Candidate A
- Reads the logs and documents before asking the AI
- Has the AI fix the cause, then runs the tests to prove it
- Rejects a change that breaks what already worked
- Explains in the Defense why this way
The hidden checks reward root-cause fixes
First missions open 30 Oct
Use AI. Own the outcome.
Measure engineers on the part AI can't do for them
Candidates fix a real problem in a real system, with AI at their side. The work is checked automatically, then an AI reviewer asks why they did it that way. You know who really understands the job before you spend time interviewing.
For companies hiring engineers, and for tech people who want to prove their skill on real work.
- Pick a missionOne of the three launch missions
- They work with AIOn a real problem, in a cloud workspace
- Read the resultPass or not, and a level for every piece
A sample result page
Submit, and this is what you get
Between 531 and 816 hidden checks, depending on the mission, grade the work automatically, with a level from C1 to C5 for every piece of it. Nobody has to read the code.
After submitting, an AI reviewer asks why they did it that way; every launch mission requires it. Someone who let the AI do it blindly usually can't answer.
Your own people take the same launch missions on their own accounts and share the result with you: pass or not and the level for every piece, so you see where the team is strong. Companies see a candidate's result only when the candidate shares it.
Screens from OperatorRank · sample data
Between 531 and 816 hidden checks, depending on the mission, grade the work automatically, with a level from C1 to C5 for every piece of it. Nobody has to read the code.
Screens from OperatorRank · sample data
The problem every team has
Résumés and take-homes don't tell you much anymore
AI writes the résumé, finishes the take-home and rehearses the interview. Everyone who applies looks equally good, while their real skill is worlds apart.
Every take-home looks perfect. Who actually did it?
Hiring teamApplied to 40 places. Silence. No idea why.
Job seeker300 résumés, filtered by keyword, and a lot of hope.
Hiring teamMy portfolio shows what I built, not how I think.
Job seekerFive interview rounds and we still don't know if they can do the job.
Hiring teamNew grad. I just want one hour of real work to prove it.
Job seeker
Why now
The same submission does not mean the same person
AI makes output cheaper every day, so résumés, portfolios and take-homes all look about as good. What stays scarce is the person who knows what to ask the AI for, can check that what came back is right, and owns the outcome. That's what OperatorRank measures.
A made-up exampleThe same-looking submission
Candidate B
- Lets the AI patch each reported symptom
- The visible tests pass, so they submit
- Never notices the fix broke something that worked
- Can't explain it in the Defense
A fix that breaks what worked earns nothing
A résumé or the final code can't tell these two apart. The timeline, the hidden checks and the Defense can.
Missions on day one
Three missions from a real warehouse system
All three are Stockroom, a warehouse service that receives, allocates and picks stock. Candidates get the whole system, plus what the floor reported, the decision records and the runbooks. They work out what the real problems are, then get the AI to fix them right.
Stockroom Full
Deliver the signed receiving, stock-trace, picker and finance-close priorities in a warehouse service without breaking accepted records.
- 75 min
- 816 hidden checks
- Defense required
Stockroom Focused
Repair allocation-ledger, reservation and ASN import behavior in the warehouse service.
- 60 min
- 655 hidden checks
- Defense required
Stockroom Receiving
Repair allocation-ledger, ASN import and expiry/FEFO behavior in the warehouse service.
- 60 min
- 531 hidden checks
- Defense required
Mission content is in English · Hidden checks counted on 19 Oct 2026
What the hidden checks reward
Patching symptoms
- Quick one-line patches for each report
- The visible tests may all pass
- Break something that worked and that fix earns nothing
Scores low
Fixing the cause
- Reads the documents and works out which rule is right
- Has the AI fix the cause, then checks it really did
- Doesn't break what already worked
Points sit on root-cause fixes
Why you can trust the result
A test with a clear spec, AI can pass for you.Our missions need a human head.
Real work never comes with a spec. It comes as a symptom, scattered evidence and business rules that sometimes disagree. The people worth hiring find what's right, then get the AI to do it right. That's what we measure.
- 01
Taken from real work, with no spec to copy
Candidates get a real system with a real problem, plus the business documents and what customers reported. The code shows what is wrong; the right answer is in the business evidence (docs, logs and tickets), not in a hint.
