Software Assurance in the Agentic Era

What is slowing down software development now?

For decades, the slow part of software was building it. That constraint is gone. AI agents now write code, assemble pipelines, and operate systems. And the volume of software entering production is climbing faster than any security team can review.

But nothing about how we trust software has gotten faster. Assurance still runs on checklists, spreadsheets, screenshots, and annual assessments. A system that changes hourly is being vouched for by a process that runs yearly.

That mismatch is the defining constraint of the AI era: the bottleneck is no longer building software. It's assuring it. Machine-speed change is the chaos. Machine-speed assurance is the order.

What steps does machine-speed assurance require for cybersecurity compliance?

You can't fix a speed mismatch by hiring more reviewers. Assurance itself must become a machine-speed system, and that takes four layers working together:

1. A machine-readable standard for evidence. Every scanner, every tool, and every framework speaks its own dialect. Until security results share one format, every assurance pipeline starts with a translation project. This is why our founders created the Heimdall Data Format, now OHDF, an OASIS standard, so that security evidence from any tool can be normalized, compared, and consumed by machines.
2. Open tooling that the world chooses. A standard nobody can adopt is a paper exercise. The open-source HDF libraries, from converters and parsers to validators, turn output from dozens of commercial and open-source scanners into standard evidence.
3. A platform that runs the whole assurance lifecycle. Assurance is one discipline with four phases: define what secure means, verify systems against it, connect the evidence to the requirements, and present the case a decision-maker can trust. For example, the Aesir Systems Automation Platform™ covers each phase — Aesir Systems Sindre™ authors the guidance, the Aesir Systems Automation Content™ library validates systems against it, Aesir Systems Bifrost™ normalizes and cross-references the evidence, and Aesir Systems Vara™ turns it into posture you can act on and defend.
4. AI that is grounded and is itself assured. At Aesir Systems, our Mimir LLM answers compliance questions by looking facts up in a curated knowledge graph and citing them, not by generating plausible text. An answer you cannot cite is disqualifying in this field, and that principle must be built into the architecture.

Software assurance must include assurance of your agents too

Here is the part almost nobody is talking about and where the agentic era gets interesting: the AI doing the work needs assurance too.

If an agent hardens your systems, authors your guidance, or triages your findings, then that agent is part of your security boundary. What data was it trained on? What can it access? How do you know its answers stayed accurate after the last update? "Trust the vendor" is not an answer an authorizing official can sign.

We hold ourselves to the same standard we build for: the AI in our platform is assured the way any system component should be — its knowledge traceable to authoritative sources, its answers cited, its accuracy measured against deterministic ground truth. Assuring AI subsystems is a discipline we expect every serious program to demand within a few years, and it's one we're building in the open, on the same standards and evidence spine as everything else.

Your software assurance must hit three targets

Put it together and software assurance in the agentic era is one lifecycle discipline applied to three targets:

• Applications — the classic case: harden, validate, assess, authorize.
• Pipelines and supply chains — the same lifecycle shifted left: SBOMs and attestations as evidence, gates as requirements, every commit re-verified.
• AI models and agents — the new frontier: training provenance as the supply chain, behavior policies as the baseline, drift monitoring as continuous compliance.

The organizations that thrive in the agentic era won't be the ones producing the most software. They'll be the ones who can trust their software and prove it at the same speed they produce it.

That's the problem we build for. See the platform, or talk to us about where your program's assurance bottleneck is today.