5-Minute DevOps: Why SAFe Fails to Deliver CD at Scale

I was asked recently why SAFe fails. Here’s one major reason.

The Scaled Agile Framework (SAFe) is the best-marketed framework sold to executives by the Agile Industrial Complex. Its goal is to improve delivery, starting with solving the problem of coordination at scale by managing dependencies through process. Instead of reducing coupling between teams, it formalizes it. SAFe layers synchronization meetings, planning cycles, and roles such as the “Release Train Engineer” across the organization to keep everyone aligned.

On paper and to the uninformed, that sounds a reasonable way to handle complexity. In practice, it locks in the very dependencies that prevent continuous delivery.

What SAFe advocates say: “That’s just the starting point. You’re expected to move beyond that.”

I’ve lived through a SAFe implementation and witnessed several others firsthand, and I know exactly why they fail to move beyond that.

Reality: It’s ironic that a group of people who are supposed to be resolving issues at scale seem to have so little clue about how things work at scale.

The Coordination Trap

For SAFe to “work,” everyone needs to be trained on the same process, and all the teams in a release train need to operate in lockstep. The “release train engineer” and “scrum of scrums” tightly couple teams around synchronized delivery and process. While this may seem to reduce chaos in the short term, that coupling is the exact opposite of what you need for continuous delivery.

In SAFe, every team must ask permission to make changes that affect anything beyond its local scope. Improvement becomes a group decision, and group decisions at enterprise scale move slower than glaciers. Even if a team sees a better way, it can’t simply act; it must align, escalate, and get consensus.

Continuous delivery, by contrast, depends on independent, decoupled teams that can improve their flow immediately and deliver value safely without waiting for the train schedule. CD requires us to use engineering to handle dependencies. In fact, if we take the constructive constraints of CD seriously, we cannot help but improve the engineering to enable that.

The Training Paradox

SAFe’s defenders often say the model is just a “starting point.” But because SAFe requires everyone to be trained on the same standardized process to maintain consistency across hundreds or thousands of people, the “starting point” becomes the destination.

When turnover happens — and it always does — new hires are trained on the official, baseline SAFe process, not whatever “improved” variant someone hopes to evolve toward. The improvement loop is broken because the training system anchors everyone to the original design.

The cost of formal change is high — retraining, documentation, governance updates, and alignment across roles — so improvements don’t happen organically. Unless change is driven from the top, it doesn’t happen at all. And executives are typically the farthest from the work, so the changes they drive are often counterproductive.

The Management Self-Preservation Problem

Continuous delivery demands decoupling teams — breaking dependencies so each can deliver independently. But in SAFe, those dependencies give structure and purpose to management roles like the Release Train Engineer.

Real improvement would mean shrinking the RTE’s responsibilities until the role disappears. That’s not a technical problem — it’s a political one. You’re asking people to dismantle the coordination system that justifies their position. Unsurprisingly, they resist.

When your operating model depends on preserving layers of coordination that continuous delivery renders unnecessary, you’ve built a system that’s optimized for self-preservation, not improvement.

Scaling Dysfunction

The entire premise of SAFe is to manage complexity through hierarchy and synchronization. But effective scaling isn’t about adding more layers of coordination; it’s about removing dependencies so teams can move safely on their own.

Continuous delivery scales by improving flow and feedback, not by adding more meetings to coordinate bad flow. Every added synchronization point adds latency, every shared dependency adds risk, and every “train” schedule adds drag.

SAFe’s mechanisms for control — the trains, the ceremonies, the alignment meetings — are precisely what prevent continuous delivery from emerging.

The Outcome

SAFe scales coordination, not delivery. It turns what should be local learning loops into enterprise-level governance processes. The result is predictably slow, brittle, and expensive.

It delivers the illusion of progress — more charts, more ceremonies, more roles — but not the one metric that actually matters: the ability to deliver working software safely and continuously.

If you want to deliver continuously at scale, don’t scale SAFe.

Scale learning, autonomy, and flow instead.