What candidates get at the start brief.mdWhat happenedops/complaints.mdWhat the floor reporteddocs/adr/Decision recordsdocs/runbooks/Runbookslogs/System logsstockroom/The system's codetests/The visible tests
- 02
Use AI freely, but everyone gets the same
A cloud workspace with AI built in. Everyone gets the same time and the same AI budget and chooses from the same set of models, and every action is recorded on our server, not sent in by the candidate.
The same for everyone Time60–75 minutes by mission, kept by the serverAI budgetThe same for everyone; when it runs out, the AI stopsModelsThe same set, chosen by the missionHidden checksThe same set for everyoneRecordedEvery command, question to the AI and code change, on our server
- 03
Graded by hidden checks the candidate never sees
Between 531 and 816 checks, depending on the mission, the same set for everyone. Points sit on the real root-cause fixes, not on quick one-line patches; break something that already worked and that fix earns nothing. Per-check results are kept for review or appeal.
Sample table of the level reached in each piece of the work Sample result page: passed, every piece reached its required level
Why OperatorRank
What the usual ways of screening can't give you
Point by point, against the ways most teams screen engineers today.
| Keyword résumé screening | Online coding tests | Take-home graded by engineers |  OperatorRank | |
|---|---|---|---|---|
| What it measures | What the résumé says | Puzzles and algorithms | Depends on the task | A real system with a real problem, plus business documents |
| Can they use AI? | AI writes the résumé | Often banned or policed | Yes, but you can't see how | Fully, and we measure whether they use it well |
| Do you see how they work? | No | Often only the final answer | Only the final result | A recorded timeline the candidate can walk you through |
| Do they understand what they shipped? | Unknown | Unknown | Needs another call | The Defense asks everyone about their own work |
| How it's graded | Keywords that match the ad | Tests on standard puzzles | A reviewer's opinion, 30–60 min each | 531–816 hidden checks, the same set for everyone |
| Are candidates watched? | No | Often camera or screen recording | No | No camera, no screen recording |
| When do you get a result? | Instantly, with no skill shown | Instantly | Days | After the automatic check, with no reviewer to wait for |
| Who decides | A filter drops people by keyword | One overall score | A reviewer's opinion | People on your team, from evidence they can explain |
Compared with common ways of screening, not with any particular product.
Built for the AI era
Many tools still treat AI as cheating. We treat it as a work tool and measure who uses it well and owns the outcome.
See what the output can't show
Two people submit the same-looking work; the timeline and the Defense show who understood it and who accepted whatever the AI wrote.
Points for the root cause
Hidden checks reward root-cause fixes and give zero to a fix that breaks what already worked. Symptom patches score low.
No engineer time
Hidden checks grade the work automatically; your team reads only the results worth reading, even as thousands of applicants arrive.
Candidates want to take it
AI allowed like real work, no camera, nothing to install, nothing to pay. A good experience is your employer brand.
Made for Thai teams
The site, the results and the organisation app are in Thai and English, and candidates can hold the Defense in Thai. The workspace and the launch missions are in English.
For companies
What you can do with it
Sample table of the level reached in each piece of the work Screen the first round without engineer time
Have candidates take a mission and share the result, let the system check it, and read each one: pass or not and the level for every piece. Nobody gets ranked for you.
Sample Defense conversation between the AI reviewer and the candidate Read how they think before the interview
The shared result shows where they're strong, piece by piece, and candidates can take you through their own Defense and timeline, so you walk into the interview with sharp questions instead of starting from zero.
Sample progress of a team assessment round Measure your own team, too
Your people take the launch missions on their own accounts and share the result with you, so the level for each piece shows where the team is strong and where it needs help.
Sample job board on the organisation side Post jobs in the same app
Open job posts and receive applications; a candidate can put a link to their own mission result in the application note, all in the same app where you read results.
Sample classes page for a school Teach in schools and courses
Open classes, keep the student list and post announcements; students practise on the launch missions with their own accounts. Results are learning progress, not hiring evidence.
Fits the way you hire
Drop nothing. Put us into the flow you already have
Résumés, take-homes, interviews and live coding all stay. Put OperatorRank at any step: replace the steps AI can now do for candidates, or make it the last step. Try each one.
Before the résumé
Job post → OperatorRank → Résumé review → Interview / live coding → Decision
Ask everyone who applies to take a launch mission first and put the result link in the application, then open the résumés of people with strong evidence. Good engineers who write weak résumés stop falling out at the first gate.
