Agentic swarms will change how everyone uses AI – but how can organizations deploy them securely?

Until the last year or so, building software has been both time and labor intensive. Maintaining it can be even harder. To tackle this, businesses have been deploying autonomous AI at scale. But now a new model is emerging that will completely transform the time and cost of producing software: agentic swarms.

Agentic swarms are coordinated networks of AI agents collaborating in parallel to code, test and optimize at unprecedented speed. Their collective power can produce results far superior to those of an individual agent – the production velocity is extraordinary and will remodel how software developers work.

They can now execute the full software development lifecycle, from research to deployment. As VentureBeat described it, for enterprises, “the era of ‘vibe coding’” has quickly transitioned into “a more disciplined concept: agentic swarm coding”.

However, despite major production gains, there’s also a growing risk of invisible agents operating beyond sufficient control.

Without governance, autonomous agents can at best drift from objectives and at worst introduce vulnerabilities or execute unauthorized actions that leave them susceptible to hacking.

This creates a new security blind spot inside the enterprise.

So, for public sector organizations looking to harness agentic swarms, how can they establish a model that enables them to achieve both incredible production velocity and robust governance and control?

The risk of unsupervised AI agents – and how ‘agentic domes' ensure governance

Amazon Web Services has suffered from at least two outages due to AI tools. In particular, an outage in December was reportedly “caused by an AI agent, Kiro, autonomously choosing to ‘delete and then recreate’ a part of its environment”. But the reason for these actions will be because the necessary guardrails aren’t in place.

In this instance, Security Researcher James O’Reilly said that the cause of the error may have emerged from the AI agent not being able to “understand the broader ramifications of (...) restarting a system or deleting a database”. If swarms operate without structured scaffolding, they produce inconsistencies.

A lack of domain grounding, for example, can lead to plausible-sounding but potentially legally wrong information. In the public sector, this can result in embarrassing public failures and legal liabilities. The problem is the governance layer that makes the agentic swarm capability safe hasn’t existed – until now.

What organizations need is a governed production environment that allows swarms of AI agents to operate safely at scale. In practice, this functions like an agentic foundry - a controlled environment where swarms can design, build and update applications while remaining within strict operational guardrails.

Within that environment sits a protective governance layer, sometimes described as an agentic dome. The dome coordinates the swarms while embedding organizational rules, compliance requirements and institutional knowledge into every output the platform produces.

This is a marked difference from a normal business software product, which represents a single static thing and has its own governance baked in – developers are constantly performing manual updates and validations. Crucially, an agentic dome is a production system.

That means the apps it builds inherit their governance from the platform, and they are continuously managed. Consequently, as a system, it can essentially create an infinite stream of outputs.

The new agentic model of development

Through the use of agentic swarms and domes, work that once cost millions and required a team of twelve over six months can now be executed in days by a swarm, and at a fraction of the price. The economics of the software industry are therefore going to go through seismic change.

The real magic isn’t only the speed of AI. Any team can make AI go fast if it so wishes. The magic is getting enterprise-grade, totally de-risked results because of this deep process of governance and control. And this governed lifecycle breaks down into three core phases.

First, teams need to specify exactly what needs to be built in a machine-readable contract. Second, they can then build it using AI swarms under incredibly strict governance. And third, they can subsequently manage the output, which creates a whole new kind of institutional knowledge.

Phase one: the machine-readable contract

The first step is to de-risk everything up front by getting rid of any ambiguity. This is how teams can eliminate the risk of AI hallucination, because everything is grounded and verified with human-approved knowledge.

And the output here isn't code – it's a machine-readable brief. This creates a map of a company’s services and how they connect.

Phase two: building

Now, as mentioned, the agentic dome doesn't actually do the building itself, it governs the AI swarms that do, and that is a critical architectural decision. It means an organization can always stay swarm agnostic and, instead, simply plug in the best swarm for the job, whether that’s writing production-grade code or structuring and distributing content.

The dome wraps a layer of real-time compliance checks, simulations and validation gates around whatever the swarm is doing, and nothing gets out the door until it's certified with a complete auditable trail.

Phase three: management

There’s a new category of software management emerging that is light years beyond a traditional CMS: a triad, three-part system. The first part manages content, but as structured, governed knowledge objects.

The second part manages capabilities, whether that’s complex workflows or automated AI processes. And the third part manages control with continuous, automated compliance and governance.

Together, this forms an institutional knowledge infrastructure that keeps software up-to-date and correct autonomously. This knowledge graph grows and gets smarter with every app that is built – and that’s a gamechanger.

Unleashing the next phase of AI-driven development

While agentic AI coding tools are being used to drive efficiency gains, a lack of effective governance and compliance infrastructure has contributed to outages and prevented companies from truly unlocking new levels of production velocity and scale.

But now, the arrival of agentic swarms and agentic domes is significantly overcoming these obstacles. Agentic swarms promise incredible levels of speed and development.

But the agentic dome is where the real value lies, producing enterprise-grade results that are totally de-risked due to a robust three-step process of governance and control.

If organizations deploy agentic swarms in this way, the economics of building and managing software are set to be transformed.

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