- 27 minutes 25 secondsS13 Bonus: Scaling Real-Time Search Data: Secure APIs for AI Infrastructure with Alaa Abdulridha, Engineering Director at SerpApi
Alaa Abdulridha is from souther Iraq, but now lives in Austin, TX. Post wars in Iraq, the country had poor infrastructure, which got him interested in building and creating things to better and secure his life. He left the country to study, and ended up in Germany as a security engineer. Outside of tech, he enjoys playing RPG video games. In particular, he likes to play World of Warcraft, and enjoys the open world, and character development from scratch.
Alaa's current company was built to scrape google search engines, in order to get around a blocker for a prior project. In the past, he used to participate in bug bounty hunting during University, and wrote about his exploits. His now founder's came across his articles, and invited him to joint the company.
This is Alaa's creation story at SerpApi.
Links
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Santiago Castineira has quite the background in international living. He was born in Argentina, but grew up in Spain, then moved to Sweden, San Francisco, and now llives in Germany. He did his grade school and university in Spain, but his masters program across Sweden, San Francisco, and Germany. He's worked in startups, bigger companies, and eventually founding and is leading his own. Outside of tech, he is a Dad of 3 kids, so he stays quite busy when he isn't working. He loves endurance sports, running half marathons and long distance biking.
Santiago and his team were well aware of the fact that tens of thousands of new vulnerabilities are published every year. While security teams were drowning, the rise of automated coding agents were starting to ship code faster and faster. He and his team realized that there needed to be an agent driven platform, designed to evaluate and secure your system like a senior security engineer.
This is the creation story of Maze.
Links
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Yaniv Tal grew up in the Bay Area in the 90's with parents who were engineers. They were both in electrical engineering, specifically digital/signal processing. He really saw the internet sport up into a massive thing. He studied the hard sciences (electrical engineering, math and physics), and his first job out of college was at HP, doing board b ring up for printers. Outside of tech, he is recently married, having a lovely wedding on a beach in Mexico. When asked "what do you do for fun?", he can't answer it, cause he is a bit of a workaholic and loves what he does. But, he does make sure he spends quality time with his new bride.
In 2017, Yaniv founded a protocol called The Graph, one of the core web3 protocols. After many years on this journey, he started to have a vision around the world's broader knowledge in a decentralized, verifiable way. Eventually, he and his team set out to launch a a solution around this vision, designed to solve fragmentation of knowledge, vulnerable to centralization, silos and misinformation.
This is the creation story of Geo.
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Today, we welcome a special guest to the podcast, Vasanth Mohan, Head of Developer Relations and Product Marking at SambaNova.
SambaNova is transforming AI with efficiency, security and sovereignty, driven by their relentless pursuit of intelligence, and running the largest models by maximizing dataflow efficiency. Vasanth and I dig into some fun - and heavy - topics at the backbone of where the industry is going with AI Inference, specifically at the hardware layer.
Questions:
- Tell me and the audience a bit about you and SambaNova.
- The Shift to Autonomy: "When we shift from a user generating a single chat response to an autonomous coding agent executing dozens of background tool calls, loop checks, and file rewrites, how does the underlying inference profile change, and what metric breaks first?
- Latency Budgets: "Token-per-second throughput used to be a nice-to-have metric for human readability, but for multi-agent workflows running in parallel, low latency is critical to prevent system timeouts. How are developers designing prompt structures and context windows to prevent compounding latencies during multi-agent orchestration?
- Hardware Heterogeneity: "Hyperscalers historically standardized on monolithic hardware, but neoclouds are increasingly mixing high-memory GPUs, specialized inference ASICs, and custom interconnects. How do you decide the optimal hardware mix inside a rack when your customer demand fluctuates between massive long-context reasoning models and rapid edge-like decoding?
- Power and Rack Density: "With high-end inference accelerators drawing massive power per node, how are neocloud data centers re-engineering liquid cooling, rack layouts, and power distribution specifically to maximize inference density rather than training throughput?
- Decoupling Prefill and Decode: "Disaggregated inference splits compute-heavy prefill operations from memory-bandwidth-heavy decode operations onto distinct hardware pools. What are the biggest real-world friction points when deploying this in production—especially around KV-cache transfer overhead and inter-node networking?
- Dynamic Orchestration: "In a disaggregated setup, workload spikes in long-context coding prompts can saturate the prefill pool while leaving decode nodes underutilized. How are leading engineering teams building smart routing layers and dynamic auto-scaling engines to balance compute across compute-bound and memory-bound hardware?
- The Economic Tipping Point: "Enterprise adoption is oscillating between proprietary API-driven models and self-hosted open-weights models. At what scale—measured in inference volume, latency SLAs, or data privacy constraints—does it become economically imperative for a company to transition off closed APIs onto self-hosted open infrastructure?
Links
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Peter Morelli was born and raised in San Francisco, one of the few natives of the area. He was front and center, watching the tech scene explode in front of him (and also blow up). He's lived all over - like New York, San Diego, Texas, London - but always ends up returning to the Bay Area. Outside of tech, he is married with 3 kids - one in college, and the other 2 in high school. He is a foodie, and loves cooking, enjoying the communal, connective aspect of having a meal with his family and friends.
Peter spent many years at Lyft, where he and his team became frustrated by traditional observability tools and how they waste money storing unused data. They started to building a solution based on dynamic, real time control paired with local, on-device telemetry storage. Once they realized their breakthrough, they spun off the solution into its own company.
This is the creation story of Bitdrift.
Links
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Julien Verlaguet is a self proclaimed "French guy", growing up in south of France. He studied in Paris, and moved to the US when he was 27, spending 10 years in the Bay Are and 5 years in New York. He's spent many years developing software, in particular, developing programming languages. Outside of tech, he is married to a Columbian woman, and admits his Spanish isn't as good as it should be. He loves to play Pétanque, merely needing a flat surface to play on.
Julien was a lead programming language designer at Facebook, and lead the open source release of a new programming language. Over time, he noticed that frontend dev was in a resolution with reactive paradigms, while backend architectures remained bogged down by manual steps. In 2022, he stepped out to create Meta-grade creativity usable in everyday software.
This is the creation story of Skiplabs.
Links
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Privacy & Opt-Out: https://redcircle.com/privacy22 September 2026, 10:00 am - 39 minutes 14 secondsS13 Bonus: The Legal AI Shift: Automating Contract Workflows with AI Agents with Nick Holzherr, Founder & CEO of GitLaw
Nick Holzherr is originally from the Switzerland, but moved to UK when he was 7 years old, to the countryside. He had no real touch to computers until he was 18, when he attended university and everything picked up for him, tech wise. Eventually, he got into building businesses, and of those, he founded a coffee company, HR software company, and whisk.com, which was sold to Samsung in 2019. Outside of tech, he is the father to two young children. He enjoys skiing and snowboarding, and jokingly, he admits that running around ensuring his agents are prompted gets in the way of his family and hobby life.
Through his entrepreneurial adventures, Nick spent large sums of money on legal contracts, ensuring that the i's were dotted and the t's were crossed. While he still feels that lawyers are very important and needed for certain scenarios, Nick wanted to create a way to level the playing field for small businesses, in the legal arena.
This is the creation story of GitLaw.
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Today, we have a special return episode from our friends at Backbox, who we heard the creation story of the company back in Season 8. In this episode, we talk with Rekha Shenoy, CEO of Backbox. Since Rekha took the helm as CEO in May 2024, the company has expanded beyond traditional security automation to launch its major BackBox 8.0 platform, unifying cloud and on-prem infrastructure visibility. They’ve also integrated human-in-the-loop, advisor-focused AI capabilities - and are back to let us know some even more "big things" happening with platform, around agentic .
Questions:
- Tell me about yourself—your path into tech and what shapes how you lead (background, influences, hobbies, family).
- Tell me about BackBox. What does the company do, and what drew you in to take the CEO seat in 2024?
- How has the product matured? How do you build your roadmap?
- Zoom out — what are you most proud of in shaping BackBox?
- What does the future look like for your product and team?
- BackBox describes AI as a "trusted advisor, not an autonomous agent" — four principles: protecting infrastructure, repeatable/verifiable results, supporting (not replacing) engineers, and transparency about how AI reaches conclusions. Where did that philosophy come from, and why hold that line while competitors race toward full autonomy?
- What does "responsible AI" actually look like in the product — not as a value statement, but as a design constraint that shaped the engineering decision?
- Tell us about your recent launch and what it enables a network team to do that they couldn't before?
- How does the launch extend or test that responsible-AI philosophy?
- At what point does "AI as advisor" start to feel like a limitation rather than a safeguard?
Links
https://www.linkedin.com/in/rekha-shenoy-950b23/
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Connor Heggie grew up in Southern California, digging into technical things early on his life. He played with legos, was influence by Iron Man, and painted pictures on the back of schematics his Dad brought him from Boeing. He went to school at Rice in Texas, feeling a sense of agency and confidence from the program he was in. Eventually, he went to work for startups across computer vision, self driving cars, and AI. Outside of tech, he has a large black Labrador named Captain. He enjoys hiking, being outside, and playing fetch with Captain until he drops in exhaustion.
Post ChatGPT, Connor was working on a side project, creating listicles around products. As he built it, he fell in love with the space of mining information from unstructured data. Once he met up with his co-founder, they started to recognize they could build multi-agent systems that could re-think how Go-To-Market teams operate.
This is the creation story of Unify.
Links
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Christian Ondaatje is originally from Los Angelas, CA. He got into GPUs as an underclassmen in college, of course through gaming and VR. He ended up starting an eGPU company in his CS program @ Harvard, though it was shut down through some cease and desist from Apple. Though he learned some hard startup lessons, his love for GPUs was only fueled more. Outside of tech, he does a lot of SIM racing. In fact, he has built his own Linus VR racing simulator rig over a couple of years He finds that the formal, online competition is very fun to participate in.
As I mentioned, Christian was way into GPUs throughout many different experiences in his life. He and his team recognized that while demand door AI inference and compute was at an all-time high, setting up bare-metal GPU infra was still complex and slow... so they set out to change it.
This is the creation story of Aranya.
Links
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Dumi Mabhena is originally from Zimbabwe, and has lived in 5 different countries. He now lives in Washington, DC, as he came to the states to attend Georgetown. Prior to that, he has been a podcast host and producer for several years, as well as starting businesses and taking part in the startup world in multiple different places. Outside of tech, he married to his wife, who he met while in South Africa. They love to travel, especially Europe in the summer, and are big into fitness and running.
Previously, Dumi started a podcast, to tell about positive experiences in Zimbabwe. As he went through the process of recording, editing, and publishing a podcast - he realized that the tools and platforms were incredibly fragmented... so much so, that it created friction in the process of telling stories. Dumi wanted to figure out a way to remove this friction from the entire process.
This is the creation story of Hilite.
Links
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