In 1885, German psychologist Hermann Ebbinghaus memorized nonsense syllables and tracked how quickly he forgot them.
His discovery is now called the Ebbinghaus Forgetting Curve, and it's brutal:
- After 1 day: ~70% forgotten
- After 1 week: ~90% forgotten
- After 1 month: almost everything gone
This was 140 years ago. The finding has been replicated countless times since. And yet we still act surprised when we can't remember that tutorial we watched last month.
The Uncomfortable Math
Let's say you completed a Docker course last month. You were excited. You understood containers, images, volumes, networking. You felt competent.
Today? Without practice, you've retained maybe 10-20% of that knowledge. The rest is gone. Not "rusty"—gone. Your brain literally pruned those neural connections because you didn't use them.
This isn't a personal failing. It's biology.
Why Practice Beats Learning
Ebbinghaus also discovered something else: active recall dramatically slows forgetting.
When you passively watch a video, information enters short-term memory and mostly disappears. When you actively use that information—write code, solve problems, build projects—it moves to long-term memory.
The difference is massive:
| Activity | Retention after 1 month |
|---|---|
| Watched a video | ~10% |
| Took notes | ~20% |
| Did exercises | ~50% |
| Built a project | ~70%+ |
This is why tutorials feel productive but rarely stick. You're not learning—you're spectating.
The Learning Trap
Modern learning platforms accidentally exploit this gap.
You watch 10 hours of Python tutorials. The platform shows you a completion bar at 100%. You get a certificate. You feel accomplished.
But completion ≠ competence. You consumed content. You didn't build skills.
The platform doesn't care. Their metric is "courses completed," not "skills retained." They're optimized for your feeling of progress, not actual progress.
What Actually Works
Spaced repetition - Review material at increasing intervals (1 day, 3 days, 1 week, 2 weeks). Each review resets the forgetting curve.
Active recall - Don't re-read notes. Close them and try to remember. The struggle of retrieval strengthens memory.
Project-based learning - Build something real. Applied knowledge sticks. Tutorial knowledge evaporates.
Interleaving - Mix different skills in practice sessions. Harder in the moment, better for retention.
None of this is new. Cognitive scientists have known it for decades. We just keep ignoring it because passive learning feels easier.
Tracking Decay
I built SkillFade to make this forgetting visible.
Every skill you track has a freshness percentage that decays over time:
- Practice something → freshness resets to 100%
- Learn something (video, article) → small boost, but decay continues
- Do nothing → freshness drops ~2% per day
After a month of no practice, a skill shows ~55% freshness. After two months, ~30%. The red warning color makes the decay impossible to ignore.
It's not gamification. There's no streak to maintain, no badge to earn. Just honest data: here's what you're forgetting.
The Point
Your skills are decaying right now. The Python you learned six months ago. The SQL from that online course. The framework from your last job.
Most of it is already gone. Not because you're bad at learning—because that's how human memory works.
The question isn't whether you're forgetting. You are. The question is: which skills are worth maintaining?
Pick the ones that matter. Practice them regularly. Let the rest go.
At least now you're making that choice consciously.
What skills have you let decay? And which ones are you actively maintaining?
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