When my co-founders and I started Cycode, we set out to solve a clear problem: application security teams were drowning in noise, juggling disjointed tools, and struggling to partner effectively with developers to secure applications. The signals were fragmented. The context was missing. All while in parallel Gen AI was coming to fruition with ChatGPT. Too often, developers were asked to fix vulnerabilities that didn’t even matter and in this ERA of the 10X developer every pain point was going to get magnified.
We knew security had to be smarter, more integrated, and more aligned to how software is actually built to support Product Security missions. That belief drove us to unify the layers of application security—from code analysis and CI/CD pipelines to supply chain visibility and developer workflows—into a single platform with the intelligence to prioritize what matters and the context to act on it. What began as a mission to simplify Application Security has steadily evolved into something larger: the convergence of ASPM, AST, and software supply chain security into a cohesive foundation for modern, Product Security.
It has been an incredible journey partnering with the world’s most iconic companies. Every day, I am honored to work with brands I’ve long admired in our mission to secure the software the world depends on. Many of these organizations have more developers than some multi national companies have employees.
We’ve now entered a new era. AI is fundamentally transforming how we build products, write code, and run businesses. Exactly what we envisioned in 2019 when Cycode was founded. We’re moving from tools that support critical functions to autonomous systems and AI agents that execute those functions with minimal human input. This shift is redefining the risk landscape and requires a new approach to security that is just as fast, intelligent, and adaptive as the systems it protects.
I am thrilled to introduce Cycode’s AI Teammates. Powered by high-fidelity data, graph intelligence, and agentic AI, these teammates automate risk reduction at scale and augment every developer with the security skills to deliver secure applications and fix what matters faster.
Meet Your Security Crew: Cycode AI Teammates
Cycode’s AI Teammates are a new generation of Agentic AI that augments human-led application security with action-oriented agents for the most common and high-impact workflows. Where previous AI integrations focused on copilots and assistants, Cycode’s AI Teammates operate like members of your security crew: informed, autonomous, and capable of carrying out tasks across detection, prioritization, and remediation.
The first cohort of Cycode AI Teammates includes:
- Risk Intelligence Graph Agent – The agent taps directly into Cycode’s Risk Intelligence Graph (RIG) to provide hard-to-find answers across code repositories, build workflows, secrets, dependencies, cloud assets, and more.
- Change Impact Analysis (CIA) Agent – Monitors code changes across pull requests and detects material changes that significantly alter risk posture.
- Exploitability Agent (SAST & SCA) – Enables security teams and developers to distinguish between theoretical vulnerabilities and truly exploitable ones that are buried in scan results.
- Fix & Remediation Agent – Goes beyond “suggesting a fix” and instead analyzes the root cause, understands the surrounding context, and proposes code fixes that match your frameworks, coding patterns, and even variable naming conventions.
Model Context Protocol (MCP) – The resource and tools layer that equips the AI Teammates with the data and capabilities needed to perform their goal. It enables every teammate to reason with full organizational context, not just isolated files or scan results. Think of it as the “operating system” for your AI teammates.
How AI and Humans Collaborate in Practice
High-risk vulnerabilities often persist for days, weeks, and months. This is not due to a lack of tooling but because each step in the vulnerability lifecycle requires time, expertise, and manual effort. This time and effort create the delta between risk creation and risk reduction, widening the security gap.
Cycode’s AI teammates are designed to close the security gap. They function as teammates collaborating with developers, security engineers, and each other to automate and accelerate processes throughout the vulnerability lifecycle. Here is how it works in practice to shorten the lifecycle of risky vulnerabilities:
1. Discovery: From Complexity to Clarity
The adage that you can’t secure what you can’t see holds true. Security starts with signals and detection. Cycode’s CIA Agent tracks code changes to identify material changes and ensure appropriate security controls are in place and executed. Security engineers can also query the Risk Intelligence Graph to search for newly disclosed CVEs in the codebase.
Better yet, AI teammates can collaborate to monitor vulnerability databases and listen to threat intelligence feeds, automatically query the RIG for high-risk CVEs, and trigger scans to determine reachability and exploitability. Contrast this with workflows where security engineers must manually monitor feeds (among other tasks), manually search for security findings to identify potential vulnerabilities, and then task developers to determine reachability and remediate the issues. The power of AI teaming comes into focus quickly.
2. Prioritization: Focus on Risk
Once a vulnerability is detected, the next question is what risk it presents to the organization. As previewed above, the RIG Agent contextualizes findings and maps vulnerabilities to your codebase, build pipelines, secrets, cloud assets, and business-critical applications. This illuminates exposure across the SDLC and pinpoints root causes.
The Exploitability Agent analyzes whether a violation in first-party code (SAST) or open-source dependencies (SCA) is reachable, executable, and exploitable in the context of your application and runtime environment. The agent understands your runtime environment and application architecture to separate exploitable risks from false positives or violations that are mitigated by design, tasks that traditionally fall on developers.
3. Remediation: Fix What Matters
With clear risk-based priorities and root-cause analysis, the Fix and Remediation Agent can take action. With context into the root cause and SDLC context, it generates context-aware code fixes that developers can review and approve. It can pair suggested fixes with security education, providing visibility into why the issue represents an exploitable risk and the reasoning behind remediation options to help developers select the best action and prevent insecure coding practices in the future.
4. Validation: Burn Down Security Debt & Build Resilience
Once a fix is deployed, Cycode can verify the effectiveness and learn from security and performance outcomes to iterate and improve. The MCP Protocol facilitates collaboration among Cycode AI Teammates and other systems. After a fix is deployed, AI agents can rescan the affected application, confirm resolution and functionality, and update dashboards and tickets. This virtuous cycle closes the loop on high-risk vulnerabilities with speed, precision, and scale not possible with manual approaches.
Advancing the Future of Software Security
Cycode was founded with a bold ambition to secure the software the world depends on. In a fragmented landscape of tools, signals, and manual processes, we saw an opportunity to bring clarity, context, and control. That vision led us to develop the industry’s most Complete ASPM platform, combining application security testing, software supply chain security, contextualized risk prioritization, and AI remediation across the software development lifecycle.
As the world races toward an AI-powered future, the nature of risk—and the requirements for security—are transforming in real time. Legacy models of siloed detection, severity-based prioritization, and manual remediation cannot scale to meet the demands of autonomous systems operating at machine speed. What’s needed now is not just better tools, but a new paradigm rooted in high-fidelity data, risk-based action, and AI-powered autonomy.
Cycode is delivering that future.
We have evolved from a unifier of Application Security signals to a pioneer of Autonomous Risk Reduction, blending high-fidelity data, risk intelligence, and agentic AI into a future-ready security ecosystem that augments every developer and security engineer. This transformation is happening now, with every AI Teammate deployed, every risk remediation, and every developer empowered to fix what matters and deliver secure code faster.
We can’t wait for you to see what comes next and join us in building the future of autonomous security together.
Want to learn more? Get a demo to see the future of Application Security for yourself.
