Dustin Dannenhauer is an AI scientist and founder based in San Francisco with 13+ years building resilient, metacognitive AI and LLM-based agent systems. He has led DARPA SAIL-ON projects and contributed core architecture to MIDCA, translating hard novelty and explainability research into applied agents for dynamic environments. At companies like GoCharlie.ai, Parallax, DVMDash and in open-source work (including NPC pathfinding for the Tuxemon RPG), he blends deep research with pragmatic engineering to ship human-in-the-loop and autonomy-focused systems. His work emphasizes robustness and goal-driven autonomy—often tackling failure modes and online adaptation rather than just accuracy improvements. As a PhD-trained researcher who has mentored students and run advanced projects for government and startups, he bridges academic rigor with product-minded delivery. He now channels that experience into founding Delegance AI to commercialize resilient social and agentic AI.
13 years of coding experience
8 years of employment as a software developer
Bachelor of Science (BS), Computer Science, Bachelor of Science (BS), Computer Science at Indiana University Bloomington
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Lehigh University
Contributions:29 commits, 1 PR, 4 comments in 7 days
Contributions summary:Dustin focused on implementing pathfinding algorithms for the Tuxemon game, a monster-fighting RPG. Their primary contributions involved modifying the map component to support collision lines and developing a breadth-first search algorithm to determine movement paths for non-player characters (NPCs). They also adjusted the player's movement logic to incorporate the pathfinding results, enabling NPC movement along pre-calculated paths.
Contributions:2 pushes, 1 branch in 6 years 7 months
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