Achievement Get: First Semester Completed

This week marked the end of CST 349, and most of the work centered on finishing our final research video project and reviewing other teams’ presentations. My team completed our video on why AI-generated images and videos sometimes seem “off.” This project brought together research, visual design, script writing, voiceover, and editing. Our goal was to make the presentation clear and engaging by keeping the slides visual and letting the script explain the deeper ideas. We communicated through Discord and shared files, and we divided the work by role. Quinton worked on the outline, Nabiha and I worked on the slides and script, Luke recorded the voiceover, and Todd edited the final video together. Overall, the collaboration went well because everyone contributed and followed through. One thing I would improve next time is setting smaller internal deadlines earlier so that the slides, recording, and editing do not all depend on one big deadline at the end.

My team’s final video project: https://www.youtube.com/watch?v=HUwc3YcmaFc Our short-form video link: https://www.youtube.com/watch?v=Us7Bg_5K9yE

Review 1: AI NPCs in Games Video link: https://www.youtube.com/watch?v=Yt_kjIU4yR0

This presentation did a strong job explaining how AI in games has changed over time. I liked that the team started with familiar examples like The Sims and Red Dead Redemption 2 before moving into newer LLM-powered NPCs like the ones in Suck Up. That made the topic easier to follow because it showed the progression from rule-based behavior to more context-aware responses and generated dialogue. The research seemed strong because the team explained key concepts like utility-based AI, behavior trees, state machines, system prompts, API calls, and context windows. The video was clear and appropriate for a technology audience, but it was still understandable for someone who may not already know a lot about game AI. One suggestion I would make is to tighten the pacing slightly or reduce some repeated explanation. The topic was interesting, and a slightly faster flow could make it even more engaging. Overall, the team showed clear organization and strong coverage of the topic.

Review 2: AI vs. Hackers: How Machines Defend and Attack Networks Video link: https://www.youtube.com/watch?v=lP6-qIvWk1c

This presentation did a good job showing both sides of AI in cybersecurity. I liked that it did not present AI as a perfect solution or as only a threat. Instead, the team explained how defenders use AI for anomaly detection, user and entity behavior analytics, phishing detection, and automated response, while attackers use AI for scams, deepfakes, malware, and social engineering. The presentation was clear because it moved logically from how AI detects threats to how attackers use similar technology. The research felt current and detailed, especially with examples like Darktrace, Microsoft Defender, Google Chronicle, Proofpoint, WannaCry, SolarWinds, WormGPT, and the AI-generated video call scam involving a major financial loss. The video was engaging because it framed cybersecurity as an arms race rather than a one-sided issue. One suggestion I would make is to slow down slightly during the most technical sections or include more visual summaries, because there were a lot of terms and examples. Overall, the presentation was informative, relevant, and appropriate for a technology-focused audience.

Review 3: Hacking Myths vs. Reality Video link: https://www.youtube.com/watch?v=tKb-5u7Heyc

This presentation was well organized and easy to follow because it used a myth-versus-reality structure. I thought that format worked really well for the topic because it directly challenged common stereotypes about hackers and explained why those misunderstandings matter. The team covered several important myths, including the idea that breaches are purely technical, hackers work alone, firewalls and antivirus software are enough, organizations notice breaches immediately, and AI mostly benefits defenders. The research quality seemed strong because the presentation referenced current cybersecurity issues such as credential abuse, ransomware-as-a-service, business email compromise, zero trust, breach detection delays, and AI-driven scams. The video was appropriate for the audience because it explained cybersecurity in a practical way without assuming too much prior knowledge. One suggestion I would make is to include a few more visuals or real-world examples throughout the video to make each myth feel more memorable. Overall, the presentation was clear, relevant, and showed strong teamwork through its organized structure.

Looking back on CST 349, I learned that professional development in computer science is not only about technical skills. This class helped me think more seriously about career planning, communication, teamwork, presentations, and how to explain technical topics to different audiences. The industry expert interview reminded me that software engineering requires continuous learning, curiosity, adaptability, and strong communication. The final video project also helped me practice turning research into something understandable and engaging, which is a skill I know I will need in future classes and in the workplace. As I move forward in the CS Online program, I want to keep improving my portfolio, building personal projects, and becoming more confident presenting technical ideas clearly.