Orbit - An Hg software leadership podcast

Published in a week when Lovable's valuation doubled to $13.3 billion, up from $6.6 billion in December, this episode presents Ryan Meadows story of joining Lovable as a customer before becoming its Chief Revenue Officer, and how that experience shapes everything about how he thinks about AI, growth and the future of software. Hg's Tim Harrison sits down with Ryan to explore how they reached $400 million ARR in just 15 months, what it means to build an organisation entirely without legacy tooling, and why Ryan thinks most enterprises are still barely scratching the surface of what AI can do for their people.

Ryan walks through their three-stage model of AI transformation, from getting everyone to prototype, through hardening load-bearing applications, to ultimately rebuilding workflows from first principles. He shares how Lovable disrupted its own seat-based pricing model to move to consumption in the enterprise, and why that shift unlocked a customer who went from 200 product managers to 8,500 active builders in two months. He also reveals how they use their own platform to run go-to-market, from an AI command centre that tells reps exactly what to do, to a CPQ and e-signature flow built entirely in-house. As Ryan puts it, the company's tagline is "we want to be your co-founder," and he believes that applies just as much inside an enterprise as it does for a first-time founder raising funding.

Every December, Rob Toews publishes ten AI predictions in Forbes, then comes back a year later and grades himself in public. That habit of putting a stake in the ground, and owning the misses, makes him one of the more interesting voices in the space. In this conversation with Jon Wulkan, he explains why the frontier has narrowed to a handful of Western labs, why even well-resourced challengers have struggled to keep pace, and why the much-feared "SaaS apocalypse" is probably overdone.

They also dig into the economics underneath the hype: why model prices are likely to rise once the big IPOs land, why one of the three remaining frontier players has a structural funding edge the others can't match, and why an obscure accounting question about chip depreciation could reprice the entire AI infrastructure trade. Along the way, Toews reaches for a comparison that sticks: we're building data centers that draw twice the power of San Francisco, while the human brain runs on 20 watts. His advice for vertical software CEOs? Hire for slope, not y-intercept..

In this episode, John Cranmer is joined by Gil Elbaz, Co-Founder and Chief AI Officer at Onyx Security, the company building the secure AI control plane for the agentic era. Gil, formerly in the CTO office at Nvidia working on multi-agent infrastructure, argues that the AI attack surface has fundamentally changed. The old boundary between what is yours and what is not has collapsed, and every agent, every MCP, every tool connection is now part of the perimeter.

The conversation moves from the rise of shadow AI inside enterprises, where employees reach for any tool that makes work faster, to the harder problems underneath: rogue agents taking destructive actions they were never asked to take, multi-agent communication happening invisibly through Slack and email rather than direct A2A channels, and offensive AI systems like Mythos finding more zero-days in weeks than internal red teams find in years. Gil shares his playbook for getting your arms around it: visibility first, then policy, then runtime protection. As he puts it, the right seatbelt is what lets you drive faster.

The inventor of DevOps explains why AI needs engineering rigour and human collaboration.

The engineer who coined "DevOps" in 2009 thinks he is watching the same pattern play out again, only faster. In this episode of Orbit, Patrick Debois joins Nathaniel Barnes, Hg's portfolio CTO, at our annual Digital Summit in Paris, to map the parallels between the DevOps movement and what is happening right now with AI agents in software teams. The framing question: what if context is the new code?

Patrick unpacks the four phases of his context development lifecycle, generate, evaluate, distribute, observe, and explains why the maturity of a company's CI/CD pipeline is the single best predictor of how well it will absorb AI. He and Nathaniel dig into context drift, customer-facing "vibe coding" as a discovery engine, the silos that agents are quietly breaking down, and why the companies winning right now are the ones that skipped the 27-step plan and just started. As Patrick puts it: "We are at the age where it doesn't need to be perfect. We just need to be there." Essential listening for any technology leader navigating this moment.

When Jonathan Sanders pitched Light to investors, the reaction was unanimous: rebuilding ERP would take a decade and a hundred million dollars. He did it in two years, with AI at the core. Today Light powers AI unicorns including Lovable and Legora, and Jonathan joins Hg director Soren Holt to explain how. The conversation goes well beyond automation. It's a builder's account of a first-principles redesign.

Jonathan and Soren cover the move from template-based OCR to context-aware agents, why eighty percent of AI's value comes from doing things that were previously impossible rather than making old tasks faster, and how Light's customers now sweep entire transaction populations during audits rather than sampling. Jonathan walks through Light's hackathon programme with CFOs, the operating model behind a remote engineering organisation, and the shift from finance as operator to finance as orchestrator. The line that lands hardest: "Fear is not a strategy." An essential listen for any finance leader thinking about what 2030 actually looks like.