernel level rather than only at the network, identity, or application layer?Can you explain what it means to revoke or contain a compromised AI session without touching the broader deployment?How does real-time blocking change the risk equation for AI agents that access sensitive data, external services, or production workflows?What kinds of AI behaviors should organizations be able to stop immediately?How do teams balance strong enforcement with the need to avoid slowing down AI development and deployment? Once organizations can discover, observe, and enforce AI behavior, what does accountability look like at the enterprise level?Linkshttps://www.wallarm.com/https://www.linkedin.com/in/tebbers/Full AbstractTim Ebbers, Field CTO at Wallarm, discusses why detection alone is insufficient for AI-driven systems, what real enforcement looks like at the runtime level, and what accountability becomes possible once all four stages are in place.Detection tells you what happened. It does not stop it. For most security incidents, that tradeoff is manageable. For AI systems that can access sensitive data, call external services, and trigger downstream actions at machine speed, the gap between detection and response is where the damage happens.The enforcement model most security teams operate today was built for a slower threat. Restarting pods, rotating credentials, and updating policies are all responses to something that has already occurred. Against an AI agent that can exfiltrate data, invoke a production workflow, or violate a compliance boundary in the time it takes to page an on-call engineer, that response model is not enforcement. It’s cleanup.Closing that gap requires controls that operate at the layer where AI behavior actually executes, not at the perimeter, not at the identity layer, not at the application boundary. Kernel-level enforcement changes what is possible: a compromised session can be revoked by user identity or trace ID, connections can be terminated at the workload level, and enforcement can happen without a pod restart, a deploy cycle, or any impact to the broader environment. That is what it means to complete the AI control loop. Discover what is running, observe what it is doing, enforce what it should not be doing, and govern with evidence that the enforcement worked. Organizations that can only do the first two are solving half the problem.Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Ahikam Kaufman spent most of his career in the Bay Area. After becoming a CPA, he started his career as CFO at a startup company. Over time, he has been giving multiple opportunities to not only serve finance, but serve business roles as well - which prepared him for his own entrepreneurial path. IE starting 3 companies and exiting one to Intuit. Outside of tech, he enjoys traveling the world, spending time with his family, and hiking. But, he notes that the demands of being a business owner limits the amount of time he spends in these things.Ahikam started to think about how automation can positively impact financial operations, specifically around managing data in the office of the CFO. After the first AI models were released, he got excited, realizing that these models would continue to get better and better, alongside operating with agency.This is the creation story of Safebooks.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://safebooks.ai/https://www.linkedin.com/in/ahikam-kaufman-688310/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Volodymyr Sydorenko lives in London, and collects mechanical keyboards. His most unusual hobby is that he does clay sculptures of characters, or random people at times. He has 2 cats, and likes to spend time outdoors. In fact, in 3 weeks time from this recording, he will traveling to Switzerland to do the Via Ferrata. To add to all of this, he has started to write children's books and hopes to publish them someday.Vitalii Sydorenko currently lives in Lisbon, Portugal. He is into sports, loves to hit the gym and regularly tracks his calories. Last year he started playing tennis and finds that he can't stop. He enjoy hiking, which is great in Lisbon. And in the past, he spent many years building startups, exiting, and also in venture capitalYou may have noticed that Volodymyr and Vitalii have the same last name... that is because they are brothers. As kids growing up, they did a lot of boxing together, as well as cling to classic films like Back to the Future.Fourteen years ago, Volodymyr got interesting in building solutions, and realized he could only get so far by himself... so he decided to build a team to deliver these solutions. Two years ago, Vitalii and Volodymyr started to consider all the of the shifts in the SDLC, and what that meant for the current business. Vitalii decided to bring his prior startup and VC experience and join the team.This is the creation story of Gearheart.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://gearheart.io/https://codestory.co/podcast/e6-jon-darbyshire-smartsuite/https://www.linkedin.com/in/gearheart/https://www.linkedin.com/in/vitalii-sydorenko-%F0%9F%92%AA%F0%9F%87%BA%F0%9F%87%A6-24b4ba35/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we are dropping another 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 this episode, Craig Thomas, Sr. Solutions Engineer at Wallarm, examines what rogue AI actually means in practice, where the risk materializes, and what it takes to move from detection to control.QuestionsWhen we say "rogue AI," what do we actually mean? Is it only malicious AI, or can legitimate systems become risky too?What are the most common ways AI systems drift outside intended boundaries? Once an organization understands what rogue AI looks like, where does that loss of control typically begin, and who is responsible for preventing it?How do shadow LLMs, unsanctioned agents, and unmanaged AI workflows create risk even when no attacker is involved? If AI drift often starts with normal business activity, where do shadow AI systems fit into that picture?Why can an AI action look legitimate in isolation but still create serious business, security, or compliance risk when viewed as part of a larger sequence of actions? As these shadow systems become more embedded in everyday workflows, why is it so difficult to recognize risk in real time?How do APIs, integrations, and connected systems amplify the impact of those seemingly legitimate actions? What changes once those actions begin flowing across APIs, business applications, and interconnected systems?What kinds of unexpected outcomes worry CIOs and CISOs most today