Instead of the take-home
Job post → Résumé review → OperatorRank → Interview / live coding → Decision
Replace the assignment AI can do in full. The shared result shows, piece by piece, who really fixed the cause, without an engineer grading it.
Before the interview
Job post → Résumé review → Take-home → OperatorRank → Interview / live coding → Decision
Keep every step and add a mission before the interview round, then start your questions from the result the candidate shares.
Finish with us
Job post → OperatorRank → Decision
Make the mission the main gate. Your team sees everyone's real skill from the results they share. People on your team decide.
For people
Prove your skill with real work, not a résumé
Practise on missions that feel like a real workday, use AI freely, and get a result that tells you plainly where you're strong and what to practise next.
Practise on real problems
Not memorised puzzles: a real system with real problems to fix.
Use AI the way you do at work
Chat with the AI, use the terminal and review diffs, as you would with an AI agent.
Know where you're strong
The checks and the level per piece say exactly what passed and what didn't.
Your practice is yours
Only you see it, until you choose to share.
Practise on free credits
Practice uses the free credits on your account; there's nothing to buy.
Nothing to install
It runs in the browser; the workspace lives in the cloud.
Fairness and privacy
The same field for everyone
What's recorded
- Commands, files, diffs and tests run in the workspace
- The conversation with the AI and the AI budget used
- The whole Defense conversation
What's never collected
- Camera or microphone
- Screen recording
- Anything typed or opened outside the workspace
Same time
The clock runs on the server. Closing the browser doesn't stop it, and nobody can add time.
Same AI choices, same budget
The mission sets which models can be used and everyone chooses from that set. The AI key never sits in the workspace.
A workspace of your own
No outbound internet, and nothing you do there touches anyone else.
No surveillance
No camera, no screen recording, nothing outside the workspace.
If we break, you can appeal
Outages are on the record. You get credit back, a retry or a re-check, as the policy says.
People decide
No AI hires or rejects anyone. The system gives evidence; a person reads it and decides.
Get started
Which side are you on?
For companies
Find engineers who can really do the job
Have candidates take a mission, let the system check it, and read the result they share before you decide. For companies, schools and training courses.
For people
Prove your skill on real work
Practise on missions from real work with free credits. Your practice results are yours alone until you choose to share them.
FAQ
Questions? We've collected the answers.
Can't find yours? Email the team. support@operatorrank.com
What is OperatorRank?
A way to measure tech skill with missions taken from real work. Candidates work with AI in a cloud workspace, hidden checks grade the result automatically, then an AI reviewer asks follow-up questions. The person who takes it gets a report they can open at every step and can share the result with a company.
Can I really use AI?
Yes, and you should use it well. Everyone gets the same time and AI budget, and chooses from the same set of models the mission allows. What's measured is whether you know what to ask the AI for, and whether you can check that what it did is right.
How is the work graded, and by whom?
The system runs between 531 and 816 hidden checks, depending on the mission, against the submitted work, with the same commands for everyone. Points sit on the real root-cause fixes, and a fix that breaks something that already worked earns nothing. The result is pass or not, a BUILD score and a level for each piece of the work.
What is the Defense? Is it scored?
After submitting, an AI reviewer asks about the candidate's actual work: why they fixed it that way, what they'd do if it broke. All three launch missions require the Defense before the result shows. It has no score and no pass or fail, and the result's owner can read the conversation back with the result.
Who sees my practice results?
Your practice results are private by default, until you create a share link yourself.
Do I have to pay to take a mission?
No. There's nothing to buy: practice uses free credits under your account's terms.
What if my connection drops or I close the tab?
The workspace lives on our servers, so your files stay where they are; come back within the mission's time. The clock doesn't stop, though. If our system is the one that fails, you can report the problem or appeal the result.
Do I need to install anything?
No. It runs in the browser; the workspace lives entirely on our servers.
Can we use it to assess our own team?
Yes, with the launch missions: each person takes one on their own account and chooses whether to share the result link with you, which shows pass or not and the level for each piece.
Does the system decide who gets hired?
No. The system gives evidence; people in the organisation read it and decide. There is no overall score that ranks people, and no automatic hire or reject button.
Use AI. Own the outcome.
You are on-call. Good luck.
Sign up now, and we'll see you at the first mission, whichever side you're on.