Announcing Agentic Development Security (ADS)
Summary
Snyk has announced Agentic Development Security (ADS), a new Evo solution designed to secure AI-driven software development. This addresses the shift where AI agents actively build software, selecting tools, executing actions, and generating production-ready code at machine speed. Traditional application security, focused on post-creation scanning, is insufficient for this continuous risk model. Snyk's scan data from nearly 10,000 developer environments shows 80% of developers use two or more AI coding environments, and 50.8% have live MCP server connections to production tools. Evo ADS embeds security directly into AI-driven workflows by securing the agent supply chain, governing agent behavior, and ensuring trusted generated code at inception. It continuously discovers and inventories components, evaluates them against policy, and operates within the agent execution loop to prevent high-risk actions. This approach ensures security checks are applied as code is generated, identifying vulnerabilities before they spread.
Key takeaway
For MLOps Engineers or AI Security Engineers adopting AI agents for development, you must shift security focus from post-creation scanning to real-time governance within agentic workflows. Implement solutions like Evo ADS to gain visibility into agent supply chains, enforce policies on agent behavior before actions execute, and validate AI-generated code at inception. This proactive approach prevents critical incidents, maintains development velocity, and ensures trusted AI adoption at scale.
Key insights
Agentic Development Security (ADS) shifts security from code to the system producing it, embedding controls directly into AI-driven workflows.
Principles
- Security must precede code commitment.
- Govern agent actions, not just outputs.
- Continuously assess agent supply chain.
Method
Evo ADS extends security into AI-driven development workflows by securing the agent supply chain, governing agent behavior, and ensuring trusted generated code at inception through real-time observation and policy enforcement.
In practice
- Inventory AI agent components dynamically.
- Block high-risk agent actions pre-execution.
- Apply security checks during code generation.
Topics
- Agentic Development Security
- AI Agents
- Software Supply Chain Security
- MLOps Security
- AI-Generated Code
- Snyk Evo
Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Security Engineer, MLOps Engineer, AI Engineer
Related on AIssential
Editorial summary, takeaway, and curation by AIssential. Original article published by Blog RSS Feed | Snyk.