when AI systems are operating across those interconnected environments? As that connectivity expands, what are security and business leaders most concerned about?And given those concerns, what does meaningful oversight actually look like when AI systems can act at machine speed? How should organizations distinguish between the experimentation they want to encourage and the unmanaged AI behavior they need to control? One challenge is balancing governance with innovation. How do organizations avoid slowing down AI adoption while still maintaining control?We know that many organizations can detect risky AI behavior after the fact. But if they can't stop it in real time, what critical gap still remains? Even with governance programs in place, many organizations are still operating reactively. In closing, what's the key difference between detecting AI risk and actually controlling it?Linkshttps://www.wallarm.com/https://www.linkedin.com/in/cu-craigthomas/Full AbstractIn this episode, Craig Thomas, Sr. Solutions Engineer at Wallarm, examines what rogue AI actually means in practice, where the risk materializes, and what it takes to move from detection to control.Not every AI threat starts with an attacker. Some of the most consequential AI risks organizations face today come from systems that are working exactly as designed, just not quite as intended. An agent that calls an API it was never supposed to reach. A workflow that exposes PII because nobody mapped the data path before deployment. A shadow LLM standing up in an AWS account because a developer needed to move fast and approval processes were slow. None of these require malicious intent to create serious business, security, or compliance exposure.Rogue AI is a broader category than most governance frameworks account for. It includes the unsanctioned, the unmonitored, and the unpredictable: AI systems that drift outside intended boundaries, take actions that look legitimate in isolation but create risk in sequence, and operate at machine speed in ways that make after-the-fact detection feel like a consolation prize. The gap most organizations have is not in detecting that something went wrong. It's closing the loop fast enough to matter.Meaningful AI governance requires more than policy and discovery. It requires the ability to observe AI behavior at runtime, understand what triggered each action and what it touched, and enforce boundaries before consequences compound. That closed AI control loop, from knowing what is running to seeing what it does to stopping what it should not, is the operational standard AI transformation demands. Most organizations are not there yet.Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Volodymyr Sydorenko lives in London, and collects mechanical keyboards. His most unusual hobby is that he does clay sculptures of characters, or random people at times. He has 2 cats, and likes to spend time outdoors. In fact, in 3 weeks time from this recording, he will traveling to Switzerland to do the Via Ferrata. To add to all of this, he has started to write children's books and hopes to publish them someday.Vitalii Sydorenko currently lives in Lisbon, Portugal. He is into sports, loves to hit the gym and regularly tracks his calories. Last year he started playing tennis and finds that he can't stop. He enjoy hiking, which is great in Lisbon. And in the past, he spent many years building startups, exiting, and also in venture capitalYou may have noticed that Volodymyr and Vitalii have the same last name... that is because they are brothers. As kids growing up, they did a lot of boxing together, as well as cling to classic films like Back to the Future.Fourteen years ago, Volodymyr got interesting in building solutions, and realized he could only get so far by himself... so he decided to build a team to deliver these solutions. Two years ago, Vitalii and Volodymyr started to consider all the of the shifts in the SDLC, and what that meant for the current business. Vitalii decided to bring his prior startup and VC experience and join the team.This is the creation story of Gearheart.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://gearheart.io/https://beyondthewow.iohttps://codestory.co/podcast/e6-jon-darbyshire-smartsuite/https://www.linkedin.com/in/gearheart/https://www.linkedin.com/in/vitalii-sydorenko-%F0%9F%92%AA%F0%9F%87%BA%F0%9F%87%A6-24b4ba35/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Tim Lidman lives in Denver, CO. He has had an unconventional path to being a Tech CEO. In fact, He moved from London to Sweden when he was 18... to try to be a heavy metal rock star, trying to make it big as a drummer. To earn extra income, he got into tech sales - which went really well. Eventually, he worked with WebEx (around the time it got bought by Cisco), for Success Factors (when they got bought by SAP), and then eventually, doing his own startup (which eventually got bought by Accenture). Outside of his professional life, he is married with 2 girls. From his music years, he extracts skills that drove his success to date, which is the ability to product development and execution down the same way you do music.In the days of his first startup, Tim's solution was used by consulting firms to power client engagement. Post exit, while overseeing things at Accenture, he noticed that the whole industry was powered by Microsoft files (PowerPoint, Excel, Word, etc.) - IE, driven manually. He started to wonder if he could codify the consulting process, to remove the manual burden.This is the creation story of Clyde.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://meetclyde.com/https://www.linkedin.com/in/timlidman/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we are dropping another 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.We all know that you can't secure what you can't see, which is why AI discovery is a first principle for AI security, but what's really required for AI discovery? It's more than just LLMs and agents. Today's episode is entitled AI Discovery isn't just AI, and joining us is Tim Ebbers, Field CTO at Wallarm. Tim and I discuss the real requirements for AI discovery, and why the connections between assets and infrastructure are part of the puzzle.QuestionsSecurity teams often say, “You can’t secure what you can’t see.” In the context of AI, what exactly do they need to see? What supporting infrastructure matters most when mapping AI risk, such as APIs, cloud services, Kubernetes workloads, data stores, identities, and external integrations?Where does shadow AI typically appear first inside an enterprise