The New Stack Podcast

The New Stack

The New Stack Podcast is all about the developers, software engineers and operations people who build at-scale architectures that change the way we develop and deploy software.

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20 episodes
Avg 28 min
English

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#1637
August 11 · 26 min
Why CPUs still matter in the age of AI agents
As AI evolves from conversational chatbots to autonomous agents, CPUs are becoming an increasingly important part of the infrastructure equation. In this episode, The New Stack speaks with Bhumik Patel of Arm and Mo Farhat of Google about how CPUs act as an “air traffic controller” for agentic workloads, handling orchestration, data preparation, semantic search, vector databases, code execution and API calls alongside GPUs and TPUs. Smaller AI models, including summarizers and evaluators, can al
#1636
July 31 · 35 min
Why Doist Says Less AI Can Deliver More
Doist CTO Gonçalo Silva says AI is reshaping software development, but success depends on restraint rather than rapid feature expansion. Instead of chasing every AI capability, Doist prioritizes “subtraction over addition,” removing features that fail to deliver lasting value despite development investment. After experimenting with nearly 20 AI concepts, the company found success with Ramble, an AI-powered voice task capture feature, while remaining model-agnostic through rigorous testing and ev
#1635
July 30 · 30 min
Why your company should (try to) build its own AI SRE
As AI coding agents accelerate software development, they also create new challenges for site reliability engineers (SREs), who are increasingly responsible for debugging systems that no single human fully understands. In this episode of The New Stack podcast, Sam Farid and Nate Heinrich of Chronosphere, a Palo Alto Networks Company, argue that AI agents should also be used for root-cause analysis, helping teams diagnose failures more quickly as model capabilities continue to improve.
#1634
July 23 · 32 min
Nvidia
In this episode with The New Stack's Frederic Lardinois, NVIDIA’s Joey Conway says advances in AI over the past year have dramatically improved the capabilities of local models, making them practical for enterprise and personal use alongside frontier cloud models. Rather than replacing large models, Conway envisions a “system of models” where specialized local models handle routine, cost-sensitive, or privacy-focused tasks, while larger frontier models tackle more complex reasoning. He explains
#1633
July 14 · 19 min
Meet Brain, the AI that decides when Azure is officially down
In this episode, Mark Russinovich, CTO of Microsoft Azure revealed Brain, the AI-powered AIOps system that continuously monitors Azure’s health, detects incidents, identifies root causes, and increasingly automates responses such as pausing problematic deployments and notifying affected customers. Built on Azure Resource Graph, Brain creates a real-time digital twin of Azure, mapping dependencies across hundreds of services, data centers, and regions. Although Brain predates the generative AI bo
#1632
July 7 · 20 min
What comes after attention? This startup says it already knows.
Subquadratic is beginning to back up its ambitious claims with benchmarks and third-party validation for its SubQ 1.1 Small model, which uses its proprietary Sparse Attention (SSA) architecture to dramatically improve long-context performance. Rather than comparing every token to every other token, SSA selectively processes relationships, enabling near-linear scaling while maintaining high accuracy across context windows of up to 12 million tokens. The company reports near-perfect retrieval perf
#1631
July 2 · 19 min
“The harness is where the hard work is”: Harness bets on agents that enterprises can trust in production
Harness has introduced Autonomous Worker Agents, a new capability that allows enterprises to replace rigid CI/CD pipeline scripts with AI agents that can deploy applications, run tests, and perform security scans while operating under existing governance, security, and audit controls. Unlike Harness' existing expert agents, which assist developers with coding and pipeline creation, Worker Agents autonomously execute pipeline tasks within customer-controlled infrastructure. Agents are defined usi
#1630
June 25 · 36 min
Public cloud vs. on-prem: Summit on where each workload belongs
More than two decades after AWS helped usher in the public cloud era, many organizations are reassessing whether a cloud-first strategy still delivers the cost and operational benefits it once promised. While hyperscalers such as AWS, Azure and Google Cloud have built enormously successful businesses, cloud spending has become a growing concern for customers as usage expands and costs continue to rise.
#1629
June 18 · 28 min
Gusto Cofounder: An AI agent that runs payroll, HR, and benefits without waiting to be asked
Gusto is betting that small businesses need more than another AI assistant. The company’s new product, Gusto Cofounder, is designed to act as a proactive business partner that helps owners manage and grow their companies, drawing inspiration from the traditional mom-and-pop partnership that co-founder and CTO Eddie Kim witnessed growing up. Unlike reactive chatbots, Cofounder can take action across payroll, HR, benefits, scheduling, insurance, and accounting workflows by leveraging data already
#1628
June 11 · 50 min
WeAreDevelopers is coming to the US to give unsung developers a bigger voice
