Why do we see so many robot demos but so few real deployments? Guillaume Binet of Copper Robotics says it's the software stack, so he's building a new real-time OS for robots. 🎧 techontherocks.show/30

Tech on the Rocks | Rebuilding the Robot Stack: Why Robotics Needs a New Real-Time OS with Guillaume Binet (Copper Robotics)

In this episode, Nitay and Kostas sit down with Guillaume Binet, founder of Copper Robotics, to dig into one of the most overlooked problems in modern robotics: the software stack that runs the rob...

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Ep 28: Building the Open Lakehouse for the AI Era with Shubham Baldava from DataZip / OLake Hudi vs. Iceberg vs. Delta, sub-10-min CDC for fintech, Arrow-based ingestion, and what Iceberg decoupling from Parquet means for AI. 🎧 techontherocks.show/28

Tech on the Rocks | Building the Open Lakehouse for the AI Era with Shubham Baldava from DataZip / OLake

In this episode of Tech on the Rocks, Nitay and Kostas sit down with Shubham Baldava, co-founder of DataZip and creator of OLake, to trace the evolution of the modern open lakehouse — from the earl...

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"Never bait and switch developers." @jt.lol watched CRDTs promise magic on day one and deliver misery by month six. Convex starts with serializable transactions and typed, reactive code instead - and it turns out that's what AI agents write best too. episode link below

New episode of Tech on the Rocks! From Art to Science: Wild Moose and the Future of AI-Powered Debugging The full founding team breaks down how their "microagents" replicate the muscle memory of senior engineers to investigate production incidents in under a minute.

Shipping ML is still weirdly manual: notebooks, translation layers, and “it ran last week” debugging. New episode with Hussain on xorq . a lockfile-style model for pipelines: declare → lock → reproduce / port / inspect lineage. 🎧 techontherocks.show/24

Tech on the Rocks | From Notebooks to Production: Xorq’s lockfile Approach for Reproducible, Portable ML Pipelines

In this episode, Hussain shares the story behind xorq: a “lockfile for ML pipelines” that makes notebook work easier to reproduce, debug, and ship. We talk about why the research→production path is...

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New episode: chatting with bauplan founders Jacopo Tagliabue and Ciro Greco on shipping AI with real-world data constraints. Why listen 1. Data pipelines determine model effectiveness, far more than most teams admit.

What if email isn’t an inbox—it’s your company’s knowledge graph? 🧠 @thatguybg.bsky.social breaks down: acquisition reality (retention/culture > price), startup energy vs. big-co burnout, Launch House, and Micro’s AI layer that turns mail into CRM/hiring/sales apps + proactive updates” link below

@steveklabnik.com Joined us on an episode where we discussed about Why: • Cargo & friendly errors > benchmarks • 6-week releases > years-long committees • How Rust united Ruby, FP & C++ devs • Next-gen picks and many more! Check the episode on your favorite platform!

🚀 New Episode Alert! ‪@cloudflare.social‬'s Josh Howard, dives into serverless computing at the edge with Durable Objects & Workers. Learn how to build globally scalable, stateful apps easily & reliably. Check our profile to listen to the episode on your favorite platform.

Investors must embrace uncertainty and unpredictability when backing innovative, rapidly evolving technologies. Eric Swan from ep.18

Most companies do not use off-the-shelf dev environment solutions; they create highly customized setups unique to their needs. @ivanburazin.bsky.social from ep.9

The halting problem does not prevent proving equivalence for many practical code transformations, making formal verification feasible in many cases. Ben Sigelman from ep.11

Edge computing platforms that run containers close to users improve performance and enable new application architectures. David Mytton from ep.10

Automation that enables one-click spin-up of complex dev environments is a critical pain point for large enterprises. @ivanburazin.bsky.social on Developer Environments in Enterprise from ep.9

AI agents capable of autonomously performing tasks on our behalf remain limited but hold transformative potential for freeing human creativity. Dean Pleban on AI & the Future from ep.4

Ownership ambiguity over data pipelines and infrastructure is a major source of friction in data and ML workflows. Dean Plebal on User & Market Strategy from ep.4

Automatic theorem proving complements conjecture generation by providing tools to verify and prove newly discovered formulas. Yaron Hadad on Scientific Research & Collaboration from ep.13

Personal and professional growth often intertwine, with experiences abroad and advanced education shaping global perspectives. Roy Ben Alta on Career & Education from ep.8

Formal verification tools like TLA+, FizzBee, and Antithesis serve different stages: design-level verification versus implementation-level testing. Jayaprabhakar(JP) Kadarkarai on Formal Methods & Verification from ep.5

Engineering excellence requires continuous learning from past successes and failures, which is often documented and shared in high-quality engineering cultures. Jayaprabhakar(JP) Kadarkarai from ep.5

Decentralized data architectures require robust infrastructure for managing governance, access controls, and rules across distributed data sources. Viktor Kessler from ep.16

Startups and new products increasingly prioritize serverless models to reduce user friction and accelerate adoption. @philippemnoel.bsky.social from ep.12

Legacy APIs based on static configurations (e.g., YAML with embedded SQL) often give way to more dynamic, code-driven approaches for flexibility and power. Varant Zanoyan & Nikhil Simha from ep.2

The integration of large language models (LLMs) into everyday tools like smartphones and laptops will accelerate the shift toward AI-driven task automation. Dean Pleban from ep.4

The value proposition of formal methods becomes clear when dealing with complex distributed transactions involving multiple independent services. Jayaprabhakar(JP) Kadarkarai from ep.5

User experience and developer interaction with complex data abstractions remain a significant challenge beyond the technical integration. Nikhil Simha & Varant Zanoyan from ep.2

AI agents and automated operators require actionable metadata to autonomously coordinate data usage and pipeline stability. Viktor Kessler from ep.16 on the importance of metadata and catalogs for the future of AI and agentic architectures.

Successful AI developer tools must balance synchronous co-pilot style assistance with asynchronous autonomous agent workflows. @ivanburazin.bsky.social from ep.9

Managing AI access and permissions requires careful role-based controls to prevent over-privileged AI actions in enterprise environments. Well said, even before hashtag#MCP was as popular as today. @ivanburazin.bsky.social from ep.9

Erik’s been in tech longer than some programming languages. @splunk founder, and now building something new with AI. We get into building from first principles, surviving PLG, brand as a GTM edge, and what Erik’s building next. Check it on your favorite podcast platform!