environment? How can it be prevented?How do relationships between assets change the risk picture? For example, why does it matter which API an agent can call or which data source a workflow can reach?What makes AI discovery harder than traditional application or cloud asset discovery? What are the similarities and differences?How should organizations prioritize what they find? Is every AI asset equally risky?What does “continuous discovery” mean in a world where AI services can be deployed, connected, or changed in minutes?Once an organization has visibility into its AI footprint, what’s next? What are the biggest gaps in today’s AI security programs?Linkshttps://www.wallarm.com/https://www.linkedin.com/in/tebbers/Full AbstractMost security teams know that you can't secure what you can't see. In the context of AI, that rule turns out to be a lot harder to satisfy than it sounds.AI discovery isn't just a matter of cataloging your LLMs and agents. The real picture includes the APIs those agents call, the data sources they reach, the infrastructure they run on, and all the AI that got deployed without anyone telling security. Building that picture requires understanding relationships, not just inventories, because risk doesn't live in assets in isolation. It lives in what those assets can do together.In this episode, Tim Ebbers, Field CTO at Wallarm, examines what a complete AI control loop actually requires at the discovery stage: what needs to be visible, why the connections between assets change the risk calculation, where shadow AI tends to appear first and how it becomes unmanaged risk, and what makes AI discovery structurally different from traditional cloud or application discovery. It also looks at what organizations should do once discovery is in place, and where the biggest gaps remain in AI security programs today.If your team is building toward continuous AI governance, this is where that work starts.Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Gregory M. Kurtzer is a veteran open-source pioneer, technologist, and entrepreneur with over 25 years of experience in high-performance computing (HPC) and large-scale enterprise infrastructure. He first gained widespread industry prominence as the co-founder of CentOS Linux, which grew into one of the world's most ubiquitous enterprise operating systems, and he later created other foundational open-source projects like the Warewulf cluster management toolkit and the Singularity (now Apptainer) container system.In 2020, Gregory founded his current venture, with the goal of modernizing infrastructure stacks for the cloud and AI era. He and his team recognized that traditional enterprise infrastructure was too fragmented and ill equipped to handle the next generation of data intensive computing.This is the creation story of CIQ.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://ciq.com/https://rockylinux.org/https://www.linkedin.com/in/gmkurtzer/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we are continuing our series, entitled Developer Chats - hearing from the large scale system builders themselves.In this episode, we are talking with Pavel Shchekotov, Founding Engineer of specializing in voice-first, conversational AI products. Pavel is going to take us through his experience as an agency founder, leading into building voice driven, consumer AI.QuestionsToday you're building AI-native consumer products around conversational interfaces and user engagement. How has that journey shaped the way you think about product engineering?What did those agency years teach you about product development that most engineers never learn?What convinced you that voice could be the primary interface rather than just another feature?What are the hardest engineering and product challenges that emerge when conversation itself becomes the product?What’s one problem that seemed trivial on paper but became surprisingly difficult at scale?What did you learn about technology adoption, trust, and user behavior from building for a demographic that much of the tech industry tends to ignore?How do you decide whether a startup problem should be fixed, optimized, or completely reimagined?What does being a Founding Engineer actually look like day-to-day, and how is it different from being a senior software engineer?Where do you think people are overestimating AI today, and where are they still underestimating it?Looking forward three to five years, what do you think the most important category of AI-native consumer product will be—and what capabilities will those products need that don’t exist yet?SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.linkedin.com/in/pavel-shchekotov/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Sushma Vadlamannati is originally from India, and moved to the states over 25 year ago to pursue her bachelors in at Texas Women's University. She comes from a nontraditional founder background, spending 15 years in the Fortune 100 companies, leading large programs with large budgets. About 5 years ago, she started advising startups and angel investing, which led her into the startup world. Outside of tech, she has 2 daughters and loves to do arts and crafts. In fact, she uses scrap material she finds at home to build miniature scenes and creations.Sushma is very familiar with the startup scene in Texas. As such, she has a keen understanding of the recurring problems for startups - the local talent pool. In addition to this, she noticed the disconnect between schools, workforce opportunities, and students/workers themselves. She decided to pivot into to building this intelligence layer.This is the creation story of zScale.