Your Candidates All Use AI Now. Your Take-Homes Can't Tell You Who's Actually Good.

DynaLab gives candidates a real codebase, a terminal, and an AI assistant. We capture every prompt, verification step, and decision. You get a 7-dimension scorecard. Automated scoring.

Or try an assessment yourself — no sign-up required →

See What Your Reviewers Won't Have To

DynaLab captures every prompt, verification step, and recovery pattern — then scores it automatically.

DynaLab Assessment
Step 1

Candidate codes with AI

Real codebase, terminal, AI assistant

Step 2

We capture everything

50+ behavioral signals per session

Step 3

You get a scorecard

7-dimension automated scoring

Try an Assessment Yourself

How it works

From role pack to scorecard in four simple steps.

1

Create a Role Pack

Choose from real engineering tasks — debugging, refactoring, code review, incident response. Set time limits and customize for your role.

2

Invite Candidates

Send assessment links via email. Candidates get a browser-based IDE with a full codebase and an AI assistant — no installs required.

3

We Capture Everything

Every prompt, edit, verification loop, and recovery pattern is captured. We detect behavioral patterns and score what research shows actually predicts production quality.

4

Review Scorecards

Get a 7-dimension calibrated scorecard across 3 tiers with evidence for every score. Compare candidates side-by-side on consistent criteria.

Evidence-Based Scoring. Not Gut Feelings.

Two developers can write the same fix through completely different processes. One explores the codebase, provides precise context to AI, and verifies every suggestion. The other pastes the error message and accepts whatever comes back. Research shows behavioral patterns predict code reliability better than output metrics (Nam & Kim, IEEE TSE). We capture every prompt, verification step, and recovery pattern.

Calibrated Trust90

Caught 3 incorrect AI suggestions

Context Engineering82

Referenced 4 files in prompts

Verification Discipline78

Ran tests after every change

+150 XPB+Overall Grade3-day streak

Sample Scorecard

Debug Database Connection Pool

82/100
Calibrated Trust90Context Engineering82Problem Decomposition85Debugging & Recovery78Architectural Judgment88Code Review75Workflow Efficiency83

Each dimension includes timestamped evidence from your actual session — edits, prompts, test runs, and decisions.

Built on Peer-Reviewed Research

Every dimension in our scoring framework is grounded in published research on developer effectiveness.

Live coding interviews measure anxiety, not ability

All women failed public whiteboard interviews. All passed private ones.

Behroozi et al., ESEC/FSE 2020

DynaLab assessments are private, async, and in a real IDE.

AI usage without verification produces worse code

AI-generated code has a 41% higher churn rate than human-written code.

GitClear, 2024 (153M lines analyzed)

We score verification discipline, not just task completion.

How developers use AI matters more than whether they use it

AI-generated code has 41% higher churn when developers accept suggestions without verification.

GitClear, 2024 (153M lines analyzed)

DynaLab measures 7 behavioral dimensions of AI collaboration — verification, context, and critical evaluation.

Structured assessments predict job performance 2x better

Structured interviews have 2x the predictive validity of unstructured ones.

Sackett et al., 2022 (Meta-analysis, J. Applied Psychology)

Every DynaLab scorecard uses the same calibrated rubric.

The Math Isn't Close

Teams using automated scorecards spend a fraction of the time reviewing candidates — and get more consistent, evidence-backed signal.

~$3

per assessment on Growth plan

vs hours of senior engineer review time

2-4 hrs

assessment time (replaces take-homes)

vs 4-8 hour traditional take-homes

7

calibrated dimensions across 3 tiers

vs pass/fail on other platforms

How DynaLab Compares

Traditional assessments miss how engineers actually work with AI. DynaLab captures the full picture — process, not just output.

Time investment

2-4 hours async, 5 min scorecard review

Take-home: 4-8 hours candidate, 1-2 hours reviewer

Whiteboard: 45-60 min live

AI assistance

Built-in, captured, and scored

Take-home: Uncontrolled (can use anything)

Whiteboard: Usually banned

What's measured

Full process — verification, context, recovery

Take-home: Final output only

Whiteboard: Algorithm correctness

Scoring

7 calibrated dimensions with evidence

Take-home: Subjective reviewer opinion

Whiteboard: Pass/fail

Predictive validity

2x higher (structured, calibrated scoring)

Take-home: Unknown (no standardization)

Whiteboard: Low (measures anxiety, not ability)

Candidate experience

Real engineering work with AI tools

Take-home: Frustrating, unpaid labor

Whiteboard: Stressful, unrealistic

Reviewer effort

Minimal — automated scorecard, quick review

Take-home: 1-2 hours per submission

Whiteboard: Real-time attendance required

Bias mitigation

Async, private, standardized rubric

Take-home: Reviewer bias, no rubric

Whiteboard: Performance anxiety, interviewer bias

Standardization

Full — same rubric, comparable scores

Take-home: None

Whiteboard: Limited

Cost per assessment

~$3 per assessment

Take-home: 1-2 hours senior engineer time per submission

Whiteboard: $150+ (platform + interviewer time)

Beta Status

23

Assessment Tasks

Debugging, reviews, triage, frontend, DevOps

7

Scoring Dimensions

Calibrated per-task behavioral analysis

50+

Behavioral Signals

Captured from every session automatically

DynaLab is in beta. These are platform capabilities, not customer claims.

Run a Pilot. See the Evidence.

We'll set up your first role pack and run 3 candidates through — free. See real scorecards on your actual hiring pipeline before committing.

5 free assessments included. No credit card required.