Jul 29, 2026

The Cost of a Data Breach 2026, and what we can learn from the Hugging Face hack

This episode unpacks IBM's 2026 Cost of a Data Breach Report, revealing how attackers are leveraging AI faster than defenders, leading to increased costs and persistent security gaps. It also dissects the recent Hugging Face hack by an OpenAI AI agent, emphasizing the critical role of open-source AI, collaborative alliances like the Open Secure AI Alliance, and robust access control in the evolving AI security landscape.

Jul 28, 2026

How Forward Deployed Engineering is done at Factory — Eno Reyes

Eno Reyes discusses Factory's unique approach to Forward Deployed Engineering, positioning FDEs as the "tip of the spear" for product feedback rather than professional services. He introduces the "software factory" concept, an AI-driven, automated pipeline from signal to deploy, enabled by Droid—a model-independent, air-gappable agent harness. Reyes emphasizes "agent readiness" through robust validation loops as key to achieving autonomy, citing successes like migrating massive codebases. He frames the FDE's role as a balancing act, demonstrating the future of autonomous engineering without alienating customers, akin to Disney's Epcot analogy.

Jul 28, 2026

How Forward Deployed Engineering is done at Ramp — Leo Mehr

Leo Mehr, Director of Engineering at Ramp, outlines two critical principles for Forward Deployed Engineering (FDE): "Always Be Scoping" to ensure the delivery of the right product by deeply understanding customer needs and context, and "Scale with Tokens" by strategically integrating AI agents into FDE workflows. He highlights Ramp's success in automating request intake and spec generation using AI, emphasizing the need for both human judgment and AI-driven efficiency to thrive in the future.

Jul 28, 2026

The Dirty Secret of Forward Deployed Engineering — Natalie Meurer, Sierra

Natalie Meurer discusses the "dirty secret" of Forward Deployed Engineering (FDE), arguing that its definition has broadened so much it has lost specific meaning, yet remains critical in the age of AI. She traces its evolution at Palantir from pure DevOps to data integration, custom solutions, and enablement, highlighting customer accountability as its enduring core. Meurer contends that as AI makes code cheap, the focus shifts to integrating data, understanding customers, and achieving outcomes—making agent engineering a direct descendant of FDE under a new name, especially evident in the move towards outcome-based pricing models.

Jul 28, 2026

OpenAI’s Plan to Make ChatGPT the Everything App — Akshay Nathan, OpenAI

Akshay Nathan, head of Core Product Engineering at OpenAI, discusses the journey and rationale behind ChatGPT Work. He explains how Codex's unexpected adoption by non-developers led to a unified agent harness, blurring the lines between developer and knowledge worker tools. The conversation delves into model capabilities, the role of artifacts and interactive 'Sites' in replacing traditional documents, and how AI fosters a new era of 'T-shaped' generalists. Nathan emphasizes the shift in productivity bottlenecks to 'ideas and taste' and the importance of 'quality at-bats' over mere 'motion' in an AI-powered development landscape.

Jul 28, 2026

Llama.cpp vs vLLM: Which Local LLM Engine Actually Scales?

Explore the strengths and optimal use cases of `llama.cpp` and `vLLM` for local LLM inference. `llama.cpp` excels on consumer hardware with optimizations like quantization and CPU support, while `vLLM` is designed for production-scale efficiency with features like continuous batching and speculative decoding on high-performance accelerators.