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://zscalecapital.com/https://www.linkedin.com/in/sushma-vad/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we are kicking off a new series entitled 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.Today's episode is entitled AI Security is API Security, and joining us is Tim Erlin, VP of Product Marketing at Wallarm. We discuss the foundational link between AI security and API security, digging into the role that APIs play in the dev, deployment, and operations of AI. We explore how they contribute to the risk profile of AI transformation projects, and how securing APIs is critical for successful AI transformation.QuestionsWhen people hear “AI security,” they often think first about models, prompts, or training data. Why do you argue that AI security starts with APIs?Where do you see organizations underestimating API risk as they move AI projects from pilot to production?How does the rise of AI agents change the stakes for API security compared with traditional application architectures?What are the most common API security assumptions that break down once AI systems begin taking action autonomously?Wallarm’s ThreatStats research points to APIs as a major overlap point for AI vulnerabilities and exploited vulnerabilities. What does that tell us about where attackers are likely to focus?How should security leaders think differently about authentication, authorization, and API abuse when the “user” may be an AI agent rather than a human?What is one practical step teams can take today to strengthen API security before AI adoption expands further?Once you accept that AI security depends on APIs, what do organizations actually need to discover before they can protect it?Linkshttps://www.wallarm.com/https://www.linkedin.com/in/tim-erlin/Full AbstractIn the first episode of the AI Control Loop series, Tim Erlin, VP Product at Wallarm, examines why AI security and API security are the same problem approached from different angles, and what organizations need to discover before they can protect either one.Every AI model needs data to act on. Every AI agent needs services to call. Every AI workflow needs integrations to function. The connective tissue running through all of it is APIs, which means the security posture of any AI system is inseparable from the security posture of the APIs underneath it.That link is not theoretical. APIs are already the most targeted attack surface in enterprise environments, and AI is making that problem significantly larger. Agents that act autonomously on behalf of users do not just consume APIs the way traditional applications do. They discover them, invoke them dynamically, chain them across workflows, and do all of it at a speed and scale that makes human review impractical. The authentication assumptions, rate limiting strategies, and abuse detection models that worked for human-driven API traffic were not designed for this, and the gaps are not subtle.Most organizations moving AI from pilot to production are underestimating how much of their AI risk surface is actually API risk surface. Shadow APIs that were never inventoried, overpermissioned integrations that made sense for a human user but not for an autonomous agent, authentication patterns that cannot distinguish a legitimate AI session from an abused one. Securing AI at the foundational level means answering the API question first: what APIs does the AI touch, what can it do through them, and what would an attacker be able to reach if any part of that surface were compromised.Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Alex Bowcut is from Salt Lake City, Utah originally, but has been in the Bay Area for the last 4 years. He's always been interested in computers, and was in middle school when smartphones were blooming. He took part in jailbreaking gadgets and such, and all of these things led to a natural interest in CS, mathematics - and eventually, startups. Outside of tech, he is married with 2 Australian shepherds. He and his wife enjoy hiking with the dogs, and skiing - unfortunately, without the dogs.Alex was approached by the founder of his current venture. He was approached while he was working at another startup, to tackle the creation of AI control and scaling within the company internally. When he joined, he immediately started changing the game in creating the initial version of their assessment model, TRAM.This is Alex's creation story at Sphere.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.getsphere.com/https://www.linkedin.com/in/abowcut/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Ankit Dheendsa is a Canadian, born and raised, living outside of Toronto today. He claims he is fortunate to have a great ecosystem of professionals and mentor sin his area, to help advise him through thick and thin. When he was younger, he was inspired to pursue building things after he watched Iron Man for the first time. Outside of tech, he is an avid boxer and kickboxer. He loves to work out and train, but when he's away from the mat, he likes to read lots of books.Ankit and his team quickly realized that although the advent of AI was exciting, hallucinations within LLMs area a big problem. They started to dig into how to lower and/or eliminate hallucinations, and ensure that the LLMs only hold onto the most important data. And they landed on a powerful approach to vector size reduction.This is the creation story of Morphos AI.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.morphos.ai/https://www.linkedin.com/in/ankit-dheendsa/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Marco Benitez lives in Naples, Florida. In the past he lived in Miami, but found Naples much more family friendly. He is originally from Mexico, along with many of his family members and businesses. Outside of tech, he is married with 2 kids. As a family, they love to go outside, be outdoors and visit the great beaches around Florida. In addition, Marco is a black belt in Taekwondo, and also does Jiu Jitsu.Marco and his team was building a wearable in the past, centered around fitness. They figured out that the real value was around feeding data into these types of wearables. When they were approached by a company who was excited about this type of solution, they started to accelerate.This is the creation story of ROOK.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.tryrook.io/https://www.linkedin.com/in/marcobzg/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we are dropping another episode in our "chats" series, specifically on the founder side - hearing from those scaling the companies themselves.In this episode, we are talking with Daulet Amirkhanov, Founding Engineer of Bead AI. Daulet is going to take us through his years at Meta and Cognee, leading into how he is building Bead AI, to take on compliance audits and AI automation.QuestionsTell me and my audience a little bit about you. You've gone from three years on high-throughput reliability infrastructure at Meta, to engineering the GraphRAG engine and semantic memory systems at Cognee, and you're now Founding Engineer at Bead AI — an a16z-backed startup building autonomous agent infrastructure for compliance audits. How did that journey shape the way you think about engineering for the age of autonomous systems?Let's zoom into the Meta years. For listeners who haven't worked at that scale — what was the exact piece of logging and reliability infrastructure you owned, what does "high-throughput" actually mean in numbers there, and what's one specific