How Bricklayer’s Agentic Platform Architecture is Tackling AI’s Indeterminism Problem for Cybersecurity
In a world overwhelmed by data and complexity, the rise of AI offers both unlimited promise and possible peril.
Most AI models, especially LLM-based systems, operate like black boxes. They produce outputs that may (or may not) be correct, but can’t explain themselves. Humans are left to interpret, double-check, or blindly trust the results.
This lack of determinism is not sustainable – especially in domains like cybersecurity where accuracy, accountability, and auditability are critical.
This has become one of the biggest barriers to operationalizing AI in cybersecurity. How was this conclusion reached? What data informed it? Can I trust the outcome? These questions echo across every boardroom and SOC.
To truly build AI-native security and intelligence, you need scalable, autonomous, and auditable decision-making across your entire security architecture. It needs to be adaptable based on the most recent data, and it must utilize every piece of information across an organization.
We knew we wanted to build Bricklayer to address these challenges from the ground up.
Introducing Bricklayer’s Agentic Platform Architecture
Bricklayer is an Agentic Cybersecurity Platform consisting of a coordinated team of intelligent, specialized AI agents, each operating transparently within clearly defined, unique boundaries.
Because Bricklayer was built specifically for cybersecurity teams, we knew that it could not be a centralized black box system where humans could not audit the work that was being automated.
The entire Bricklayer platform was built to be agentic. Plugins, reports, procedures, and decision interfaces are all built to act as autonomous yet cooperative components, each with their own role, scope, and knowledge. This creates a modular ecosystem where complex cybersecurity workflows can be broken into understandable, auditable pieces.
Everything in the Bricklayer platform – whether it’s an agent performing enrichment, a plugin accessing third-party tools, or a report being assembled for an executive – is treated as part of a collaborative system. These components don’t just execute tasks in isolation; they share context, learn from outcomes, and coordinate in real time.
Instead of asking one monolithic, black box model to “figure it all out,” Bricklayer empowers an agentic architecture where specialization, transparency, and teamwork drive results. The result is a security platform that doesn’t just do work—it explains it, scales it, and improves it over time.
Bricklayer’s patent-pending agentic platform enables AI agents to independently coordinate, collaborate, and execute tasks across complex workflows – without relying on a centralized brain.
Bricklayer Patent Pending Model
- Agent-to-Agent Collaboration: Enables agents to communicate, delegate, and manage tasks among themselves
- Dual-Role Architecture: Each agent is role-flexible, with the ability to act as both a contributor and a manager
- Context-Aware Execution: Agents retain and share knowledge, adapting to real-time needs
- Autonomous Procedure Execution: Complex tasks are broken into steps and completed across agents with full tracking
- Built for Enterprise Security: Designed specifically to meet the needs of modern SOC environments
Unlocking Scalability with Modular Components
Every objective is broken down into discrete tasks. A task is an atomic unit of work: a prompt, an agent, and one or more inputs. Subtasks can be spawned by agents acting as managers for the work involved within a single task.
In Bricklayer, every objective begins with a goal – not just a fixed script. AI agents dynamically break that goal into discrete, manageable tasks, assigning roles and collaborating based on context, expertise, and constraints.
This mirrors how high-performing human teams operate: smart people come together, assess what’s needed, and self-organize to get the job done – within the structure of shared tools, data, and objectives.
Unlocking Transparency with Cross-Platform Traceability
Every step is traceable. Within each task or subtask, Bricklayer highlights exactly what information was used and how it informed the agent’s decision.
With Agent Source Citations, Bricklayer Agents actually show precisely what parts of your documents informed their decisions – not just what they read, but what they actually used. Each reference is linked back to its original document with full context, allowing instant verification, faster reviews, and deeper trust.
When it comes to complex procedures, we know how fast the security landscape moves. To address this, Bricklayer AI agents generate a procedure outcome dynamically at runtime, based on their own reasoning and decision path. It’s contextual and adaptive, meaning that different procedures yield different outputs, and even within the same procedure, results adapt to the unique data.
