Built an agent skill that makes Replit Agent help you learn, not just produce code

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Hello dear community.

Despite being new, as a first post introduction, I declare having spent quite a real time researching what happens to coding skills when AI does most of the work.

The short version of what I realized:

it depends entirely on how you interact with the AI, not whether you use it.

There’s a growing body of evidence (34 peer-reviewed sources at this point) showing that unrestricted AI coding assistance can actually harm skill retention — one RCT found an 11 percentage point drop on a 45-day delayed test when learners used ChatGPT freely vs. studying traditionally (Barcaui, 2025). Another study across 6,000+ participants found that sycophantic AI feedback (“Great approach!”) makes people make worse decisions than no AI feedback at all (Cheng et al., 2026, Science).

But the same research shows a specific interaction pattern that preserves learning: predict-compare-update. Before the AI generates code, you predict what the approach should be.

Then you compare your prediction against the AI’s solution. Then you explicitly update your mental model based on the difference (Shen & Tamkin, 2026).

I turned this methodology into a Replit agent skill called predict-calibration. When installed, it modifies how the agent works with you:

  • Before generating solutions to meaningful problems, it asks what you’d do first

  • It gives honest feedback instead of sycophantic praise (following the ELEPHANT anti-sycophancy framework)

  • It classifies requests by cognitive load type — boilerplate gets generated freely, but algorithm design and debugging get scaffolded so you actually learn

  • It detects when you’re stuck in habitual patterns and gently surfaces alternatives

It doesn’t slow you down on mechanical work. It kicks in where the learning actually happens.

To install:

git clone https://github.com/nmwv0/az8tlab.git .agents/skills/predict-calibration

Or download from github.com/nmwv0/az8tlab and place the contents into .agents/skills/predict-calibration/ in your Repl.

The skill is self-contained — no backend, no API keys, no dependencies. It just changes agent behavior.

Based on research from az8T Lab, the first ever Replit project I’ve been working on since the beginning of February 2026. Built to last.

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Thanks for the welcoming reply. Happy it may help. Of course, each article of the entire reference corpus has been quite carefully cherry picked and crafted onto the skill file “Evidence Summary - Predict Calibration Methodology”, before having been distilled onto the Github repo’s Readme.

Rather worth checking. Its exactly the point, AI use, more particularly, is increasingly being taken for granted and may erode specific cognitive skill mastery overtime instead of preserving and enhancing the related abilities […] This indeed didn’t missed me neither, which became inspiring toward producing serious countermeasures. The methodology baking this skill may seem oversimplified to be true, yet its elegantly elaborated for realistic efficiency.

Your presence in this community is truly appreciated

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