architectural decision from those years that still shapes how you build today?A lot of infra engineers stay in infra. You made a deliberate move from human-scale systems at Meta to agent-scale systems at Cognee. What did you see in that moment that convinced you AI agent infrastructure was the next distributed systems frontier — and not just the current hype cycle?Cognee is a GraphRAG and semantic memory company, and your work there was on the agent infrastructure side. Your biggest design call was decoupling the MCP architecture so multiple agentic systems can share unified memory through a standalone process, rather than each one coupling to its own Python runtime. Walk us through what problem that was solving and the key design decision you made.Give us a concrete example: an agent task that breaks when each agent has its own vector store, but works once they share unified state through the decoupled MCP architecture you built. What's the actual mechanism that makes the difference?Most engineers in this space come from an ML or applications background. You're coming at agent infrastructure from a pure distributed systems lens. What does that lens let you see that the ML-native crowd is missing?Bead is a16z-backed and going after compliance audits, which isn't the obvious first market for autonomous agents. You joined as Founding Engineer in January and are shaping the technical core now. From your seat: what makes compliance audits the right wedge for agent infrastructure, and what are the foundational decisions you're making today that will define what the product can do two years from now?Make a technical claim about agent infrastructure that most people in this space would push back on — and defend it. Where are you the dissenting voice?Without breaking anything confidential — what's the hardest unsolved problem on your plate at Bead AI right now, and how are you approaching it?Two years from now, what's the piece of agent infrastructure that we'll consider "obviously necessary" but doesn't exist yet? Who builds it, and what does it look like?SponsorsUnblockedBraingrid.ai.TECH DomainsMezmoLinkshttps://usebead.ai/https://www.linkedin.com/in/amirdnur/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Kunal Bhatia is originally from India, but moved to the Bay Area to start building his company. He admits there is quite a contrast between the two places, but originally he was from Bangalore, which is like the Silicon Valley of India - so the professional transition felt familiar. He's worked in AI For 12 years, and is on his 3rd company in the AI space. Outside of tech, he is married with a 3 year old daughter. He and his family love to go on hikes and be outdoors.Kunal and his team have been researching AI technologies within their current venture. In particular, they were focused on building self improving AI. Beyond that, they have started building and thinking about how to build the AI platform that builds all other technology.This is the creation story of Hexo Labs.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://hexolabs.com/https://www.linkedin.com/in/kunalbhatia91/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Ofir Stein is based in Tel Aviv, Israel, born and raised in Jerusalem. He spent many years in the Israeli air force, in infrastructure and security, before he moved to Tel Aviv. He's a tech guy through and through, bragging about his raspberry pi setup at home, which adjust the AC settings based on the temp outside. Outside of tech, he is married with a daughter and a dog. He's connected and close to his family, which he notes is how he refreshes and reloads as a founder, alongside playing tennis from time to time.Ofir and his cofounder started interviewing CISO's and security professionals on how they feel about access management. The found out that this was the first line of attack for bad actors, but from a business standpoint, access management is a slow to value feature. They decided to build a platform that was based on just in time access, over the slow to value setup plaguing the industry.This is the creation story of Apono.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.apono.io/https://www.linkedin.com/in/ofir-stein/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Anusha Iyer is a first generation immigrant, born in India. She moved to the states with her family, when her Dad was going grad school at Ohio State. She fondly remembers sitting on her Dad's shoulders for Buckeyes football games, as he was fan enough for the whole family. Outside of her professional life, she has 2 kids in college who were coding since they could walk - but neither of which ended up in computer science. She loves to cook, and notes that she is not a recipe follower - she likes to use whatever is at her fingertips.Anusha has been in the cybersecurity space for quite some time, starting off in naval research in DC. Further down here career, she had a friend reach out to pitch an idea to build a platform for dynamic machine identification.This is the creation story of Corsha.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://corsha.com/https://www.linkedin.com/in/anusha-iyer/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Thomas Schlegel lives in Nashville, TN, but grew up in rural Virginia. He didn't have the internet for a large portion of his childhood - but, his friends did! So that meant he was spending more time at his friends place, and eventually when MySpace came around, he was the guy to build everyone's custom site. He's always been the wild idea guy amongst his friends, always the tinkerer. Today, he's married with twins on the way. He loves to run, either on the road or the trails. And when he gets the chance, he enjoys a good conversation with good people, contemplating or pondering the bigger things in life.In the past, Thomas was a lead engineer at a professional services organization in Tennessee. While at a conference, he met the CEO of his current venture, and they hit it off. He was intrigued by their company, and several years later, he started working for the company as an individual contributor - and quickly activated his entrepreneur DNA to solve ALL the problems.This is the creation story of Built.