Adversarial Technical Verification Protocol
Your HR Filters Are Blind to Your Next 10x Engineer.
80% of technical resumes are now inflated with LLM-generated hype. Your senior developers are losing 15 hours a week interviewing "Paper Seniors" who can't ship complex logic. BetterSignalHQ uses Adversarial Logic Probes to break AI-cheaters and uncover raw architectural talent before you send a single calendar invite.
// monitoring: senior-engineer-interview-bandwidth
Weekly Engineering Hours Lost
15h/ lead
Paper Senior Detection Rate
> 80%flagged pre-interview
The Hard Truth
The $250k Integrity Gap
Our Claim-to-Signal Verification stage cross-references every resume claim against live probe performance. The average mis-hire who clears a standard screening costs a lean team 6+ months of roadmap. We catch them in Stage 4 — before they ever reach your calendar.
30 Minutes Back Per Interview
The average senior engineer loses 3.2 hours per unqualified interview loop. Our 10-stage pre-screen — from Intent Verification through the Logical Drift Probe — means your Lead Architects only sit down with verified architects. Not performers. Architects.
The Signal Your Filter Missed
Keyword filters reject candidates whose résumé doesn't tell the story their commit history does. Our GitHub Trajectory + 2x Logic Replay surfaces the unconventional builder who ships — the one your ATS scored a 62% and your competitor is about to hire.
The Signal Recovery Protocol
How We Isolate the Signal: A 10-Stage Adversarial Protocol.
BetterSignalHQ isn't another "friendly interview bot." It's a hardened verification layer that assumes every candidate is using LLMs. We recover signal across ten stages—from Intent Verification, Ecosystem Intelligence, and GitHub Trajectory, through Claim-to-Signal and Requirement Alignment, to Logical Drift, Hidden Invariants, Token-to-Solution Efficiency, the Humanity Signature, and a final 2x Logic Replay of the entire thought process.
01–03 Intent, ecosystem awareness & GitHub trajectory surface motivation, ecosystem fluency, and code growth patterns.
04–07 Claim-to-signal, requirement alignment, logical drift, and hidden invariants expose architecture-level thinking.
08–10 AI leverage, behavioral traces, and a 2x logic replay confirm a human architect is in control.
1. Intent Verification · Intent
Intent Verification
We filter for high-motivation, company-specific intent before we touch code. The engine looks for how precisely the candidate understands your domain, why they want this role, and whether they've done real homework on your stack and constraints.
Company Context
references roadmap & risks
Preparation
studied stack & product
Motivation
specific, non-generic
2. Ecosystem Intelligence · Ecosystem
Ecosystem Intelligence (The "Passion Probe")
We test whether candidates are awake to the ecosystem they're building in—from React 19 shifts to security incidents like Log4j to AI's impact on their tools. High-signal architects continuously integrate new constraints into their mental model of the stack.
React 19
mentions breaking changes & tradeoffs
Security
references Log4j & supply-chain risk
AI Impact
uses LLMs as tools, not crutches
3. GitHub Trajectory · The Past
GitHub Trajectory Optional Background
We bypass "Green Squares." Instead, GitHub Trajectory maps language growth, commit quality, and architectural stewardship over time. This stage can be toggled on for candidates with public work, giving you a longitudinal view of how they actually evolved.
Refactor Density
14 structural / 18 months
Stack Breadth
TS, Go, infra-as-code
Quality Trend
improving
[trajectory] languages=3 · code_reviewed=82% · anomalies=0
4. Claim-to-Signal · The Resume
Claim-to-Signal Verification
Resumes are now AI-hallucinated. We cross-reference every claim—from "Kubernetes Expert" to "Low-Latency Guru"—against real-time performance in our probes. We flag the Integrity Gap immediately.
Resume Claim
"SQL Expert" · "Performance Tuning"
Probe Result
Failed index-optimization + lock-contention probes
[gap] integrity_score=0.31 · recommendation=hard filter
5. Requirement Alignment · The Spec
Requirement Alignment Background
Before any coding, we test whether candidates interrogate the spec. High-signal architects clarify ambiguous milestones, dependencies, and failure modes instead of sprinting into code that solves the wrong problem.
Clarifying Questions
milestones, SLAs, edge-cases
Assumption Calls
explicit, documented
Risk Surfaced
delivery & failure modes
6. Logical Drift · The Interview
The Logical Drift Probe
We don't ask candidates to "invert a binary tree." We present standard coding problems but inject "Logical Drift"—a fundamental rule change that breaks standard LLM training data. AI-cheaters hallucinate the standard answer. Real engineers catch the constraint.
> LLM output: "standard solution detected"
> Human output: "constraint mismatch · re-evaluating requirement"
Drift Applied
+17%
LLM Failure Rate
91%
Human Detection
72%
7. Hidden Invariants · The System
Hidden Invariant Testing
We present code with a hidden dependency mapped to dummy logs. A junior cleans the code and breaks the system. A Senior stops and asks: "What owns these orphaned keys?"
