DataPack
Vibe UX Coding & Usability
Train AI coding assistants on real UX implementation patterns, interaction logic, debugging workflows, and front-end problem solving grounded in production behavior.
Sample coming soon
Solution
AI coding models can generate working code, but they still miss how that code is experienced by users — friction, flow, layout, accessibility, and design-system consistency.
Flikforge turns real interface behavior into structured, rights-cleared training data for assistants that need to build software people can actually use.
Browse Relevant DataPacks →The Core Problem
AI coding models generate syntactically correct code — but correct isn’t the same as usable. Without session-level behavioral signal, models have no training data for where layouts fail silently, where friction accumulates, or where design drift goes undetected. That gap is why AI-generated code can look right and still underperform in production.
Performance Gaps Addressed
UI positioned without usability signal — models can't distinguish layouts that work from those that silently fail users.
No model for where users abandon tasks — friction patterns are invisible without session-level behavioral signal.
Conventions copied without usability signal — models replicate patterns that look correct but consistently underperform.
Code diverging from design system undetected — no signal connecting design decisions to measurable usability outcomes.
Relevant DataPack
Code repositories don’t contain session behavior, friction patterns, or design-system outcomes. This DataPack delivers the structured usability signal AI coding and vibe coding models need — interaction logic, placement context, behavioral patterns, and production UX grounded in real sessions.
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DataPack
Train AI coding assistants on real UX implementation patterns, interaction logic, debugging workflows, and front-end problem solving grounded in production behavior.