Defending an AI-Assisted Answer: A Talking-Points Playbook
Interviewers catch AI users with the explain-it-back vector, not the overlay. The four-phase playbook for defending your answer.
Aceloop Journal
How candidates actually get the offer.
Tactical guides for FAANG-style coding interviews. Patterns, problem walkthroughs, company-specific prep, comparisons, and the stealth side of AI-assisted interviewing.
Latest
Just published
12 Algorithm Patterns: Talking Points for AI-Assisted Code
Twelve patterns (sliding window, two-pointer, DP, and more) with the anti-pattern phrase and the strong-candidate phrase for each.
Test Any AI Interview Tool in 60 Seconds (Free Simulator)
Aceloop's proctor simulator runs the same vectors a real proctor uses: keystroke, focus, screen-capture.
Pillars
Engineering deep-dives
Four Stealth Layers Aceloop Stacks at the Windows Kernel
Display-pipeline filtering, process concealment, window-enumeration blocking, detection-query spoofing: four kernel layers, structurally invisible.
How CoderPad Enterprise's Anti-Cheat Detects AI Tools
A forensic walkthrough of CoderPad Enterprise's detection stack: content scripts, hotkey enumeration, screen-share fingerprinting.
How Proctor Content Scripts Work, and Why Browser AI Fails
A forensic look at the JavaScript proctoring platforms run inside your interview tab: six DOM APIs and why browser-based AI fails.
Should You Use AI on a Coding Interview? Decision Tree
Eight forks, no preaching: a senior engineer's framework for deciding whether to use AI on a specific round in 2026.