[09:14:03] candidate deletes "legacyMapping"
[09:14:04] ▶ invariant_breach: orphaned_log_entries_detected
[09:15:22] ▶ senior_candidate: "what owns these orphaned keys?"
Blind Refactor Score
high = risk
System Awareness
architect-level
8. Token Efficiency · The Future
Token-to-Solution Efficiency
Modern 10x Engineers leverage AI as a force multiplier. We measure the "Token-to-Productivity Ratio." Can they guide an LLM to a complex fix in 2 prompts, or 20?
Prompt-to-Fix Path
[Complexity: High... Prompts: 2... Token Efficiency: 98th Percentile]
9. Humanity Signature · The Behavior
The Humanity Signature Background
We track the "Thought-to-Code" ratio. Real developers delete, hesitate, and jump between logic and UI. LLMs dump perfect blocks of code linearly. We provide a Signal Confidence Score based on behavioral problem-solving, not just correct outputs.
Thought-to-Code Ratio
Undo Events
human-like
Cursor Jumps
non-linear
Signal Confidence
0.91
10. 2x Logic Replay · Final Review
The 2x Logic Replay Background
We generate a high-speed filmstrip of the candidate's entire thought process—every edit, pause, and branch—compressed into a 2x replay for your final decision review. Your team sees the real problem-solving arc, not just the end state.
// Initial problem: sort by custom rule
function sort(arr) {
return arr.sort((a, b) => a - b);
} [replay] stitched from keystroke_trace() + invariant_monitor()
Signal vs. Theater
Every other process is a liability
your CTO is personally absorbing.
The problem isn't that you're hiring frauds. The problem is that your current process cannot tell the difference. Here's exactly where it breaks — and which stage of our protocol seals it.
Standard AI Screeners
BetterSignalHQ
Candidate Intent
The process assumes any applicant is worth thirty minutes of your time. No motivation filter exists.
Intent Verification measures domain-specific motivation and company research depth before a single technical probe runs.
LLM-Proof Logic
Any candidate with GPT-4 open on a second screen scores in the top 20% of every coding assessment on the market.
Logical Drift Probe injects rule changes that break LLM training data. The model hallucinates the standard answer. The engineer catches the constraint.
Resume Integrity
"Senior React Engineer" equals whatever the candidate typed. No recruiter on earth can validate architecture claims live.
Claim-to-Signal cross-references every resume claim against live probe performance. Integrity score surfaces in real time.
Growth Trajectory
Green squares. Commit count as a proxy for seniority. No view into language evolution, refactor quality, or stewardship.
GitHub Trajectory maps language growth, refactor density, and architectural stewardship across 18 months. Depth over decoration.
AI as Multiplier
Whether a candidate uses AI as a precision tool or a crutch is completely invisible to every screener on the market.
Token Efficiency measures the prompt-to-productivity ratio. Two prompts to a complex fix, or twenty? That delta is the 10x signal.
Human vs. LLM Output
No behavioral trace. No pause analysis. A perfect code block is a perfect code block — provenance unknown.
Humanity Signature tracks keystroke cadence, undo events, cursor jumps, and Thought-to-Code ratio. Architects pause. Paste-and-pray does not.
Hiring Manager Deliverable
Maybe a transcript. Nothing your Lead Architect can act on before their 30-minute final call.
2x Logic Replay delivers a compressed filmstrip of the entire thought process. Your team reviews the arc before the call. The interview becomes a formality.
Net Result
Your CTO spends 40 minutes with a candidate who memorized the answer. Roadmap slips. The real hire goes to your competitor.
Your CTO opens the 2x Logic Replay before the call. They already know. The interview is a formality. You make the offer.
Sahil Garg
Founder
Why I Built This
"I was the intern in the room."
In early 2026, I watched my senior colleague arrive before anyone else, skip his lunch, and stay late — all on the same day he had to ship a critical feature. The reason: an interview had been dropped into his calendar for a candidate claiming 3.5 years of React experience.
The interview lasted forty minutes. The candidate couldn't explain a single project on his own resume. But nobody stops an interview once it's started.
My senior came back to his desk, opened his laptop, and worked through dinner to hit his deadline. Nobody acknowledged what had just happened. It was just... normal.
A few months earlier, I had been on the other side of that table — a 20-year-old whose actual ability never made it through the filter. Not because I couldn't do the work. Because the process never asked the right questions. I watched senior engineers spend their most valuable hours on a process that was failing everyone in that room — including them. Candidates performing. Interviewers guessing. Nobody getting what they actually needed.
I couldn't unsee either moment.
"BetterSignalHQ is my attempt to fix the part nobody talks about — the thirty minutes before a senior engineer wastes their afternoon, where the signal was always there if you knew how to read it."
Low-Risk Pilot · High-Signal Return
Don't gamble your runway on a Paper Senior.
Stop rejecting hidden gems and interviewing frauds. Let us run an Adversarial Signal Audit on your next 5 candidates.
No credit card required. If we don't catch at least one AI-augmented mismatch your team would have wasted time interviewing, the audit is completely free.