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://getbuilt.com/https://www.linkedin.com/in/thomas-schlegel-678772215/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Yoni Avital lives in Tel Aviv, Israel, with his wife and 3 older children. The oldest kid is a boy, so Yoni and he try to see as many football games as possible. He enjoys shopping with this girls, though it's cause he is their Dad, not because he enjoy shopping. He likes to travel, hike, and enjoys a nice white wine in warmer weather. His most memorable hike was at Yosemite, when he started at 4 am and came across a lot of wildlife.Yoni was in the virtual desktop space in the past. What he and his team realized was that troubleshooting these virtual experiences were incredibly complicated. They started to build an enterprise task manager, to centralize a task management UI to control the endpoints. When customers started asking to use it daily, Yoni figured out they had something unique.This is the creation story of ControlUp.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.controlup.com/https://www.linkedin.com/in/yoavital/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Brooke Hipps currently lives in Fort Worth, TX but grew up down the road in DeSoto. She is entrepreneur through and through, from the early years of learning from her parents, to starting three businesses of her own, in fashion, construction and estate planning. Outside of tech, she has three kids - one out of college and 2 still in college. Brooke is an outdoorsy person, enjoying spending time in nature, hiking, camping and playing a round of golf every now and again.Recently, Brooke's sister passed away. Obviously, this was a difficult moment for her and her family, but what made it more difficult was that her sister didn't have a will. Brooke started asking the question "why bit?", and exploring building something to help Texan's with writing a love letter to your surviving loved ones.This is the creation story of Weekend Will.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.weekendwill.com/https://www.linkedin.com/in/brooke-hipps-792224116Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we have a special guest on the Code Story podcast - Patrick Vuong, Director of Product at Moderne. Moderne is the agent tools company, building the. Knowledge, discovery and execution tools that AI agents rely on - so they can operator faster, more accurately, and at far lower cost.In today's episode, Patrick is going to tell us about the company, and how Moderne is enabling developers to build software faster, and with the best context - using agents and agent tools. Their approach to semantic models produce deterministic over probabilistic, or inference driven, tools, which for this engineer/host, has been a point of skepticism for AI since the beginning.QuestionsTell me and my audience a little bit about you.What is Moderne?Moderne is enabling developers to operate software systems at the speed of agents. Tell me about this product suite.Why do Agents need tooling? Where do we see AI in ROISomething jumped out at me... you mentioned you are not only building tooling for agents that are deterministic.As we peer into tech stacks across the industry, where does Moderne fit?OK so this is clearly a pivot for Moderne. With this, who are your customers now?What does the future like for your product - what you offer - and your team?For you personally, you are entering into a new chapter with Moderne. What makes you most excited, going from Microsoft to entering the startup world with the company?In your journey, who has influenced the way you work? Tell me about a person, or many persons, or something you look up to and why.So you worked at Microsoft for 8 years, and are now transitioning to Moderne. Say you were getting on a plan and sitting next to someone about to make this same transition - what advice would you give them?SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.moderne.ai/https://www.linkedin.com/in/vuongpatrick/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Aron D'Souza is originally from Australia, the son of a Chinese mother and an Indian-Portuguese father. He is a graduate of Oxford, and got his PhD from the University of Melbourne. A lawyer by training, he has built 12 companies and has had 5 exits - working with folks like Peter Thiel, the New York Stock Exchange and the Enhanced Games. In general, he's a problem solver, and turns all of his fun into work.Aron made the stark realization that we are a divided society, and do not have a trusted, unbiased media source. He attempted to build a rudimentary version of a solution for a tribunal of truth 20 years ago, but the tech wasn't ready for it. That is, until the most recent advances in AI.This is the creation story of Objection AI.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://objection.ai/https://www.linkedin.com/in/arondsouza/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Nikunj Bajaj was born in India, and completed his undergraduate studies there. The intrigue of Silcon Valley in 2013 brought him to the Bay Area, where he got his masters degree from Berkeley. His studies and his time after school supremely informed what he is building now, at his current venture. But outside of tech, he is an outdoorsey person, enjoying running, biking and scuba diving, with his favorite place to dive being Bali. He enjoys playing board games with his friends, and listens to a lot of audiobooks from a wide range of genres.After joining Meta, Nikunj realized that building machine learning models for the company is different than using public ecosystems. The realized early on that machine learning models will hit an inflection point, where the stacks will need to change and adapt. He and his team decided to take on this challenge ahead of that inflection point.This is the creation story of True Foundry.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.truefoundry.com/https://www.linkedin.com/in/nikunj-bajaj-10476824/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Tyler Hochman got started early in the world of entrepreneurship. In Middle School, he got into Gemology, fascinated by the formation of gems, becoming a young GIA certifier. This taught him to get out of his comfort zone, from which he started his first business as a junior at Stanford. Past that, it's been a similar process of identifying a problem and looking at how to build a solution. Outside of tech, he is married with a 1 year old son, and another child on the way. He loves spending time with his son, enjoying all of the things parenthood throw at you.Tyler built a workforce turnover solution half a decade ago, in the space of predicting employee turnover in a business. It got a lot of solid traction, but what he and his team noticed was that though people wanted to use the solution, they didn't have the infrastructure necessary to provide data to the tool. This led he and his team to swim a bit downstream to build that data pipeline for customers.This is the creation story of FORE Enterprise.