Hire developers whoactually use AI well.
"AI-fluent" is the new "team player": everyone writes it, nobody can prove it. And LeetCode was never going to. So we built CrowdVibe. A sandboxed IDE with an AI assistant on the side, scenarios tuned to the role, and a full report plus session replay at the end. Real signal, not vibes.
Every candidate "uses AI." Almost none use it well.
The day-to-day of engineering changed. Hiring didn't. Most coding tests still ban AI or score against rubrics from 2018, so you end up hiring for puzzle-solving instead of the skill that drives output today: working effectively with an AI partner on real tasks under real constraints.
- Algorithm puzzles unrelated to the role
- AI tools banned (yet used in real work)
- Pass/fail grade with no signal beneath
- No visibility into how the candidate thought
- Real engineering tasks tuned to the role level
- AI assistant built in, measured, not banned
- 5 weighted dimensions with an AI-written summary
- Full session replay with integrity flags
From invite to hire decision in one afternoon
Four steps. No installs, no proctor calls, no synchronous interview block. Your team configures once, then reviews structured signal per candidate.
Configure & Invite
From your company dashboard, pick the role level (junior to staff), stack (TypeScript/Node, React, Python/FastAPI), and scenario mix. Generate an invitation link and send it, or attach it to a job listing.
Sandbox Provisions
Candidate clicks the link, lands in a pre-flight lobby, and a fresh isolated sandbox spins up automatically. No installs, no setup. Same environment for every candidate: same Claude model, same system prompt, same tooling.
Candidate Builds with AI
Three real-world scenarios in a Monaco IDE alongside an embedded AI assistant. Telemetry captures every keystroke, AI prompt, paste, test run, and focus event in real time, all replayable later.
Review & Decide
Get a six-tab report covering Performance, Behavior, Provenance, Grading, Integrity, and Methodology, plus a complete time-synced session replay. Share with the team, export to PDF, or compare candidates side by side.
Run scenarios in the stack your team actually ships in
Every language runs in the same isolated sandbox with the same AI assistant, telemetry, and scoring rubric. Pick the one that matches the role.
Need a language not listed? Ask us, most stacks can be enabled within a sprint.
Not just whether it ran. How they got there.
Five weighted dimensions surface the signal that matters in AI-era engineering. Every dimension is graded automatically and explained in plain English.
AI Leverage 25%
Does the candidate use AI as a force multiplier or a crutch? A secondary AI model analyses prompt specificity, problem decomposition, and whether they reach for AI on architecture and edge cases, not just rote code generation.
Critical Review 20%
Does the candidate catch AI mistakes, or paste them straight into prod? Each suggestion they accept, edit, or reject is logged. Thoughtful evaluation scores; blind acceptance does not.
Task Completion 25%
Does the code actually work? Automated test suites grade against acceptance criteria, edge cases, and error-handling paths, same rubric for every candidate.
Code Quality 20%
ESLint + Semgrep static analysis flags input validation, error handling, security anti-patterns, and structural smells. Surfaces candidates who ship sloppy AI output unchecked.
Speed & Efficiency 10%
Time-to-completion normalised by difficulty, plus a prompt-efficiency ratio measuring productive iteration vs. aimless looping. Rewards intentional work, not raw speed or prompt volume.
Screen on your stack, your work.
Stock scenarios are a starting point, not a ceiling. Generate AI-built coding scenarios from a job description, an existing repo, or a freeform brief, then refine them in a guided builder until they reflect the work your team actually ships.
Generate from a Job Description
Paste a JD or pick an existing job listing, CrowdVibe drafts a scenario tuned to its skills, stack, and seniority. Review the brief, starter files, and test suite before publishing.
Choose the Scenario Type
Code-write, debug, code review, system design, stakeholder comms, or git workflow. Mix scenario types in a single assessment to test the dimensions of the role that matter to you.
Calibrate the Difficulty
Junior, mid, senior, or staff, difficulty calibrates the brief depth, edge cases, and grading rubric automatically. Same scenario, four bars: pick what matches the role.
Bring Your Own Starter Files
Upload starter code and a test suite, or let CrowdVibe scaffold both for you. The candidate's sandbox boots with exactly your repo layout, no synthetic playgrounds.
Add Follow-Up Scenarios
Chain scenarios that react to the candidate's submitted code, a stakeholder-comms exercise that asks them to explain their changes, or a git-workflow follow-up that ships the diff. Real engineering rarely ends at "tests pass."
Test Drive Before You Send
Run any scenario yourself in the same sandbox the candidate sees. Validate the brief, check timing, and review the report it produces before exposing a single applicant to it.
Reusable Scenario Library
Every published scenario lives in a private library shared across your team. Tag, filter by difficulty or type, and reuse across job listings, so each role keeps building on consistent signal.
Identical Grading, Custom Content
Custom scenarios still grade on the same five weighted dimensions. Your scoring stays comparable across candidates and across roles, even when the brief is unique to your company.
A signal your team can actually defend
The moment a candidate submits, your team gets a structured report with an AI-written summary, sub-score breakdown, prompt analysis, integrity flags, and a complete time-synced session replay.
Candidate Report, Sarah K.
AI-augmented developer assessment, Web Development (Full-Stack, Senior)
Submitted: 7/13/2026, 6:40 PM · Duration: 42 min
Top 22% of Full-Stack developers
Strong AI collaboration with room for edge case mastery
Sarah's prompts are specific and well-structured, she consistently breaks complex problems into targeted AI queries. She caught 2 of 3 AI mistakes in the refactoring scenario. Main growth area: edge case coverage in Scenario 2 and a missed timing vulnerability in Scenario 1.
Prompt Strategy Analysis
How effectively the candidate communicated with the AI assistant
Targeted Problem Decomposition
StrengthBroke Scenario 1 into 4 focused AI queries instead of asking for a complete solution, leading to higher defect detection and more deliberate fixes.
Edge Case Prompting
ImproveIn Scenario 2, built the happy path but didn't prompt AI about error states, partial failures, or rate-limiting edge cases. A "what could go wrong?" prompt earlier would have caught these.
Score Tiers
Where this candidate falls in the CrowdVibe framework
Defensible signal. Fair to candidates.
Designed with engineering managers and recruiters who screen technical candidates every week. No gimmicks, no leaked answer keys.
Identical Conditions
Every candidate gets the same Claude model, same system prompt, same scenario set tuned to the role level. Scores compare cleanly across your funnel.
Integrity Built In
Focus tracking, idle classification, paste-source detection, and hallucination flags surface anomalies. You see how a candidate worked, not just what they submitted.
Full Session Replay
Scrub through a candidate's session like a video, code edits, AI conversations, test runs, and focus events all time-synced. Skip to interesting moments via auto-generated markers.
AI-Analysed Reports
A secondary AI model writes the executive summary, classifies the candidate's persona, and explains sub-scores in plain English, so non-technical stakeholders can follow along.
Frequently asked questions
Everything hiring teams need to know about CrowdVibe.
Hire on signal, not on vibes.
Send your first CrowdVibe assessment in under five minutes. Get a multi-dimension report and a full session replay back, ready for your next hiring loop.