Over five months, Akadi developed and refined advanced enemy AI systems for the Ewan-DuplessisK/PFE_FTJ_Proto repository, focusing on scalable multi-enemy encounters, robust combat mechanics, and maintainable code architecture. Leveraging Unreal Engine, C++, and Blueprints, Akadi implemented behavior trees, data-driven configuration, and inter-agent communication to support complex gameplay scenarios. The work included transitioning core systems from Blueprints to C++ for performance, integrating debugging tools, and enhancing localization. Akadi addressed gameplay stability through targeted bug fixes and refactors, delivering reliable, extensible systems that improved iteration speed, gameplay balance, and deployment readiness while collaborating closely with cross-functional teams.
June 2025 monthly summary for Ewan-DuplessisK/PFE_FTJ_Proto focusing on reliability, gameplay polish, localization, and tooling improvements. Delivered key features, fixed a production deployment bug, and enhanced debugging capabilities to improve development efficiency and release readiness.
June 2025 monthly summary for Ewan-DuplessisK/PFE_FTJ_Proto focusing on reliability, gameplay polish, localization, and tooling improvements. Delivered key features, fixed a production deployment bug, and enhanced debugging capabilities to improve development efficiency and release readiness.
In May 2025, the project delivered a set of targeted updates to enemy AI, combat systems, navigation, and debugging tooling, driving stronger gameplay balance and faster iteration. The work focused on delivering business value through reliable systems, observable performance improvements, and maintainable code while stabilizing core combat loops for long-term scalability.
In May 2025, the project delivered a set of targeted updates to enemy AI, combat systems, navigation, and debugging tooling, driving stronger gameplay balance and faster iteration. The work focused on delivering business value through reliable systems, observable performance improvements, and maintainable code while stabilizing core combat loops for long-term scalability.
April 2025 performance summary for Ewan-DuplessisK/PFE_FTJ_Proto focusing on AI-rich combat, stability, and engineering excellence. Delivered core enemy behavior enhancements (RVO-based aggro, dialogue-capable AI, advanced grab mechanics) and reliability improvements (no-crash guards, post-QTE lifebar). Progressed performance-oriented CPP transition (BP to CPP, multi-enemy coordination, target variable alignment) and expanded developer tooling for faster iteration (Enemy AI systems/dev tooling integration). Strengthened anti-gank logic and combat versatility (no-enemy attack scenarios, CQC options), while maintaining code quality through refactors and clean-code initiatives. Close collaboration with R&D and cross-functional teams accelerated iteration and reduced risk of regressions across enemy systems.
April 2025 performance summary for Ewan-DuplessisK/PFE_FTJ_Proto focusing on AI-rich combat, stability, and engineering excellence. Delivered core enemy behavior enhancements (RVO-based aggro, dialogue-capable AI, advanced grab mechanics) and reliability improvements (no-crash guards, post-QTE lifebar). Progressed performance-oriented CPP transition (BP to CPP, multi-enemy coordination, target variable alignment) and expanded developer tooling for faster iteration (Enemy AI systems/dev tooling integration). Strengthened anti-gank logic and combat versatility (no-enemy attack scenarios, CQC options), while maintaining code quality through refactors and clean-code initiatives. Close collaboration with R&D and cross-functional teams accelerated iteration and reduced risk of regressions across enemy systems.
March 2025 performance summary for Ewan-DuplessisK/PFE_FTJ_Proto. Focused on establishing a scalable AI foundation capable of multi-enemy scenarios and enhancing inter-agent communication. Delivered data-driven configuration, foundational AI assets, controllers, and behavior trees, enabling rapid iteration and future expansion. Implemented talking tasks between enemies to improve coordination and increase player challenge.
March 2025 performance summary for Ewan-DuplessisK/PFE_FTJ_Proto. Focused on establishing a scalable AI foundation capable of multi-enemy scenarios and enhancing inter-agent communication. Delivered data-driven configuration, foundational AI assets, controllers, and behavior trees, enabling rapid iteration and future expansion. Implemented talking tasks between enemies to improve coordination and increase player challenge.
December 2024 monthly summary for Loris-Moreau/UE_Traversal: Delivered foundational enemy AI and combat scaffolding to accelerate iteration and testing. Implemented a blueprint-based patrol system and created a dedicated test level to validate enemy behaviors. No major bugs fixed this month; focus was on establishing a robust, reusable AI framework and test assets for upcoming milestones, driving business value through faster QA cycles and lower integration risk.
December 2024 monthly summary for Loris-Moreau/UE_Traversal: Delivered foundational enemy AI and combat scaffolding to accelerate iteration and testing. Implemented a blueprint-based patrol system and created a dedicated test level to validate enemy behaviors. No major bugs fixed this month; focus was on establishing a robust, reusable AI framework and test assets for upcoming milestones, driving business value through faster QA cycles and lower integration risk.
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