0xensec Daily Roundup — March 16, 2026
As the practice of software engineering rapidly evolves with the mainstreaming of large language models (LLMs), a new paradigm—agentic engineering—is emerging at the intersection of AI capabilities, software production, and security risks. Agentic engineering, as defined by Simon Willison, involves developing software through coding agents that can iteratively write and execute code to achieve defined objectives. Unlike traditional LLM-assisted code generation, agentic systems run in loops, employing toolchains—including live code execution—to incrementally refine solutions. This shift is not simply a productivity boon; it represents a significant attack surface transformation. The interplay of goal-directed autonomous coding with reinforcement from real-world testing could accelerate vulnerability discovery, exploit development, and the pace of adversarial innovation [1].
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