How to Identify Low‑Quality Resumes and Spot Fake Experience in Technical Interviews

1. How to Identify Low‑Quality Resumes in the Initial Screening

Training institutions often provide resume writing and interview coaching, resulting in many resumes with uniform, templated characteristics.

1) Young age but holds an advanced degree

While not a definitive rule, most candidates meet typical academic expectations; those with self‑studied qualifications should demonstrate unique technical highlights.

2) Older age but little technical experience

Older candidates often have reduced learning ability for new technologies, making a lack of practical experience a serious concern.

3) Project experience limited to CRM systems, e‑commerce sites, management platforms, survey tools, or classroom exam systems

Project experience is a key indicator of a candidate’s level; the market continuously produces innovative internet companies and emerging industries.

4) Project background does not match internet development trends

Project timelines must align with market evolution; for example, lottery projects after 2015 or live‑streaming before its rise would be inconsistent with real market demand.

5) Multiple projects across different jobs share identical technical architecture or structure, lacking novelty

Different companies typically use varied tech stacks; identical architectures across several positions suggest resume padding.

6) Overly novel technologies are highlighted while older, essential technologies are omitted

Experienced CTOs and architects usually prefer stable, mature technologies; training providers tend to chase the latest hype, leading candidates to ignore foundational skills.

7) Rich work experience but only low‑level responsibilities

This may indicate limited growth opportunities at the previous employer, insufficient personal capability, or excessive resume embellishment.

8) Companies spanning multiple provinces or cities

Many resumes show cross‑city job changes, especially from small firms (<50 employees) in cities like Wuhan, Xiamen, Ningbo, or Nanjing, making verification difficult.

9) Lack of evidence of personal technical passion

Technical enthusiasts often have blogs, GitHub profiles, or forum contributions; these can be verified via search engines.

2. During the Interview: How to Detect Exaggeration and Inconsistencies

There is no single standard, but the following points are commonly used in practice.

1) Assess company size, team structure, and collaboration methods to gauge real work experience

Ask about the number of employees, team composition (product, backend, frontend, mobile, UI, testing), cooperation patterns, product lifecycle, release frequency, user base, and concurrency metrics.

2) Verify employment dates, project initiation/completion times, technology stacks, and iteration processes

Many candidates over‑package their resumes; probing dates, technologies used, and review procedures can reveal discrepancies.

3) Evaluate technical depth through targeted questions

Examples include:

For a candidate claiming Redis expertise: ask about used data structures, business scenarios, plugins, serialization methods, and encountered issues.

For a candidate claiming HTTP protocol and crawling experience: ask about common HTTP headers, handling of mismatched front‑end/back‑end data, HTTP message structure, cookie header name, meaning of "Transfer‑Encoding: chunked", and segment loading processes.

Often candidates lack fundamental knowledge despite years of claimed experience, such as not knowing GitHub for a two‑year Git user, or being unfamiliar with Redis data structures after a year of usage.

In conclusion, while some resume embellishment is acceptable, recruiters should strive for a balanced assessment to find candidates who truly match product needs. The author’s experience eventually led to hiring suitable teammates and hopes other interviewers can similarly find the right technical partners.