Avsnitt
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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 Schyokotov, 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.
Questions
Today 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?Sponsors
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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.
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Saknas det avsnitt?
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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.
Questions
When 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?Links
https://www.wallarm.com/https://www.linkedin.com/in/tim-erlin/Full Abstract
In 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.
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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.
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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.
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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.
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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.
Questions
Tell 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?Sponsors
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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.
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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.
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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.
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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.
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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.
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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.
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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.
Questions
Tell 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?Sponsors
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https://www.moderne.ai/https://www.linkedin.com/in/vuongpatrick/
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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.
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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.
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https://www.truefoundry.com/https://www.linkedin.com/in/nikunj-bajaj-10476824/
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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.
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https://foreenterprise.com/https://www.linkedin.com/in/tyler-hochman-83b547130/
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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.
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https://getduckbill.com/https://www.linkedin.com/in/meghanvjoyce/
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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?Sponsors
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The 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/@futureofai
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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.
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https://lovelaice.com/https://www.linkedin.com/in/catalinaturlea/
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