With this type of flexibility, it’s essential to showcase exactly what happened and why. Traditional user interfaces and dashboards won’t work because they rely on predefined views before a decision is made. With Bricklayer’s Agent Debrief, an Agent will create a single page overview to tell your human team exactly what they need to know about a procedure – what happened, why decisions were made, success rates, and more.
Every Agent Debrief doubles as an executive- or analyst-ready report, created instantly by AI and aligned to how humans consume evidence: decision, justification, supporting data. Analysts no longer need to sift through hundreds of log lines, relationships, and fields, massively reducing their reporting hours and cognitive load.
Every decision is traceable, reviewable, and explainable – supporting internal audits, external compliance, and long-term trust in AI.
How to Implement Bricklayer’s Agentic Platform Architecture into Your Human Team
Using Bricklayer’s Procedure Engine to Plan with AI Agents
Bricklayer’s agent collaboration, modular ecosystem, and complete traceability all come together in Bricklayer’s Procedure Engine. In Bricklayer, a procedure is a collection of tasks that come together to form an automated workflow to accomplish a specific goal.
The Procedure Engine empowers your team to define their high-level cybersecurity goals – while leaving the complexity of planning to a team of intelligent AI agents.
When a cybersecurity analyst specifies what they want to accomplish – such as producing a threat report, mapping an attack surface, or triaging alerts – Bricklayer dynamically generates a procedure. This procedure is grounded in real-time knowledge of the customer’s environment: security tools, policies, org structure, institutional knowledge, and more.
Transparency and Predictability at Every Step
Crucially, these procedures are never executed blindly. They are reviewed and approved by humans, preserving operational oversight and ensuring alignment with organizational policies. By breaking down goals into specific tasks and subtasks, the platform constrains agent behavior within deterministic guardrails, eliminating the risks of open-ended, unpredictable AI execution. It’s planning with structure, transparency, and accountability.
By using the dynamic procedure planning to break the goal down into individual tasks, Bricklayer enables humans and AI agents to plan together, leveraging not only what the human knows about their own environment, but also what the AI agent team knows about each of their domains: business context, tools, datasets, policies, and more.
Automate Actions with Full Traceability
Once approved, Bricklayer executes the dynamic procedure as a sequence of tightly scoped tasks. Each task is an atomic unit of agent work, combining a prompt, a specialized agent, and zero or more data/tool inputs. Tasks may spawn subtasks, which are managed and delegated by agents acting in a dual role—as both contributors and managers.
Execution is fully traceable. For every task and subtask, Bricklayer highlights exactly which inputs were used and how they shaped the outcome. Rather than hiding logic in opaque black boxes, the platform “shows its work,” allowing customers to validate, audit, and learn from every agent decision. This execution model doesn’t just drive results—it builds trust and repeatability into the automation layer.
Bricklayer Agentic Platform Architecture in Real Life
Let’s walk through an example:
You decide that you want a report on your desk every day at 0900 that maps your company’s external attack surface.
Here’s how you might do it manually using Shodan:
- Search for all known public-facing assets
- Correlate to IP ranges
- Cross-reference with threat intel
- Create visuals and summary insights
Now here’s how Bricklayer’s agents do it:
1. Goal Declared: “Provide a daily attack surface summary at 0900 for my company.”
2. Procedure Generated: The platform dynamically generates a procedure based on your environment.
3. Tasks Created: Individual agents handle reconnaissance, enrichment, threat mapping, and reporting.
4. Audit and Delivery: The output is explainable, traceable, and repeatable—delivered to the right human.
The Future of AI in Cybersecurity: Agentic Platform Architecture
Bricklayer is not just another security automation tool. It’s a platform for orchestrating intelligent agents across dynamic, auditable, and collaborative workflows.
We believe the next wave of innovation in cybersecurity—and beyond—will come from breaking monolithic systems into intelligent, interacting components. That’s how we escape the black box.
And that’s why we built Bricklayer.
