General
PromptBeginner5 minmarkdown
- Implementing proper authentication (JWT
OAuth2)
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General
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Backend Architect
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General
PromptBeginner5 minmarkdown
- Vision: YOLO
ResNet
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General
PromptBeginner5 minmarkdown
- Frameworks: PyTorch
TensorFlow
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General
PromptBeginner5 minmarkdown
- LLMs: OpenAI
Anthropic
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General
PromptBeginner5 minmarkdown
- ML Ops: MLflow
Weights & Biases
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General
PromptBeginner5 minmarkdown
Hardware: Edge TPU
Jetson Nano/Orin integration
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General
PromptBeginner5 minmarkdown
description: Use this agent when implementing AI/ML features
integrating language models
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General
PromptBeginner5 minmarkdown
C++: ROS2 C++ nodes
performance optimization
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General
PromptBeginner5 minmarkdown
target_skills: Edge AI optimization
ROS2
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General
PromptBeginner5 minmarkdown
Edge deployment (TensorRT
ONNX
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General
PromptBeginner5 minmarkdown
focus_areas: Edge AI for military robotics
context-aware vision systems
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General
PromptBeginner5 minmarkdown
target_companies: [Anduril
Palantir
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General
PromptBeginner5 minmarkdown
description: Capstone project integrating gaze estimation with ROS2 to control gimbal-mounted cameras on UGVs/quadcopters
featuring transformer-based operator intent prediction and AR threat overlays
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General
PromptBeginner5 minmarkdown
hardware: ESP32
RP2040
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General
PromptBeginner5 minmarkdown
12-Month AI and Computer Vision Roadmap for Defense Applications
{
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General
PromptBeginner5 minmarkdown
### Version 1.5 (January 11
2026)
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General
PromptBeginner5 minmarkdown
- Elevated Grok to top-tier in AI engine recommendations (real-time
tool use
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General
PromptBeginner5 minmarkdown
- Clear
grounded
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Data
PromptBeginner5 minmarkdown
- Suggested follow-up actions (prototype scope
data prep
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General
PromptBeginner5 minmarkdown
- Instead
suggest non-AI or hybrid alternatives (e.g.
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General
PromptBeginner5 minmarkdown
- Key risks or dependencies to monitor (e.g.
bias checks)
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General
PromptBeginner5 minmarkdown
- Keep it minimal and adaptable
including placeholders for iteration or error handling
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General
PromptBeginner5 minmarkdown
- Recommendations for iteration (A/B testing
feedback loops)
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