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://foreenterprise.com/https://www.linkedin.com/in/tyler-hochman-83b547130/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Meghan Joyce comes from a long line of people living life to the fullest. She takes a lot of influence from her grandmother, who was an entrepreneur, making and selling dresses in the early 1900's, influencing her to take a hold of every moment in life and capitalize on the time you have. She's led groups at Uber and Oscar, prior to starting her current venture. But outside of tech, she is the mother of 3 children. Her favorite hobby is to spend time with the people she loves, meeting them where they are. But when she has spare time to herself, she enjoys being in nature, hiking or walking on a beach, and staying active.Meghan was sitting on a bed in Amsterdam, and experienced a problem with parental technology (IE a breast pump) that was keeping her from running things at Uber. While sitting on hold with the company, trying to get another one available, she started to wish she had a solution that would help her with this, while she attended her meetings at Uber.This is the creation story of Duckbill.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://getduckbill.com/https://www.linkedin.com/in/meghanvjoyce/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today we have a special guest and author on the Code Story podcast, Steve Brown. Steve is a former DeepMind futurist, and recently published a book called The AI Ultimatum: Preparing for a World of Intelligent Machines and Radical Transformation. In the book, he provides a step by step framework to guide leaders in identifying use cases for AI, turning it into business value, and obtaining buy in from employees.In our conversation, Steve is going to elaborate on why AI is a teammate (not a threat), the top AI rollout mistakes, leadership and management tactics that need to go, and much more.Questions: What led you to write this book? Ultimately, what were you trying to accomplish?We often hear that AI is coming for our jobs, but you argue it’s actually our newest teammate. Can you elaborate on this more?Let's double back on something you said, around the flavors of agents. What are those 3 different flavors of agents?Over time, leaders can fall into operating out of their experience - IE assumptions about a particular endeavor. With the advent of AI, what assumptions need to be retired, and what needs to replace them?In the same vane as the last question, you mention that old-school management fails in the age of AI. What do you mean by this, why does it fail and what needs to be changed?In the book, you talk about the AI wins you can use today, effectively pointing at immediate impact teams can feel from using AI. Can you talk to 2-3 of the most important ones?Can you explain why reinvention beats reduction? If this is the case, how can leaders and employees move into this way of thinking?Today, people are trying to rollout AI and getting it wrong - from the startup to the enterprise. What are the top AI rollout mistakes for companies to avoid?SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinksThe AI Ultimatum: Preparing for a World of Intelligent Machines and Radical Transformationhttps://beacons.ai/aifuturisthttps://www.stevebrown.ai/https://www.linkedin.com/in/futuresteve/https://www.linkedin.com/company/aitransformation/https://www.youtube.com/@futureofaiCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Catalina Turlea is originally from Romania, growing up in the countryside there. Post getting her bachelors, she moved to Austria for her masters, and landed in Germany for 13 years. She is married with a 3 year old daughter and many, many pets. She loves to spend time with her family, in nature and the mountains. She used to do a lot of sports, but being a startup founder doesn't really allow for as much running or hiking. She also is into calligraphy, which she calls her hidden superpower.Catalina has been building products for 14 years, and recently was running a small tech consultancy for startups. What she observed was that a lot of products contained an AI feature, but the "feature" was based on a prompt, didn't work well, and wasn't a good fit for the users. Eventually, she and her co-founder realized they saw the same problem, and built a platform to support products teams in building valuable AI features.This is the creation story of Lovelaice.SponsorsUnblocked (https://getunblocked.com/codestory)TECH Domains (https://get.tech/codestory)Mezmo (https://mezmo.com/codestory)Braingrid.ai (https://braingrid.link/code-story)Linkshttps://lovelaice.com/https://www.linkedin.com/in/catalinaturlea/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Dr. Aqib Rashid was born and raised in London. He spent a lot of time around computers and tech growing up, and his parents pushed him towards becoming an expert in a discipline, being a positive influence on society. But he maintained his balance in life by playing sports, which inspired him to want to lead a team in the future. But outside of tech, he is a Dad to a one year old boy. He enjoys spending time with him outdoors, and finds that the real beauty in life is watching him grow up.In Sept 2023, Aqib had completed his PhD around the subject of using AI to detect malware. His current venture was looking at how to implement this sort of approach into their products. Quickly, he got to work building a new product to detect malware in your files.This is Dr. Rashid's the creation story of Glasswall.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.glasswall.com/https://www.linkedin.com/in/aqibrashid/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

