How Daniel Stenberg, Founder of curl, is Navigating the AI Onslop

In this episode of the MonkCast, James Governor sits down with Sanjay Sarathy, SVP of Developer Experience at Cloudinary, to discuss developer trust, and why it still matters in the agentic software development era. With more than four million developers signed up, and 40% of new registrations now coming from agents, Cloudinary is rethinking what trust means, but maintaining true to its core values. Sanjay walks through the principles guiding that work: products that work as promised every time, human support that scales, accuracy in AI-assisted answers, transparency, long-term API stability, keeping the developer voice in the product loop, and investing in education for students and early-career developers.

In this RedMonk Conversation, Anne Bertucio de Hollembeak, COO of ROOST (Robust Open Online Safety Tools) , chats with Kate Holterhoff about the importance of open source tools in trust and safety, especially in the age of AI. She shares insights on building safety tools, the role of open source, and how these efforts can create a safer online environment for everyone.

Why do some teams see massive speedups from AI coding agents while others barely notice a difference? In this RedMonk New Builders Conversation with AWS, Kate Holterhoff talks with Liam Greenamyre, Principal PM of Developer Platforms at AWS, about the uneven impact of AI on software development and how to restructure work so agents can succeed. Liam explains why making tasks verifiable is the single biggest lever, then walks through the Agent Toolkit for AWS: a remote MCP server, 100+ skills, plugins, and a rules file that work with Claude Code, Codex, Kiro, and more. They dig into how a single RunScript tool covers 15,000+ AWS APIs token-efficiently, how IAM context keys separate human and agent actions, how agents discover new services like Aurora DSQL, and why isolated dev accounts make safe sandboxes for autonomous agents. Liam closes with a bold prediction: the biggest changes ahead are organizational, not technological.

Most of an enterprise application stack is open source that nobody is paid to maintain. Gunnar Hellekson of Red Hat puts it at 60 to 70 percent, and that gap is what IBM's Lightwell is built for. He walks James Governor through the mechanics: members scan and triage their own dependencies, submit what they find with the source identity stripped out, and get fixes back after an embargo period before those fixes reach a wider network and, where a maintainer still exists, the upstream project. Financial services goes first. Hellekson is candid that plenty of customers cannot use the service yet, because joining would only lengthen a patch backlog already measured in months. Mythos, the two agree, mostly revealed how bad things already were. They also work through token economics, why nobody needs to scan OpenSSL separately, and why a fix should end up as deterministic code rather than something an AI keeps rediscovering.

In this RedMonk conversation, Pankaj Gupta, Senior Director of Product Marketing, VCF Division, at Broadcom, chats Platform Engineering in the AI era with Stephen O'Grady. Gupta explains that more than 90% of organizations run an internal platform, but despite widespread adoption, Gupta thinks most platforms are hitting two ceilings. They were built, in his phrase, "AI blind," and they were built for exactly one user, the developer. AI has already moved the bottleneck from writing code to getting it into production, and the user base is about to change shape. Also in this episode: when golden paths harden into golden cages, why FinOps and security can no longer be bolted on, and Gupta's five pillars for platform engineering 2.0. The RedMonk conversation is sponsored by Broadcom.