WeAreDevelopers, the Berlin-based developer conference founded in 2015, has grown into a major global event, attracting 15,000 developers from over 70 countries each year. In 2026, it expands beyond Europe with new editions in San Jose, California, and Bengaluru, India. Co-founder and CEO Sead Ahmetovic says the conference was created to give developers a stronger voice in an industry where marketers, salespeople, and entrepreneurs often receive more recognition.
#1625
May 27 · 27 min
Why MotherDuck refuses to fork DuckDB
At a recent MCP developer summit, The New Stack spoke with Till Döhmen, AI lead at MotherDuck, about the company’s growing role in the evolving DuckDB ecosystem. Backed by investors including Tomasz Tunguz, MotherDuck is commercializing the open-source analytical database DuckDB while also expanding how employees interact with data through AI agents rather than traditional dashboards.
#1626
May 21 · 26 min
JetBrains is selling independence as the rest of AI coding picks sides
JetBrains is positioning itself as the last major independent AI coding-tool vendor in a market increasingly tied to hyperscalers and foundation model labs. Speaking at Google Cloud Next, JetBrains VP of business development Mikhail Vink argued that competitors such as Microsoft Copilot, Anysphere Cursor, and Windsurf are all tied to either AI labs or cloud providers. By contrast, JetBrains says its independence allows customers to switch freely between models from OpenAI, Anthropic, and Google
#1624
May 15 · 19 min
Why Block handed Goose to the Linux Foundation
What began as an internal developer tool at Block has evolved into a broader open-source initiative with industry backing. Goose, Block’s AI coding agent, followed a path similar to Amazon’s transformation of internal infrastructure into Amazon Web Services. After deploying Goose companywide, Block open-sourced the tool under a permissive license, leading to rapid adoption across the developer community.
#1623
May 13 · 22 min
Fivetran's CPO: closed data stacks won't survive the agent era
At Google Cloud Next 2026, Fivetran Chief Product Officer Anjan Kundavaram argued that enterprise data systems are unprepared for the scale of AI-driven analytics. Unlike humans, AI agents can generate exponentially more queries, often routing them through the same expensive compute infrastructure. Kundavaram compared it to “using a Lamborghini to mow the lawn.” To address this, Fivetran introduced its “Open Data Infrastructure” vision and a benchmark designed to expose hidden AI workload costs
#1621
May 12 · 28 min
The new FinOps problem isn't cloud bills
At Google Cloud Next 2026, Finout co-founder and CEO Roi Ravhon and Google Cloud FinOps lead Pathik Sharma discussed how FinOps is rapidly evolving for the AI era. Ravhon argued that while cloud FinOps had a decade to mature, AI economics are forcing the industry to adapt within a year. Unlike traditional cloud workloads, AI costs are unpredictable because token usage varies even for identical prompts, while advanced reasoning models consume significantly more tokens despite falling prices.
#1620
May 7 · 25 min
How Microsoft is governing thousands of Kubernetes clusters without manual intervention
Managing Kubernetes at fleet scale introduces significant complexity, especially as organizations expand from a few clusters to hundreds or thousands across cloud, on-premises, and edge environments. While GitOps remains the dominant model for declarative management, its traditional one-to-one repository-to-cluster approach struggles to handle multi-cluster realities such as global traffic routing, shared secrets, and unified observability. As Stephane Erbrech, Principal Software Engineer at Mic
#1618
May 6 · 31 min
Why long-running AI agents break on HTTP and how Ably is fixing it
In this episode ofThe New Stack Makers, Matthew O’Riordan, CEO of Ably, explains how infrastructure originally built for human collaboration is now well-suited for long-running AI agents. While Ably initially resisted positioning itself as an AI company, the rise of agents that reason, call tools, and operate over extended periods revealed a natural fit for its real-time communication platform.
#1619
May 6 · 32 min
Why the Linux Foundation adopted MCP, with Jim Zemlin and Mazin Gilbert
Agentic AI is advancing rapidly, with open-source projects racing to keep pace with real-world deployment. To accelerate progress, the Linux Foundation consolidated key technologies—Model Context Protocol (MCP), Goose, and AGENTS.md—under the newly formed Agentic AI Foundation (AAIF) in late 2025. At the MCP Dev Summit in New York City, Linux Foundation CEO Jim Zemlin and newly appointed AAIF executive director Mazin Gilbert discussed this transition. Zemlin explained that leading both organizat
#1617
May 1 · 23 min
Fresh data has us asking, does AI demand Kubernetes?
Kubernetes is rapidly emerging as the de facto operating system for AI, with two-thirds of organizations using it for generative AI inference and 82% adopting it in production. Its ecosystem — including tools like Kubeflow — enables organizations to build, scale, and retain control of AI systems through open, community-driven infrastructure. Bob Killen of CNCF and Liam Bollmann-Dodd of SlashData shared insights from recent reports showing that AI success still hinges on strong engineering fundam
#1616
April 30 · 26 min
How SUSE positions itself as the infrastructure layer for the AI era
In this episode of The New Stack Makers, Pete Smails outlines how SUSE is evolving from its Linux roots into an AI-native infrastructure platform. Speaking at KubeCon + CloudNativeCon Europe 2026, Smails explains the company’s strategy to unify AI, containers and virtual machines on a single open, enterprise-ready foundation. Central to this is SUSE Rancher Prime, which enables consistent orchestration across hybrid and multi-cloud environments, alongside SUSE Virtualization for modernizing lega

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