Как ВЗЛОМАТЬ систему найма и попасть на собес в 2026 / Самый полный гайд по обходу ATS и СБ

Summary

The video examines how recruitment works from the employer’s side, including job boards, recruiter workflows, applicant tracking systems (ATS), AI screening, candidate checks, and personal-data handling.

Anton Nazarov’s central argument is that job searching is a competitive funnel: candidates need to understand how employers filter applicants and improve their chances of reaching a human interview. Many claims are based on the speaker’s investigation and interviews; they are not independently verified here.

Hiring funnel and recruiter economics

The typical process begins when a hiring manager asks HR or a recruiter to fill a role. Recruiters often have only high-level knowledge of the role, so hiring relies heavily on filters, résumé searches, and screening.

The speaker distinguishes between:

• Internal recruiters, who are typically paid a monthly salary. He cites 100,000–150,000 rubles as a typical range.
• External agency recruiters, who may charge up to two months of the candidate’s salary or 25% of annual compensation for a placement.

Candidate leverage depends on the labor market. When there are many applicants for each opening, employers can impose faster timelines and more unpaid work. When talent is scarce, candidates have more bargaining power.

Recruiters source candidates through both active applications and passive searches of résumé databases. Candidates should optimize for both routes.

Job boards and résumé visibility

The speaker describes HH.ru as the dominant Russian job aggregator, with alternatives often duplicating its listings. He claims HH.ru reported about 40 billion rubles in revenue and 23 billion rubles in net profit.

Employers can search résumé databases, open contact details, promote vacancies, and use other paid services. The video cites several prices in different contexts:

• An HH Pro subscription of about 700 rubles per month
• Up to five automatic applications per day
• A package of 120 contact openings for 14,220 rubles per day
• An ATS vendor’s contact cost of roughly 1,500 rubles
• A standard 250,000-ruble hiring fee

These figures refer to different products or services and are presented as the speaker’s findings.

Employer-side filters may include experience ranges, location, education, and other attributes. The speaker says incomplete résumé fields or missing keywords can reduce visibility before a recruiter reviews an application.

Visibility playbook described in the video:

• Fill in résumé fields and include a brief cover letter.
• Match relevant skills and terminology to the job description.
• Check how a résumé ranks in search results and compare it with higher-ranked examples.
• Consider completing platform skill checks and keeping the profile active.
• Apply through multiple channels—job boards, company sites, LinkedIn, Telegram groups, and referrals—rather than relying on one source.

The speaker also recommends tactics such as creating test accounts and changing résumé details to avoid matching older records. These are presented as ways to influence search or avoid duplicate detection, but they can involve misrepresentation and create legal, reputational, or hiring risks.

ATS operations and personal-data risk

An Applicant Tracking System (ATS) is described as a workflow and record-keeping tool for moving candidates through stages such as résumé review, screening, security checks, and offers.

ATS use grew as online recruitment and application volumes increased. The speaker says a programmer vacancy might receive about 50 applications historically, 250–300 during the pandemic, and up to 1,000 in the current market.

ATS platforms help recruiters manage candidate records, automate messages, track funnel stages, and measure activity. The speaker emphasizes that ATS databases are generally employer-specific, not one universal blacklist shared by all recruiters.

The video alleges that résumés may be copied into ATS databases from job boards, email, or social platforms without proper consent, and may remain after a candidate hides a résumé or deletes an account. It also describes fake vacancies as a way to collect candidate data.

Compliance recommendation in the video: Candidates can request information about stored data, revoke consent, and ask organizations to delete records. The speaker recommends documenting requests and contacting Roskomnadzor if a company does not respond. These are legal claims and recommendations from the speaker, not legal advice.

For employers, the operational takeaway is to treat consent, retention, deletion, and access controls as real compliance processes—not just settings in an ATS. The speaker says ATS vendors often describe themselves as data processors while placing responsibility on the employer.