David Matalon grew up in Great Neck, outside of New York City. He's always been interested in tech, way back in the early days of PCs, DOS, Windows and even Novell. In fact, he was the high school kid with an IT Consulting business on the side (yes, he wore a beeper to school). He graduated from NYU, and started his first company Offyx. Outside of tech, he is married with 4 kids. When asked about what he does for fun, he says that enjoys the all compassing nature of work and family life.David's whole career has been centered around helping companies deliver distributed applications. In most of recent history, virtual desktops or VDI has been the de facto solution for businesses, with lots of issues and pains baked in. David and his team heard the cries of their customers, and decided to build a better solution - one, with a blue border.This is the creation story of Venn.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.venn.com/https://www.linkedin.com/in/davidmatalon/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today, we are dropping another episode in our "chats" series, specifically on the Founder side, - hearing from those scaling the companies themselves.In this episode, we are talking with Vadim Dedov, CEO at Catchers. Vadim is going to walk us through what problem he wanted to solve with Catchers, and how his product development journey took him through architectural decisions, product optimization, team building and more.QuestionsBefore we talk about Catchers, I’d love to understand you a bit better.What experiences or responsibilities earlier in your life shaped how you think about work, systems, and accountability today?What problem were you dealing with before Catchers existed? Not as a product idea yet, but as a real operational pain you kept running into.At what point did you realise this couldn’t be solved with people, spreadsheets, or manual coordination anymore and that technology was the only way forward?How did Catchers actually start taking shape as a product? What was the very first version you built, and what did “good enough” mean in a business where mistakes affect people’s income and compliance?How long did it take to get to something usable, and what constraints defined your MVP?Looking back, what were the most important trade-offs you made early on?Things you consciously postponed or simplified, knowing they might come back later.Let’s zoom in on the product itself. What is the core product insight behind Catchers — the thing you believe differentiates it from a typical HR or staffing platform?How did your thinking about architecture evolve as scale increased? Was there a moment when you had to stop moving fast and redesign parts of the system properly?How did you approach building your core team around such a complex, operations-heavy product? What qualities mattered most in the people you trusted with this system?Can you share a decision that didn’t go as planned and how you and your team dealt with the consequences?When you step back and look at what you’ve built today, what are you most proud of not in terms of features, but in terms of reliability, impact, or how the system holds under pressure?As you look ahead, how do automation and AI change the way you think about workforce platforms — and what advice would you give to someone building infrastructure-heavy products today?SponsorsUnblocked (https://getunblocked.com/codestory)TECH Domains (https://get.tech/codestory)Mezmo (https://mezmo.com/codestory)Braingrid.ai (https://braingrid.link/code-story)Linkshttps://catchersjob.com/https://www.linkedin.com/in/vadim-dedov-060b8935a/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Yoav Crombie was born and raised in Israel, serving in the army for 6 years as an engineer. He's been in the tech industry of 35 years, but doesn't see this work as work. He thoroughly enjoys what he is doing, especially with what is going on with AI right now, specifically around the quick creation process. Outside of tech, he has been married for 30 years. He loves water sports - kite surfing, regular surfing and paddle boarding. In addition, he loves to cycle, and was the Israeli road champion many years ago.Yoav realized that companies were struggling that businesses were struggling to implement and adopt AI. In particular, he noticed that there was risk in publicly sharing your data. But alongside that, other companies wanted more control to how AI functioned for their country. So his company started to build a solution to solve both of these problems.This is the creation story Pragatix, a product of AGAT Software.SponsorsUnblocked (https://getunblocked.com/codestory)TECH Domains (https://get.tech/codestory)Mezmo (https://mezmo.com/codestory)Braingrid.ai (https://braingrid.link/code-story)Linkshttps://agatsoftware.com/https://agatsoftware.com/secure-ai-platform/ai-suite/ai-agent/https://www.linkedin.com/in/yoavcrombie/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Robert Brennan grew up in Boston and loved it so much that he ended up calling it home again. He spent time in New York between his bookend times, but he enjoys the chill pace and great music of Boston over the fast pace of the big apple. Outside of technology, he likes to read nonfiction and fiction, specifically science fiction. He loves music, and. Has been playing guitar for 25 years now. He frequents the live music scene around Boston, and even lives near a jazz club.Robert observed the release of the first version of Devin a few years ago, which was very exciting to see agent driven development. But he and his co-founders were concerned with who was going to govern how this software was going to get written - and they hypothesized that it should be open source and community driven.This is the creation story of OpenHands.SponsorsUnblocked (https://getunblocked.com/codestory)TECH Domains (https://get.tech/codestory)Mezmo (https://mezmo.com/codestory)Braingrid.ai (https://braingrid.link/code-story)Linkshttp://openhands.dev/https://www.linkedin.com/in/robert-a-brennanCheckout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Tobi Konitzer was born in Germany, and studied cultural studies as an undergraduate student. Eventually, he went to Duke to get a PhD in political science. And that eventually changed to be a PhD in computational social science at Stanford - which is basically writing code to answer social science questions. After graduating in 2017, he joined Facebook Research for a year, then founded two AI startups. Outside of tech, he has 2 young daughters, who he likes to spend time with and take to the park. He used to be an avid trail runner, but his favorite to do is think... and to do so as often as possible.For the last 10 years of his career, Tobi has been chasing optimized decisioning and outcomes using AI. Five months ago, he decided to join his current venture, and use AI to shift the conversation from "tooling for marketers" to using AI to build an autonomous decisioning system, that learns and improves over time.This is Tobi's creation story at Growthloop.SponsorsUnblocked (https://getunblocked.com/codestory)TECH Domains (https://get.tech/codestory)Mezmo (https://mezmo.com/codestory)Braingrid.ai (https://braingrid.link/code-story)Linkshttps://www.growthloop.com/https://www.linkedin.com/in/tobias-konitzer-phd-65984454/Checkout our episode stacks on Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy