Software Huddle

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Episodes

Latest episode

Oct 2026

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EN-US

About the show

Join us in insightful and in-depth interviews with tech experts, covering software development, entrepreneurship, and technology trends. For more on Software Huddle, visit softwarehuddle.com or contact team@softwarehuddle.com.

Listen to episodes

60 recent

October 27, 202643 min

Faster Code Validation for AI Agents with Dan Manges

Today, we have Dan Manges, Co-Founder and CEO at RWX, on the show! Dan previously served as CTO at Braintree and co-founded Root Insurance, and is now building a CI/CD platform designed for the agentic era. In this episode, we explore how AI coding agents are changing software development and why the bottleneck is shifting from writing code to validating it. Dan explains why traditional CI/CD workflows are struggling to keep up, and how RWX uses content-based caching, graph-based execution, and a CLI-first approach to make builds faster and more efficient. We also dive into how engineering teams can rethink their development workflows around AI agents, from validating code changes before opening pull requests to using sandboxes and distributed compute. Dan shares his thoughts on harness engineering, why developer tooling needs to evolve alongside AI models, and what it takes to build reliable software when code is becoming increasingly cheap to produce. Finally, we discuss how teams should measure engineering productivity beyond build times and costs, and why Dan believes the shift to agentic development is creating opportunities to rethink how software gets built and shipped. Tune in for a deep dive into CI/CD, AI coding agents, and the future of software engineering. Visit https://www.rwx.com/blog/series-a for more info.

October 20, 202638 min

Building the AI Dark Factory with Robert Brennan

Today, we have Robert Brennan, Co-Founder and CEO at OpenHands, on the show! Robert previously worked at Google and Fairwinds, and is now building an open-source platform for AI-powered software development. In this episode, we explore how AI agents are changing the way developers work, from automating code reviews and debugging to proactively monitoring production systems and fixing issues. Robert explains what makes an AI agent reliable, why agent harnesses are becoming commoditized, and how teams can continuously improve agent performance. We also dive into how software teams should prepare for agentic development, including the trade-offs between monorepos and microservices, trunk-based development, and traditional code review workflows. Robert also walks us through OpenHands’ SDK and Agent Canvas, and how they enable developers to build and manage autonomous workflows. Finally, we discuss the idea of an AI “dark factory,” where agents handle everything from writing code to testing and deployment. Robert shares his prediction that source code could become an antiquated abstraction layer within the next few years, and what that means for the future of software engineering. Tune in for a deep dive into AI coding agents, developer tools, and the future of autonomous software development. Visit https://www.openhands.dev/ to learn more.

August 18, 202652 min

Open Source Self-Improving AI with Vignesh Baskaran

Today we are talking with Vignesh Baskaran, the CTO and co-founder of Hexo Labs, about teaching AI agents to improve themselves. Vignesh has been training neural networks since 2012, back when he was still called a data scientist. Then he became an ML engineer and now an AI engineer, though he says the underlying work has never really changed. It's to figure out how to make a system behave the way you intend it to. He built the litigation search engine that Google itself became a customer of, and now he's chasing something new, agents that rewrite and retrain other agents without a human in the loop. We dig into Sia, the meta-agent at the center of Hexo's research, and why improving an agent means touching both its harness and its actual model weights, not just one or the other. We talk about proxy evals for when you don't have much to ground truth. The Darwin-Gödel machine and why formal verification is too strict a bar for anything commercial. How Hexo's work echoes DeepMind's Alpha lineage from AlphaGo to AlphaEvolve, and the spectrum from clearly verifiable to totally subjective tasks? Why VAE evals are quietly wrecking agent quality across the industry, and a great story about an agent that discovered a customer's own eval file was silently corrupted, something buried in hundreds of thousands of traces that no human would have caught.

April 8, 202655 min

AI and Proactive Reliability with Kolton Andrus

Today we're talking with Kolton Andrus, the Founder and CEO of Gremlin, about what happens to reliability when AI is writing most of the code. Kolton helped build the Chaos Engineering practice of both Amazon and Netflix before starting Gremlin. In our conversation we talk about scar tissue, the intuition engineers develop from being woken up at 3:00 AM to fix production outages and how AI doesn't have any of it. It generates code in an afternoon that maybe took a team previously weeks to build, but none of those painful lessons come along for the ride. We dig into why 10x more code might mean 10x more failures. The concept of reliability guardrails, think ethical guardrails, but for keeping your systems up. Why you still have to test in production no matter how good your staging environment is? How Gremlin is rethinking their product for the world where agents, not engineers, are essentially the primary users.And why we're entering a painful, narrow part of the hourglass before AI gets good enough to handle all of this on its own.

March 27, 202651 min

Making Data Agent Ready with Andre Elizondo

Today we are talking with Andre Elizondo, the Director of Innovation at Mezmo about their open source agentic harness for SREs called AURA. Mezmo got their start handling observability data at scale. Logs, traces, metrics, the usual stuff. AURA is their answer to a growing problem, as system complexity outpaces humans' ability to make sense of all that data, how do you actually make it actionable for AI agents? We get into their approach to context engineering, essentially making data agent ready before it hits the model. Why they built their own orchestrator in Rust? How they handle memory and self-correction in agent loops? Their take on MCP and where it fits versus Skills and code sandboxing and how the SRE role is evolving as agents become trusted teammates. Visit mezmo.com/aura

January 9, 202653 min

Exponential Engineers with Ashmeet Sidana

Today on the show, we have a special guest — Ashmeet Sidana, the founder of Engineering Capital. Ashmeet started his career as an engineer at some great companies like Hewlett-Packard and Silicon Graphics before founding his own company, getting it acquired, and eventually starting his venture capital firm, Engineering Capital. With his strong engineering background, Ashmeet looks for startups that have a technical insight — something unique that gives them an edge over their competitors. This focus on technical insight sets Engineering Capital apart from other VC firms that often emphasize market insight or distribution insight or some other kind of advantage. We talked about AI, Exponential Engineers, Entrepreneurship, and had a lot of fun.

September 16, 202542 min

Powered by Neurons with Ewelina Kurtys

Today we have Dr. Ewelina Kurtys on the show. Ewelina has a background in Neuroscience and is currently working at FinalSpark. FinalSpark is using live Neurons for computations instead of traditional electric CPUs. The advantage is that live Neurons are significantly more energy efficient than traditional computing, and given all the energy concerns right now with regards to running AI workloads and data centers, this seems quite relevant, even though bioprocessors are still very much in the research phase.

August 12, 20251 hr 8 min

Lessons from Building AI Agents with Rafal Wilinski

Today we're talking with one of our favorite engineers, Rafal Wilinski. Rafal has been on the cutting edge of AI development in the last few years as he has led AI teams at Zapier and Vendr. Rafal walks us through the hard-won lessons about actually integrating AI tools into the applications you're building. One of the hardest things in integrating these AI tools is how to ensure you're getting better and not regressing as you improve your prompts and upgrade your models. He shows how using evals is one part of the story along with deeply investigating customer signals to see how they are or aren't succeeding with AI. Along the way, we also talk about RAG, his favorite models, his AI development toolset, and why Poland has been killing it lately. Check it out and be sure to follow Rafal if you want to learn more on building with AI.

August 5, 202551 min

Building a High-Ownership Engineering Culture with Matt Watson

If you’ve ever felt like engineering teams are stuck in execution mode—heads down, building what they’re told—then today’s episode is for you. We're talking about what it really takes to build high ownership engineering cultures where devs aren't simply just shipping code, but they're helping shape the product. And our guest this week is Matt Watson. He's a long time founder, engineer, and now the CEO of Full Scale, a company that helps startups and scale ups, grow their engineering teams with top talent from the Philippines. Matt's also the author of a book called Product Driven that shows how engineers can build with more clarity, purpose, customer focus and we get into some of the details in that book during this podcast. So in this episode, we get into everything from the downsides of specialization to the importance of empathy, to why code shipped isn't the same as value delivered. We hope you enjoy it.

July 22, 20251 hr 4 min

Building CI for the age of AI Agents with Aayush Shah

Today's episode is with Aayush Shah. Aayush is one of the co-founders of Blacksmith, which is a CI compute platform. Basically, Blacksmith will run your GitHub Actions jobs faster and with more visibility with the standard GitHub Actions CI runners. The founding team has a fun background doing systems work at Cockroach and Faire, and they're taking on a big problem in running this massive CI fleet. The explosion in AI agents has really changed the CI world. CI is more useful than ever, as you want to be sure the changes from your agents aren't breaking your existing functionality. At the same time, there's a huge increase in demand and spikiness of CI workloads as developers can fire off multiple agents to work in parallel, each needing to run the CI suite before merging. Aayush talked about how they're handling this load and facilitating visibility into test failures. We also covered cloud economics. Aayush said the traditional cloud-based storage options don't work for them -- EBS and locally attached SSDs are too expensive for their workloads where they don't need the standard durability guarantees. He walks us through building their own fleet outside the hyperscalers and the plans going forward, along with some of the economics of multi-tenancy that Blacksmith has previously written about.