Differences in the basic assumptions software developers and systems engineers make about how a project will be structured mortar over many projects into an enduring wall of confusion. This wall manifests itself in the systems/software integration phase where the bulk of rework occurs in the vast majority of projects. To remove this source of unrealized value, both groups must change how they communicate about software and system interfaces.
The Real Source of the Conflict
Many depict this as Agile vs. Waterfall. But those pictures miss the mark. Developers operate in short sprints, shipping testable increments every two weeks. Systems engineers are planning verification activities that may not run until 18 months from now. Neither is wrong, as long as you’re talking about what the process was designed to do. The problem is that they’re tasked with making the same thing but on different clocks.
The V-Model lifecycle where most systems engineering work takes place was designed for physical products and long procurement cycles. Agile was designed for software-based products that can be deployed and changed continuously. So, when the developer asks “can we change this interface?” and the systems engineer responds, “that interface was locked in the architecture review six months ago,” both are right. They’re just working from different blueprints that no one brought to the same table.
Those differences hurt most when they hit the budget. Finding and fixing a requirements error during coding or testing can cost up to 30 times more than resolving it during the design phase (Software Engineering Institute, Carnegie Mellon University). Most requirements errors aren’t even random. They’re the result of missing details, and those missing details go back to the fact that the developer deciphering the requirements wasn’t the person who wrote them.
Delivering Requirements as Data, Not Documents
The most significant advice you can give systems engineers is don’t rely on static documents. Move to Model-Based Systems Engineering (MBSE). If a systems engineer needs to describe an interface, they can write a Word document. A developer will then read that document, interpret it, and manually implement what they believe is being asked for. If the same interface is represented in a SysML model, the developer can query it programmatically, they pull the precise information they need in a structured way without any interpretation.
This isn’t a trivial difference in process preference. The nature of the requirement itself shifts depending on where it lives. As a written sentence in a document, it remains static. As a requirement in an MBSE model, it is structured data with defined relationships to other requirements, system behaviors, and test cases. This data can be version-controlled, differenced, and traced automatically.
To create that shared technical foundation, many engineering organizations are having their teams take a specialized mbse course to ensure systems engineers and developers alike understand how to build and read a digital system model. The aim is not to turn every developer into a systems engineer; it is to provide enough shared language on both sides that handoffs cease to be translation exercises in frustration.
Replacing Static ICDs With Executable Contracts
Using live API contracts and custom schema validation achieves the same end with better results. One team defines the interface in a machine-readable model. The contract lives in a repository that both teams can access. The other team writes to that contract, which can be automatically validated. If the software team steps outside the model, systems engineers are immediately informed before any code is released. There’s none of the lag that comes with translating a change to a Word doc and emailing it over the fence.
The shift from bloated, static documents to a model exposing that same content in a consumable form is a major step forward. It’s a faster, more efficient way of working, and it’s only possible with machine to machine interoperability. This is how systems engineering boundaries become something developers can actually work with, not as constraints passed down from above, but as guardrails that integrate directly into the development pipeline.
Connecting the Toolchains
One of the most prevalent sources of duplicated work is the disconnect between systems engineering tools and software development tools. Systems engineers use tools like Cameo/MagicDraw. Developers are in Jira, GitHub, GitLab, etc. When these toolchains are not connected, your requirements traceability is just a straight-up manual job, someone copies information from one system into the other, and those two records immediately begin drifting apart.
This is not a nice-to-have API integration. It’s the only mechanism through which requirements traceability becomes something you don’t have to consciously think about all the time. One of your devs closes a ticket in Jira? The linked system requirement in the MBSE model should go from “IMPLEMENTING” to “IMPLEMENTED”. Systems engineer revises a requirement? The associated development tasks should automatically update to reflect that. This integration exists, but it’s the kind of non-trivial work that needs real, honest labor, so it doesn’t happen without intent.
Cross-Training Changes the Conversation
Technical integration is nice and all, but you can’t just assume that people know what they’re reading when they look at another team’s documents. Systems engineers who’ve never dealt with microservices or containers can’t responsibly design specifications for a software team. And software developers with no concept of systems engineering or hardware constraints don’t know which shortcuts are too dangerous.
That’s why cross-training matters. Everyone needs to have a general sense at least of what the other side is concerned with. If the developers understand a bit about what’s involved in systems engineering, they’re less likely to inadvertently paint themselves into a corner because they only focused on what’s happening at the code level. And vice versa.
We’re all here to ship a system that works. The question is whether the engineers can get the integration sorted faster because they recognize something from the earlier conversations. Or whether they’re doomed to reinvent the wheel, sending descriptions and pseudo-requirements back and forth until someone gives up and books a conference room.
