dynamic work simulations · built for AI-era roles

The nature of work has changed.The way we assess must too.

asaya is simulation-based assessment for AI-augmented engineers: a personalized sandbox that scores how people actually work with AI, under real constraints.

See how it works →Talk to us

AI-Fluency Index™Behavioural TelemetryAdvanced ProctoringDynamic

behavioural telemetrylive-proctoreddynamic scenario engineevidence you can auditAI-Fluency Index™real constraints

02 · the problem

Every signal is broken.

Layering AI over a broken process multiplies the chaos and the noise. Every proxy we trusted is now synthetic.

broken

Résumés

Written by a model, tuned for the keyword filter. Optimized to pass, not to predict.

unverifiable

Portfolios

AI-generated and borrowed. You can no longer tell whose work you are looking at.

gamed

Interviews

Candidates use AI to apply. Companies use AI to filter. Real talent gets lost in the middle.

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of companies report a bad hire this year due to flawed assessment.

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of interview performance doesn't correlate with actual job performance.

1 in 4

profiles will be fake by 2028.

3 in 4

managers have already faced AI-generated applications.

Every fake signal adds another interview a human must absorb.

03 · the assessment void

The job changed.
What we measure has not.

Every legacy assessment skips four of the five skills that make an AI-augmented engineer. The void compounds daily.

tools	Code correctness	AI orchestration	Judgement / ambiguity	Product mindset	Stakeholder communication
Coding screens RackerHank · Docility	✓	✗	✗	✗	✗
Take-homes AI-written · unverifiable	AI-done	✗	✗	✗	✗
Human interviews $200–450/hr · inconsistent	✗	✗	weak proxy	✗	✗
asaya simulation-based · validated	✓	✓	✓	✓	✓

+% YoYAI-augmented engineering

+% YoYForward-deployed engineering

+% /yrAI engineer, the #1 fastest-growing role

source: Dice · Lightcast · BLS · SHRM · 2026

04 · how it works

Your environment in.
A calibrated simulation out.

A five-minute setup generates a personalized, browser-accessible sandbox simulation, rooted in evidence-based assessment science.

stage 01

Quick intake

~5 minutes

A five-minute form on your stack, the role, and the capabilities that matter. Everything we need to build your simulation, nothing more.

stage 02 · asaya layer

Intelligence engine

The asaya engine personalizes and calibrates a simulation from your real environment: your tools, your problems, fixed in difficulty.

stage 03 · asaya layer

Personalized sandbox

A browser-accessible workspace with live personas, an AI assistant, and real-world constraints. Generated in seconds, not months.

stage 04 · asaya layer

Scientific evaluation

Behavioural telemetry captures every decision, prompt, and recovery as it happens. Every action scored; every score evidence-linked.

stage 05

Capability, measured

A full competency profile and an AI-Fluency Index™ come out the other side: ranked, comparable, and fully auditable.

Personalized for fidelity. Standardized for fairness.

05 · inside the simulation

One workspace. Every real-world tool.
Every action, scored and ranked.

Candidates work in a real, sandboxed dev environment, not a whiteboard. Everything the role touches on day one is one tab away.

Simulation sandboxtime59:07 / 90mtokens200,000 / 200,000compute60.00m / 60mmoney$25 memory2,048MB

docs

messages

teammate & client personas

data

database

terminal

assistant

AI

deliverable

desired outcome

Advanced proctoring

Live-proctored and identity-verified, end to end, so you know who actually did the work.

Dynamic scenario engine

Personalized to the role's environment with progressive difficulty. Never identical, impossible to leak.

grounded in assessment science: fairness · comparability · validity · reliability

06 · the signal

We measure how the answer was built.

~5,000 signals per session. Every pixel, every keystroke. Every score linked to the exact evidence moments that earned it.

01 · the basics

Core competency

Software engineering fundamentals
Problem decomposition & structuring
Code quality, accuracy & debugging

02 · the process · most important

How they work

AI orchestration & prompt design
Verification & judgment: knows when AI is wrong
Adaptability when the model fails
Stakeholder communication & product mindset

03 · the outcome

What gets delivered

Deliverable meets brief & constraints
Resource efficiency: time, tokens, cost
Stakeholder-ready output

AI-Fluency Index™a calibrated spectrum to measure AI orchestration

AI-Dependent

Leans on AI for answers; can't tell when it's wrong.

AI-Augmented

Directs AI well and verifies it; a reliable, productive contributor.

AI-Orchestrator

Multiplies output, catches model failures, and knows when not to use it.

07 · the impact

Evaluate 20 candidates for a role in 4 interviews instead of 40.

Keep the SME judgment that can't be replaced. asaya absorbs the broken middle, replacing manual screening with automated, work-evidence-based assessment.

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faster screening

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cost saving

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SME time saved

40 → 4

interviews per 20 candidates

Reducing the immeasurable cost of missed talent. Giving genuinely capable people a fair shot.

ready when you are

Measure what matters.

Run a pilot with one role for FREE. See real signal in a week, and never assess the old insufficient way.

Talk to us →