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. For more content from The New Stack, subscribe on YouTube at: https://www.youtube.com/c/TheNewStack

  1. 5 dage siden

    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. On this episode of The New Stack Makers, Summit’s Byron Dill argues that many enterprises have become overly reliant on public cloud infrastructure, using it for workloads that may be better suited to private environments. Rather than treating the cloud as a one-size-fits-all solution, Dill advocates for a more segmented approach that places workloads where they make the most sense based on cost, security and management requirements. The conversation draws parallels to the rapid adoption of AI, where organizations often discover unexpected costs after implementation. Dill explores when repatriating workloads from the public cloud to private infrastructure can reduce expenses, simplify data management and improve control, while examining the costs, timelines and industries best positioned to benefit from a private cloud strategy.   Learn more from The New Stack around cloud spending:  How to Cut Cloud Waste Without Constricting Developer Productivity  AI agents need to spend money — Stripe and iWallet are building the rails  Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

    37 min.

  2. 18. jun.

    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 CTOEddie Kimwitnessed growing up. Unlike reactive chatbots, Cofounder can take action across payroll, HR, benefits, scheduling, insurance, and accounting workflows by leveraging data already stored within Gusto. Users interact with the platform through text messages or Slack, while a consent framework ensures access to sensitive payroll and employee data remains tightly controlled. Businesses can grant explicit permissions and gradually increase autonomy as trust is established. The platform also integrates with third-party tools such as Google Workspace, enabling it to gather data, perform calculations, run payroll, and communicate results automatically. Kim said the product was built by a five-person team in just eight weeks using Claude Code, which he believes demonstrates how AI is expanding software creation beyond traditional engineering roles. Looking ahead, Gusto plans to add more integrations and eventually enable customers and developers to share reusable, industry-specific business automations. Learn more from The New Stack around how AI is expanding software creation beyond traditional engineering roles: How AI Is Reshaping Software Engineering: Key Takeaways From DeveloperWeek 2025 AI and the Future of Code: Developers Are Key The Engineer in the AI Age: The Orchestrator and Architect Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

    29 min.

  3. 11. jun.

    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.  He believes developers, despite being less vocal, build the products that power the modern world. The event began as a small meetup that quickly gained popularity, filling a gap between highly specialized technical gatherings and broader business-focused conferences. Former GitHub CEO Thomas Dohmke highlights another benefit: giving developers a platform to share the stories behind their work and inspire peers.  Discussing the future of software development, Dohmke predicts AI agents will handle much of the coding, while developers focus on managing ideas, prompts, and workflows. Ahmetovic agrees, arguing that developers will remain essential, spending less time typing code and more time thinking, orchestrating, and creating new solutions.  Learn more from The New Stack around the latest in developer community growth:  How Community Helps Developers Grow  Empowering Developers Is Critical to Drive AI Innovation  3 Ways Organizations Can Redefine the Developer Experience  Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

    50 min.

  4. 27. maj

    Why MotherDuck refuses to fork DuckDB

    At a recent MCP developer summit, The New Stack spoke with Till Döhmen, AI lead atMotherDuck, about the company’s growing role in the evolving DuckDB ecosystem. Backed by investors includingTomasz Tunguz, MotherDuck is commercializing the open-source analytical databaseDuckDBwhile also expanding how employees interact with data through AI agents rather than traditional dashboards. Döhmen emphasized the company’s close collaboration withDuckDB FoundationandDuckDB Labs. Because MotherDuck operates what he described as the world’s largest fleet of DuckDB databases, the startup regularly pushes the database to its limits and feeds insights back to the core maintainers. Rather than forking DuckDB to create proprietary advantages, MotherDuck instead extends the platform through its existing architecture while contributing core improvements upstream when needed. The conversation highlighted the delicate but productive relationship between venture-backed companies and the open-source projects they commercialize, positioning MotherDuck as another example of startups driving both OSS adoption and strong business growth simultaneously. Learn more from The New Stack around the latest in DuckDB: DuckDB: Query Processing Is King DuckDB: In-Process Python Analytics for Not-Quite-Big Data Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

    28 min.

