FaangCoder Team

FaangCoder is built by a small team of Windows internals engineers. We write the kernel driver. We build the display-pipeline filter. We reverse-engineer the proctor stack on CoderPad, HackerRank, CodeSignal, and CoderPad Enterprise — then publish what we find here.

The product is a single-purpose Windows-native overlay that reads your problem and code straight from process memory at the kernel, runs them through the model, and streams the answer back — without any of the four detection vectors that get every other AI interview tool flagged. We've shipped this through enough live FAANG-tier loops, on enough proctored platforms, that we know which proctor vectors are real and which are marketing. We write about both.

The blog covers three things. First, stealth and detection mechanics — what each proctor stack actually does, why the user-mode flag every competitor leans on isn't enough, and what kernel-level techniques (the same techniques commercial anti-cheat suites like BattlEye and Easy Anti-Cheat use to catch cheaters) look like applied to the inverse problem. Second, competitor teardowns — we test every named competitor on real platforms and publish the results, including pricing math, false-stealth-claim audits, and reliability under load. Third, interview prep that works in 2026 — LeetCode patterns, system design templates, FAANG-loop playbooks. The prep content holds up without our tool; the stealth content makes the case for it.

Our brand stays low-profile by design. The louder a stealth tool gets, the faster proctor vendors fingerprint the binary. We grow through referrals, ship a free /proctor page that lets you verify any AI interview tool against the same detection vectors a real proctor uses, and trust the engineering depth to do the talking. If you want to verify the technical claims yourself, every post on this site links back to either the /proctor simulator or to the relevant Microsoft Learn / public-research source.