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Cognify

Cognify

Cognify

| (0) | Free
The unified simulation and evaluation layer for the AI era — inside your editor.
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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Simulate how real users experience what you build, as you build it, inside your editor.


What is Cognify?

Cognify is the unified simulation and evaluation layer for the AI era: a design intelligence platform that predicts how real populations will interact with your product before a single real user sees it.

Think of it as a flight simulator for your product. Instead of shipping a design and waiting weeks for analytics to tell you what went wrong, Cognify runs large populations of synthetic users through your interface in minutes, surfacing where they hesitate, where they drop off, and exactly what to fix.

Everyone else mimics the answer. Cognify simulates the path.

Where competitors prompt a model for a plausible opinion, Cognify models the actual human process that produces an outcome: the route, the hesitation, the backtracking, and the point where someone gives up.


Cognify in Your Editor

The VS Code extension brings Cognify's simulation layer directly into your development loop.

Rather than a separate tool you visit after the fact, the extension embeds Cognify as a continuous feedback layer inside your editor. As you build, write UI code, iterate on components, and ship new flows, Cognify runs in the background and surfaces behavioral signals in real time:

  • Where synthetic users get stuck on what you just built
  • Which interaction patterns trigger confusion or abandonment
  • Predicted task success, drop-off rate, and time-to-completion, before you ship

The same engine that powers Cognify's web platform now lives inside VS Code, Cursor, and JetBrains, closing the loop between writing code and understanding how people will experience it.


What You Get

Behavioral Simulation

Cognify traverses your interface with large populations of synthetic users: agents grounded in real cognition, behavior, vision, and language. Each run produces:

  • Predicted metrics: task success rate, drop-off rate, clicks to task, time to task
  • UX issues ranked by severity: High / Medium / Low, with specific file and component references
  • Concrete recommendations: not just "this is broken" but exactly what to change and why
  • Synthetic user journey maps: step-by-step paths showing where users got stuck
  • A/B variant predictions: upload two versions, get a prediction of which will win and why

Multimodel Humans

Simulations draw from a diverse synthetic population across five dimensions:

Dimension What it captures
Cognition Attention, memory, reading speed, confusion
Vision Visual salience, hierarchy, what gets noticed
Behavior Personality, patience, risk tolerance, biases
Physicality Accessibility, device type, motor constraints
Language Comprehension, literacy, tone sensitivity

Persona Types

Run simulations against specific user archetypes including Visual Scanners, Goal-Oriented Users, Methodical Users, and Exploratory Users, or mix a custom population to match your real audience.


How to Use

In the Editor

  1. Install the Cognify extension from the VS Code Marketplace.
  2. Open the Command Palette:
    • Windows / Linux: Ctrl + Shift + P
    • macOS: Cmd + Shift + P
  3. Run Cognify: Getting Started to activate the extension.

On the Web

You can also access the full Cognify platform directly at app.getcognify.ai to run simulations, review results, and manage your projects from the browser.


Roadmap

  • Real-time simulation feedback as you edit UI components
  • Inline annotations showing predicted friction points directly in code
  • Trajectory diagnostics: humanistic paths through your interface, diagnosable at the component level
  • Non-language evals: vision, attention, and behavioral signals beyond text
  • A/B simulation from within the editor, comparing two implementations before merging

Links

  • Website: getcognify.ai
  • Repository: github.com/mh-mubashir/cognify-extension

License

MIT

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