If you’re responsible for software today, the pressure isn’t coming from one direction – it’s coming from two.
On one side, development is accelerating. AI is increasing the volume of code, the speed of iteration, and the expectation that teams can move faster without adding headcount.
On the other, the expectations around compliance haven’t changed – in fact, they’ve intensified. License obligations still apply. Vulnerabilities still matter. SBOMs still need to be accurate. And regulations are codifying these requirements.
Individually, these expectations make sense. Together, they expose a gap.
The Model Worked Until the Inputs Changed
For a long time, that model worked reasonably well. Most third-party code entered through package managers, dependencies were explicitly declared, versions were known, and provenance was traceable. It wasn’t perfect, but it created a system that was at least understandable and, in most cases, governable.
That environment is changing quickly. Code is no longer introduced primarily as well-defined components. Increasingly, it appears as fragments… snippets generated inline, logic assembled without a manifest, without a version, and often without a clear origin. What used to be discrete building blocks is now something far more fluid.
As that shift takes hold, the assumptions behind traditional SCA begin to break down. Tools designed to analyze dependency trees struggle when there are fewer dependencies to analyze, and approaches that rely on matching known components lose effectiveness when the code no longer exactly matches a known component. The issue isn’t just reduced accuracy; it’s a widening gap between what is actually in the codebase and what your systems are capable of seeing.
That gap shows up in ways that are becoming increasingly familiar. License obligations go unidentified. Vulnerabilities slip through undetected. SBOMs no longer reflect the reality of the software they are meant to describe. For engineers, this creates risk that is difficult to interpret in the moment and even harder to address without slowing down. For legal and compliance teams, it creates exposure that is difficult to quantify and even harder to report with confidence.
The Breakdown Isn’t Just About Technology – It’s Timing
The instinct, naturally, is to respond the way we always have… by reinforcing the controls downstream. Scan later, audit before release, introduce additional gates to catch what might have been missed earlier.
But that approach depends on something that is no longer true: that humans can keep up with the pace of code creation.
The result is a model that creates friction on both sides. For developers, compliance becomes either a blocker that interrupts the workflow or a source of rework discovered too late. For legal and security teams, it becomes a bottleneck that constrains delivery – or, in some cases, something that is bypassed altogether in order to maintain speed.
At that point, the problem isn’t technology. It’s timing. And when timing is the issue, adding more controls in the same place doesn’t solve it.
- Code volume is exploding
- Open Source is everywhere
- AI is generating code at scale
- Provenance is increasingly unclear
- Can’t keep up with volume
- Is blind to unmanaged code and snippets
- Becomes a bottleneck
From Gatekeeping to Built-In Compliance
What has to change is where compliance happens.
Instead of something that is checked after code is written, it has to become something that happens as code is created – not as a separate step, and not relegated to a periodic activity, but as part of the development process itself. This is the shift from gatekeeping to built-in compliance, and it reflects a broader change in how software supply chain integrity is maintained.
In practical terms, that means moving toward a model where the systems involved in building software can also interpret it as it is being created. Open source, third-party, and proprietary code can be identified as it appears, even when introduced as modified or partial snippets. License obligations – including more complex or mixed-license scenarios – can be understood in context. Copyright considerations can be surfaced early, and known vulnerabilities can be detected in real time, with guidance provided while decisions are still being made.
The impact of that shift is less about earlier detection and more about continuous alignment. Compliance is no longer something that trails behind development; it moves with it.
For developers, that changes the experience in a meaningful way. The expectation is no longer that they act as licensing or security experts, nor that they pause their workflow to run scans or interpret results. Instead, guidance becomes part of the development process itself… present in the moment, aligned with the task at hand, and designed to support forward progress rather than interrupt it.
Late inspection leads to:
Rework. Delays. Release friction.
In home construction, that’s like waiting until final inspection to check the wiring or foundation.
It doesn’t scale. It guarantees problems.
For legal, security, and compliance teams, the shift is just as significant, but in a different direction. Rather than reconstructing what happened after the fact, they gain a continuous view into what is actually entering the codebase – how the code is composed, what licenses apply, where risks exist, and how those risks should be addressed. Because that visibility is embedded into the development process, it creates a level of control that is difficult to achieve through periodic audits alone.
A Different Model for How SCA Works
Audits, in this context, don’t disappear, but they do change. What has historically been a slow, manual, and periodic process can become something far more continuous. Analysis that once required significant human effort across large codebases can be automated, updated in real time, and combined across multiple inspection layers – snippet detection, dependency analysis, license intelligence, and vulnerability identification. The result is not just faster audits, but a fundamentally different role for them: less about risk detection, more about compliance validation.
- Slow and manual
- Episodic — happens
at key moments - Results require human interpretation
- Snapshot view only
- Automated and continuous
- Always on —
not episodic - Structured outputs generated automatically
- Updated as code evolves
It’s tempting to think of this as simply adding AI capabilities to existing tools, but that framing misses the broader shift. This is not about incorporating a chatbot or introducing a new interface. It is about changing how software composition analysis is delivered and consumed in an environment where AI is an active participant in development. In that environment, the primary actor is no longer just the human navigating a system; it is the system itself, operating continuously and at scale.
SCA, in turn, has to evolve to meet that reality. It has to be accessible programmatically, capable of operating continuously, and designed to integrate directly into the processes that are generating code in the first place.
Organizations that move in this direction are not simply improving their tooling. They are changing how software is built and governed.
That alignment has always been the goal. It has just been difficult to achieve within a model that separates development from compliance.
Where This Is Heading
The same tension that exists at the beginning – between speed and control – is what ultimately drives this shift.
On one side, development will continue to accelerate. AI will generate more code, increase iteration speed, and raise expectations around how quickly teams can deliver.
On the other, the need for compliance doesn’t go away – in fact, it ramps up. License obligations still apply. Vulnerabilities still matter. SBOMs still need to be accurate.
What changes is how those two forces are reconciled.
If AI is going to write an increasing portion of the code, it also has to take on more responsibility for understanding that code… where it comes from, what risks it carries, and what obligations it creates.
That responsibility can’t sit entirely with human teams operating downstream.
And in many ways, it marks the beginning of a different model… one where speed and compliance are no longer in tension, but aligned by design.
FossID Agentic SCA is the New Model
This is exactly the problem we set out to solve with FossID Agentic SCA. It’s our approach to making software supply chain integrity continuous, real-time, and built directly into how code gets written – so developers can move fast with confidence, and legal and security teams regain the visibility and control they need.
If this sounds like what you’re seeing in your organization, take a closer look at what we’ve announced. You can read the full press release and join the waitlist to get early access and help shape where this goes next.
