Agentic Coding: Rules, skills, subagents, and reflection—how we steer models so multi-step work stays coherent.

Agentic coding here means treating the LLM as part of a system : you supply constraints (rules), reusable procedures (skills), and split responsibilities (subagents), then merge and review (reflection) instead of hoping one giant prompt does it all. This repository is a small, concrete rehearsal of that pattern. The runnable piece is a User Analytics dashboard—enough UI and mock data to force real decisions about structure and state. The artifact matters less than the orchestration layer you see below: the same ideas written as code-shaped docs you can skim like a technical post, not a pile of file links. The thesis (one glance) ┌─────────────────────────────────────────────────────────────┐ │ Runnable app ≈ ~25% of what you optimize for │ │ Agentic layer (rules, skills, subagents, reflection) ≈ rest │ │ │ │ Goal: repeatable, inspectable workflows—not one-off prompts │ └─────────────────────────────────────────────────────────────┘ Rules: project manifest Rules are non-negotiables: wha