  5. 21. maj

    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 developmentMikhail Vink argued that competitors such as Microsoft Copilot, Anysphere Cursor, and Windsurfare all tied to either AI labs or cloud providers. By contrast, JetBrains says its independence allows customers to switch freely between models fromOpenAI,Anthropic, andGoogle Cloudwithout being locked into one ecosystem. That flexibility underpins JetBrains’ broader AI strategy. Rather than building its own foundation model, the company is focusing on orchestration and governance through JetBrains Central, announced in March as a management layer for AI agents, usage controls, analytics, and consumption-based billing. Vink said the company’s profitability, 16 million users, and 300,000 commercial customers from its long-running IDE business have allowed it to remain venture-free and model-neutral. JetBrains argues that as developers increasingly swap between AI models, neutrality may become more valuable than owning the models themselves. Learn more from The New Stack around the latest in AI coding-tools:  JetBrains ‘Agentic’ AI Agent Helps Automate Coding Tasks JetBrains: AI agents are about to repeat the cloud ROI crisis  JetBrains names the debt AI agents leave behind Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

    26 min.

  6. 15. maj

    Why Block handed Goose to the Linux Foundation

    What began as an internal developer tool atBlockhas 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 intoAmazon Web Services. After deploying Goose companywide, Block open-sourced the tool under a permissive license, leading to rapid adoption across the developer community. But according to Manik Surtani, Office of the CTO, Block and Co Founder of Agentic AI Foundation, early momentum exposed governance challenges. Although Goose was technically open source, Block retained trademark ownership, creating concerns for enterprises seeking truly independent governance. To address this, the team partnered with the creators ofAnthropicand the Model Context Protocol community to establish theAgentic AI Foundationunder the umbrella of theLinux Foundation. Goose, MCP, and Agents.MD became the foundation’s initial projects, chosen largely to accelerate the launch of the new organization and create a collaborative ecosystem around agentic AI development. Learn more from The New Stack around the latest in open-source AI:  Anthropic extends MCP with a UI framework Why the Linux Foundation adopted MCP, with Jim Zemlin and Mazin Gilbert Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

    20 min.

  7. 13. maj

    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 in closed ecosystems. Kundavaram said agents can optimize for cost instead of speed, choosing cheaper compute engines when appropriate — but only in open architectures with multiple options. Closed systems force every query through high-cost paths. He also warned that fragmented data and weak context create a “triple whammy” of poor AI responses, soaring analytics bills, and wasted compute. While many organizations respond by tightening controls, Kundavaram argued the better path is investing in open infrastructure, interoperability, and strong semantic data practices before AI costs spiral further.   Learn more from The New Stack around the latest in enterprise data systems:  Enterprise AI Success Demands Real-Time Data Platforms AI Agents Are Morphing Into the 'Enterprise Operating System' Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

    23 min.

  8. 12. maj

    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. Both emphasized that effective AI FinOps requires intelligent orchestration, routing workloads to the cheapest capable models instead of defaulting to expensive frontier models. Sharma noted that AI costs extend beyond APIs to GPUs, storage, training, and organizational adoption. They also cautioned against relying solely on LLMs for operational automation. Deterministic systems, observability metrics, and human approvals remain essential guardrails. Ultimately, both stressed that FinOps is primarily an organizational and cultural discipline, recommending newcomers start with the FinOps Foundation before investing in tools. Learn more from The New Stack around the latest in FinOps:  Why FinOps Isn’t About Saving Money  FinOps Foundation’s FOCUS 1.2 Expands to SaaS, PaaS  Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

    28 min.
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Om

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. For more content from The New Stack, subscribe on YouTube at: https://www.youtube.com/c/TheNewStack

Oplysninger

  • Skaber
    The New Stack
  • Aktive år
    2014 - 2026
  • Episoder
    300
  • Vurdering
    Ikke anstødeligt
  • Copyright
    © All rights reserved
  • Websted for serie
    The New Stack Podcast

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