Broadcom and Platformengineering.org Launch Platform Engineering 2.0 for AI Era
The new framework evolves internal developer platforms to support AI-native workloads and autonomous agents.
Broadcom and Platformengineering.org have introduced "Platform Engineering 2.0," a strategic evolution of internal developer platforms designed to meet the demands of the AI era. The initiative argues that traditional platforms, while foundational, are now insufficient for the scale and nature of AI-native workloads.
This shift focuses on transforming existing infrastructure to support non-human AI agents and real-time cost management. Rather than proposing a complete rebuild, the framework presents this as an extension of current foundations. Broadcom noted via The Register that platforms built over the last few years were designed for human developers shipping containerized apps at a human pace, stating, "That world is gone."
The Shift from 1.0 to 2.0
Platform Engineering 1.0 centered on creating "golden paths" and self-service internal developer platforms (IDPs) to help human developers deploy containerized applications. However, the rise of AI coding assistants has shifted the primary bottleneck in the software lifecycle from the act of writing code to the process of delivery.
Furthermore, the emergence of AI agents as active users of these platforms necessitates entirely new capabilities. These include specialized identity management, dynamic GPU allocation, and sophisticated token management—requirements that were not priorities during the first wave of platform engineering. The scale of adoption is already significant; according to Google's 2025 DORA research, 90% of organizations now report using an internal platform, and 76% have dedicated platform teams.
Why AI Demands Evolution
Traditional platforms are increasingly becoming bottlenecks for AI adoption. Without evolving to a "2.0" model—which incorporates AI-native substrates, multi-persona experiences, and composable design—enterprises face significant operational risks. These include inefficient GPU spending and security vulnerabilities, such as prompt injection.
Financial governance is a critical driver for this evolution. Embedded FinOps are now essential to curb systemic waste; 97% of IT leaders believe some of their public cloud spend is wasted, with 52% estimating that this waste exceeds 25% of their total public cloud budget. By shifting security down and integrating real-time cost controls, Platform Engineering 2.0 aims to prevent these inefficiencies from scaling alongside AI growth.
What's Next
Industry observers will now watch how enterprises implement these "AI-native substrates" to govern autonomous agents. The primary challenge remains the transition from human-centric workflows to those that can support the velocity and autonomy of non-human actors while maintaining strict security and budgetary guardrails.