Does the End of SaaS Also Mean the End of SAFe?

The Rise of AI-Driven Architectures

The emergence of AI-native systems is challenging traditional enterprise models. As companies transition from centralized SaaS solutions to dynamic, on-demand, and composable architectures, a critical question arises: Does this shift signal the decline of SAFe (Scaled Agile Framework)?

The warning signs have been present for some time. SAFe has evolved into an ecosystem of its own, continuously expanding while delivering diminishing returns. Critics, including proponents of Unfix, argue for more adaptable frameworks that align with today’s complexity. Even without AI, SAFe has struggled to keep pace with modern enterprise demands.

The Issues at Hand

🔹 From SaaS to AI-Native Workflows
AI is replacing monolithic SaaS applications with autonomous AI agents, dynamic workflows, and serverless infrastructure. Teams no longer depend on rigid platforms but instead leverage data meshes and automated deployments.

🔹 SAFe’s Scaling Approach vs. AI-Driven Adaptability
SAFe was built around human coordination—structured backlogs, ARTs, and PI planning cycles, assuming large teams working toward a unified goal. AI, however, decentralizes decision-making in real-time, enabling smaller, more autonomous teams. This shift aligns with emerging development paradigms such as Cell Development (see: Autonomous Coding Agents & The Cell Paradigm).

🔹 Continuous Flow Over Fixed Increments
AI-driven deployment operates in continuous, automated cycles, challenging SAFe’s fixed iteration model. Traditional planning horizons of months are increasingly obsolete. Amazon, for instance, has been deploying to production every second since 2015—what should the standard be today?

🔹 From Agile Teams to AI-Augmented Teams
The shift isn’t from Agile to Waterfall; it’s from human-driven Agile to AI-augmented, self-organizing teams. If AI can optimize backlogs, resolve dependencies, and facilitate coordination, what role does SAFe’s extensive structure still play?

🔹 Building a New Stable Core
Organizations are moving away from stability through large-scale alignment. Instead, small, independent teams must construct a stable core through robust development, deployment, and test automation. SAFe, in its current form, does not adequately prioritize these engineering fundamentals as essential individual skillsets.

The Future of SAFe in an AI-Driven World

SAFe won’t disappear overnight, but its value proposition is increasingly challenged. The focus is shifting from orchestrating human teams to fostering AI-human collaboration at scale. If SAFe is to remain relevant, it must undergo fundamental changes to align with this new reality.