Project-Based Take-Homes That Resist Cheating in 2 Hours

You fast-track a "can't miss" analytics candidate after a clean take-home: crisp charts, tidy repository, thoughtful write-up. Two weeks after onboarding, dashboards break, basic SQL requests stall, and every "quick question" becomes a Slack thread that smells like someone else is doing the work. By the time you unwind it, the blast radius is not just replacement cost. It is trust with stakeholders, roadmap slippage, and awkward internal conversations about why your process let a proxied or AI-generated submission through. By the end of this playbook, you will be able to design a project-based take-home that fits a strict time cap while generating integrity signals and a clear escalation path when something feels off.

Use project-based take-homes when you need evidence of real Day 1 execution: scoping, tradeoffs, reproducibility, and communication under constraints. Short, scoped projects also make it harder to "borrow" a pre-solved answer bank compared to standard puzzles. Risk context matters. Checkr reports that 31% of hiring managers say they've interviewed a candidate who later turned out to be using a false identity. Directionally, that implies identity risk is no longer edge-case noise for remote-friendly roles. It does not prove your team's fraud rate is 31% or that every role is equally exposed. Pindrop notes that 1 in 6 applicants to remote roles showed signs of fraud in one real-world pipeline. Directionally, that suggests remote pipelines should assume some level of adversarial behavior. It does not tell you which signals are most predictive in your specific funnel, so you still need instrumentation and review discipline.

Assign clear ownership before you redesign the assessment. Without it, you will oscillate between being too strict (false rejects) and too permissive (fraud leakage). Recommended operating model: Recruiting Ops owns workflow and SLAs, the Hiring Manager owns the rubric and calibration, and Security or GRC reviews the integrity policy and data retention controls quarterly.

Start with a time cap you can defend, then design the prompt to be "complete at the cap" instead of "perfect when overworked". A project that requires heroics invites outsourcing and punishes honest candidates. A reliable pattern is a small, messy dataset or event log with one business question and one technical constraint. The output should include a reproducible command and a brief decision log that makes the candidate's thinking legible.

Treat integrity as a risk scoring problem, not a morality trial. Your goal is to route ambiguous cases into a fast step-up, while keeping clean candidates moving. The most useful signals are the ones you can explain in an audit: what was observed, why it is suspicious, and what you did next.

Weight the rubric toward reasoning and reproducibility, because those are expensive to fake consistently at scale and correlate with Day 1 performance. Penalizing formatting and style encourages cosmetic perfection that is easy for generative tools to produce. Calibrate the rubric in a 30-minute session with 3 historical submissions (good, average, suspicious) so reviewers score consistently and you avoid random false positives.

Write the policy down so it is enforceable, reviewable, and consistent across roles. The point is not more rules. It is fewer surprises and a clean audit trail when you step a candidate up. The artifact below is a practical configuration you can hand to Recruiting Ops and Security to implement consistent routing and evidence capture.

These patterns increase funnel leakage, increase false positives, and train adversaries on your blind spots.

IntegrityLens AI is built for teams that want project-based assessments without stitching together an ATS, a testing tool, and a separate verification flow. It combines ATS workflow + identity verification + fraud detection + AI screening interviews + coding assessments so your take-home stage is both fast and defensible. TA leaders and Recruiting Ops teams use IntegrityLens to automate stage movement, SLAs, and step-up routing. CISOs and Security teams use it to enforce consistent identity gates, review access, and evidence handling. In this specific use case, IntegrityLens helps you: verify identity in under three minutes before high-trust steps, run time-capped coding assessments, capture integrity signals as structured events, and generate Evidence Packs that explain why a candidate was stepped up or cleared. Key platform elements: - ATS workflow with auditable stage transitions - Biometric identity verification with typical end-to-end verification time of 2-3 minutes (document + voice + face) - AI screening interviews available 24/7 for follow-up and step-up questions - Technical assessments supporting 40+ programming languages - Security baseline including 256-bit AES encryption and GDPR/CCPA-ready controls

Measure operational outcomes first, then quality. If you cannot keep review effort stable, your "integrity" redesign will quietly be rolled back. Track these weekly and review them in the same meeting as funnel conversion: step-up rate, step-up pass rate, reviewer minutes per submission, candidate complaints about scope, and the proportion of offers that required step-up adjudication. Use trends, not single-week spikes. If you need a starting point, an illustrative example target is keeping reviewer time under 20 minutes per submission and keeping step-ups to a small, reviewable queue. Do not treat those numbers as universal benchmarks. Tune them to your hiring volume and role criticality.