AI in Practice · Featured Project
Tough Guy & College Boy
A short-form AI character series exploring comedy, human judgment, production craft, and transferable instructional-design practice.
PROJECT TYPE
AI-assisted micro-video series
MY ROLE
Concept · writing · direction · editing
DESIGN FOCUS
Attention · contrast · pacing · judgment
STATUS
Three videos · still evolving
Instructional-design purpose
Comedy is the artifact. The design decisions are the evidence.
Tough Guy & College Boy began as a creative AI-media experiment, but the series demonstrates transferable learning-design skills: audience awareness, message design, scripting, pacing, media selection, iteration, feedback, emotional tone, and purposeful use of AI rather than novelty for novelty’s sake.
The recurring pattern is simple: surface a misconception or overconfident assumption, create a moment of tension or surprise, then get out of the learner’s way.
One concrete learning use
A 12–15 second misconception reset
Imagine a cybersecurity module. Tough Guy dismisses multifactor authentication because “I already got a strong password.” College Boy gives one short response that exposes the flaw. The learner then moves immediately into the real explanation or practice activity.
Instructional function: surface the misconception, create cognitive tension, reset attention, then transition to learning.
Watch the series
Three shorts. One evolving production language.
The videos stay central. The notes beside them explain what changed from one iteration to the next.
Tough Guy #1 — Establishing the Formula
The first short establishes the visual and comic contrast: a cinematic, AI-generated Tough Guy versus the deliberately ordinary “College Boy” in a real workspace.
Production: generated character image, ElevenLabs synthetic voice, HeyGen animation, live-action reaction footage, Camtasia editing, and the recurring monitor gag.
Key discovery: the joke works because the AI spectacle is ultimately undercut by a human who created, directed, edited, and judged the whole thing.
Tough Guy #2 — Expanding the Production
The second short develops the relationship between the characters and makes AI itself part of the dialogue: face generation, synthetic voice, avatar performance, training videos, and the human choices behind them.
Production evolution: more deliberate voice direction, ElevenLabs/11Creative avatar work, fake video-call material, multi-monitor staging, and a larger reveal built around the rocking-horse gag.
Key discovery: increasingly sophisticated AI tools still need strong scripting, timing, direction, and editorial restraint.
TOUGH GUY #3
Shorter Can Be Stronger
VIDEO MODULE PLACEHOLDER
Tough Guy #3 — Shorter Can Be Stronger
The third short strips the idea down. Tough Guy threatens, “I’m gonna get you,” while College Boy calmly researches what the phrase means and responds with genuine curiosity rather than fear.
Production evolution: a much faster build, tighter timing, and confidence that a complete comic beat does not need 20 or 30 seconds simply because video allows it.
Key discovery: brevity can strengthen the learning or communication effect when the beat is complete.
Sound became part of the writing
Rhythm can carry the emotional turn.
The jaw-harp passage in the series is not really melodic. It works through rhythm: odd and comic at first, then increasingly unsettling as tempo and volume rise. The same sonic material changes emotional meaning without needing additional dialogue.
That discovery opens a larger production path: keyboard, electronic drums, rhythm, silence, stings, and recurring character cues can become part of the design rather than decoration added at the end.
Why this matters for learning design
Timing is instructional. A pause can make a learner notice. A rhythmic escalation can signal that an assumption is becoming absurd. A short sonic cue can create continuity across a series. These are small production choices, but they influence attention and interpretation.
How the production evolved
AI generated material. I kept making decisions.
The toolchain changed from episode to episode, but the design loop stayed recognizable.
1
Purpose
Decide what the joke, contrast, or misconception is actually doing.
2
Prototype
Generate character, voice, visuals, or dialogue variants quickly.
3
Direct
Adjust delivery, pacing, reaction, framing, and the relationship between the characters.
4
Edit
Cut what is unnecessary. Let timing, silence, sound, and reveals do work.
5
Evaluate
Ask whether the finished beat communicates—not merely whether the AI output is impressive.
6
Iterate
Carry useful discoveries into the next short instead of forcing every technique into one video.
Selected tools
Tools changed. Judgment stayed central.
AI / synthetic media: ElevenLabs, 11Creative, HeyGen, generative image/video tools.
Authoring / production: Articulate Storyline, Camtasia, live-action camera work, monitor playback.
Sound: jaw harp treatment, Yamaha keyboard, and an expanding interest in original rhythmic cues.
Human-in-the-loop principle
The interesting part is not what AI can generate.
The portfolio evidence lies in what gets selected, rejected, rewritten, redirected, shortened, recombined, performed, edited, and finally judged worth showing.
What I’m learning
A reusable microlearning pattern is emerging.
Tough Guy & College Boy can be useful wherever a short contrast is more effective than another explanatory paragraph: onboarding, cybersecurity, compliance, customer service, leadership, inclusion, or technology adoption.
The characters do not need to carry the lesson. Their job may simply be to surface the misconception, earn attention, create a memorable contrast, and hand the learner back to the real learning activity.
Still evolving
This is a project, not a finished formula.
Future episodes can test new subjects, shorter structures, original sound, AI-assisted performance, and different ways of connecting the comic beat to a genuine instructional need.
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