AI and automated screening

Recruitment technology vendors promote AI for generating job descriptions, sourcing candidates, scoring résumés, and conducting automated screening.

The speaker argues that many “AI” features are keyword matching or workflow automation rather than robust assessments. A model may rank a résumé higher because it contains more matching terms, even if those terms do not demonstrate stronger ability.

A key concern is garbage in, garbage out: AI-generated job descriptions may contain irrelevant skills, and résumé scoring against those descriptions can reinforce errors. The speaker also warns that such tools may reproduce biases from their training data.

The video cites a vendor or conference claim of a 70% reduction in résumé-processing time, but says it does not show that hiring quality, performance, or probation outcomes improve. It also cites a claim that 15–20% of candidates may be lost through AI screening, with vendors treating the remaining volume as acceptable.

Management implication: Evaluate recruitment automation using quality of hire, interview-to-offer conversion, candidate drop-off, and retention—not just speed or recruiter workload.

Screening and interview practices

The speaker criticizes subjective “culture fit” judgments and informal recruiter intuition, arguing they can reject qualified candidates before technical evaluation.

He cites research suggesting that:

• Recruiters who estimated candidates had only a 0–5% chance of passing a technical interview were often wrong: those candidates reportedly passed 47% of the time.
• Candidates assigned a 95–100% chance of passing reportedly passed 64% of the time.
• Recruiters’ assessments of the same candidate can vary substantially.
• Years-of-experience filters have less than 1% predictive value, while structured interviews, work samples, and cognitive assessments are more useful predictors.

Recommended hiring playbook: Define role-relevant competencies, use consistent questions, assess work samples, and track actual outcomes. The video argues this is more defensible than relying on résumé tenure, prestige, or an undefined “vibe.”

For candidates, the speaker recommends preparing structured examples using the STAR framework (Situation, Task, Action, Result), practicing technical explanations, and giving concrete accounts of decisions and incidents. He also advises adapting communication to the interviewer’s style.

The video discusses using AI assistants and other tools during interviews, including deceptive uses. These are described as tactics some candidates may try, not as sound or risk-free professional advice.

Security checks

The speaker says security checks vary by company and may range from basic identity and public-record checks to broader OSINT research. He argues that the security service’s primary purpose is company security, not validating technical competence.

He rejects claims of a universal nationwide recruiter blacklist or an all-powerful security service, while acknowledging that companies may examine public information, employment history, litigation, debts, and other records.

The practical recommendation is to understand what data an employer requests, avoid signing documents under pressure, and distinguish legitimate security checks from intimidation. The video presents these as general observations, not a definitive description of every employer’s process.

Metrics and figures cited

Metric Figure cited in the video Internal recruiter salary 100,000–150,000 rubles/month External recruiter fee Up to 2 months’ salary or 25% of annual salary HH.ru revenue / net profit About 40bn / 23bn rubles HH Pro subscription About 700 rubles/month Automatic applications via subscription Up to 5/day Contact-opening package 120 contacts for 14,220 rubles/day ATS contact cost / hiring fee About 1,500 rubles / 250,000 rubles Applications to a programmer role About 50 historically; 250–300 during the pandemic; up to 1,000 now Claimed résumé-processing time reduction 70% Candidates potentially lost through AI screening 15–20% Recruiter résumé review time About 5–7 seconds Reported technical-interview pass rates 47% for candidates rated 0–5%; 64% for those rated 95–100% Predictive value of years-of-experience filters Less than 1%

Presenters and sources

The presenter is Anton Nazarov. He refers to input from seven consultants and fact-checkers, as well as interviews or conversations with recruiters, ATS salespeople and vendors, security professionals, former law-enforcement personnel, and active security officers.

Other named people and sources mentioned include Anna Afonina, Lesya Naboka, Evgenia, Svetlana Petrovicheva, Vladimir Balun, and an unnamed security-service source. The video also cites recruitment research, ATS materials, conference presentations, and company documents obtained through sources.