Learning Mode plugin makes Claude refuse to write code, guides learner instead

Learning Mode addresses a fundamental tension in AI-assisted learning: LLMs (AI systems that understand and generate text) are so capable at writing code that learners can obtain working solutions without understanding them. El Sayed's skill flips the default by making the assistant refuse to write code in learning contexts and instead guide the learner through a diagnostic cycle. The approach is grounded in established learning science—the skill explicitly combines diagnostic checkpoints, guided inquiry, graduated hints (a four-rung ladder climbed when the learner is stuck), self-explanation, and transfer checks (asking the learner to handle a changed example or counterexample). The boundary between assistance and ownership is precise: the learner owns the target skill, and the assistant removes incidental friction. This prevents the assistant from doing the work while maintaining pedagogical scaffolding.

The skill's architecture adapts to intent. It first asks whether the learner wants a quick answer, guided learning, or direct delivery, then activates only for explicit active-learning requests ("Teach me," "Guide me," "I want to practice"). Routine questions and delivery requests bypass Learning Mode entirely. For visual topics—data structures, state machines, architectural patterns—Learning Mode prefers diagrams, tables, and flows, asking the learner to predict, sketch, or trace rather than passively consume. Verification is built in: the skill checks version-specific APIs, current service limits, security requirements, and surprising claims against authoritative sources, marking them as verified, inferred, or unconfirmed. Journaling is opt-in and preserves progress across sessions if enabled.