Snyk Named a Leader in The Forrester Wave™: Agentic Development Security Tools, Q4 2026

* Snyk was named a Leader in The Forrester Wave: Agentic Development Security Tools for Q4 2026.
* Snyk received the highest score in the Strategy category across Vision, Roadmap, and Partner Ecosystem.
* Current offerings include AI dynamic testing, AI coding guardrails, autonomous proprietary code remediation, and developer experience.
* AI coding agents are changing who performs development work.
* Six-six percent of developers using AI work with coding agents.
* Seventy-three percent of those using AI assistants or agents use them daily.
* The developer's role is shifting from writing all code to orchestrating agents.
* Agents bring their own supply chains, install packages, connect to MCP servers, and invoke tools.
* New critical and high-severity issues detected grew 10x in the past year, and roughly eight new issues are introduced for every one remediated.
* Snyk's platform includes Evo by Snyk, which comprises agent-native security solutions across three loops: code artifact, AI workforce, and AI applications teams build.
* Evo Agentic AppSec secures the code artifact via AI security agents that find, fix, and block vulnerabilities.
* Evo Agentic Development Security (ADS) protects the AI workforce by governing agent actions and inputs via Snyk Studio.
* Evo AI-SPM governs risks in models, agents, skills, and servers to generate a live AI-BOM and enforceable controls.
* Evo Continuous Offensive Security (COS) validates loops using Agent Red Teaming.

The narrative establishes a critical tension between the exponential speed of agentic development and the lagging pace of traditional security governance. The core pattern is the acceleration of risk creation outpacing the ability to govern it, which Snyk positions as the necessary convergence point for securing this new reality. The implication is that security must transition from inspecting static artifacts (code) to governing dynamic, autonomous workflows (agents). The data on agent usage and attack speeds—where eCrime breakout times are measured in seconds—suggest that traditional response cycles are fundamentally obsolete when applied to AI-driven systems. This forces a paradigm shift where security visibility must encompass the entire agent lifecycle: the code output, the components pulled in, the workforce skills utilized, and the resulting applications. The division into agent-native solutions (Evo) suggests a pattern of fracturing complex problems into manageable, interconnected layers of control (artifact, workforce, application). The challenge for organizations is not just finding tools, but integrating these layered controls to achieve unified visibility across execution, governance, and validation. The necessity of 'Proof' in the evaluation points toward the underlying problem: trust must be verified deterministically when autonomy is introduced.
BRIDGE QUESTIONS:
How do existing organizational structures for security and development change when work is orchestrated by autonomous agents rather than executed by human command? What are the specific operational costs associated with trusting agent-generated remediation versus continuous verification? How can organizations move from simply integrating tools to establishing a cohesive, unified feedback loop across code, agent behavior, and application deployment?