Legible

Legible

How It Works

Service method

Review first. Diagnose second. Rebuild only if it is worth paying for.

Legible behaves more like a careful recruiter review than a scoring tool or quick-fix generator. The service earns the paid step by making the free diagnosis clear first.

Step 1 Set up the case

We start with the target role, current challenge, and the core materials shaping the application.

Step 2 Review before speaking

The case is read before the diagnosis appears, so the product shows its work before it judges.

Step 3 Rebuild after the free diagnosis

The rebuild is offered only after the free diagnosis has made the problem concrete.

The customer journey

1. Case setup

The customer shares the role target, challenge statement, and relevant materials.

2. Active review

The service surfaces what it found before it reveals the main blocker.

3. Free diagnosis

The customer gets one named blocker, one explanation, and first correction priorities.

4. Structured follow-up

If the customer continues, the service asks a short set of questions only to improve proof and targeting.

5. Access and payment

After the diagnosis, you enter an invitation code to unlock the full rebuild. No payment wall before you have seen the evidence.

6. Rebuild dossier

The result is a rewritten CV, an optional cover letter, and three concrete next steps.

What makes this different

  • No instant diagnosis before review
  • No payment wall before value is shown
  • No dashboard logic for its own sake
  • One job: identify the blocker and improve the hiring signal

Free

Useful on its own

The free layer should be good enough to make the product credible, even if the customer stops there.

Paid

Deeper, not just bigger

The paid layer is justified by better rewrites, sharper positioning, and a clearer next-move dossier.

Real example

This is what a free diagnosis looks like.

A real case — anonymised. Senior Backend Engineer, 7 years of experience, not getting through to interview. This is what the review found, and what changed after the rebuild.

Main problem found

Strong track record, no evidence of impact.

Seven years of backend engineering across growing teams — but none of the roles show what changed because of the work. A recruiter scanning the CV cannot quickly judge seniority, because there are no results to anchor against. The experience is clearly there. The proof of it is not.

What was visible in review

Every bullet describes a task or area of involvement. "Working on backend services," "collaborated with cross-functional teams" — these appear in almost every backend CV and carry no signal about the level of the person writing them.

Why it matters

Without outcomes, a recruiter cannot distinguish a mid-level engineer from a senior one doing identical work. Two candidates with the same bullet structure but different actual impact look the same on paper.

What likely happened in review

The reviewer moved on within 20 seconds, unable to confirm seniority from what was written. The CV was probably set aside rather than rejected — a silent filter, not a conscious decision.

What needs fixing

Lead every role with one quantified outcome — what changed, by how much, over what period. Even a rough range is stronger than a description of responsibility.

The single clearest change Replace the first bullet in each role with a result. Not what you did — what changed because of it.

Three immediate actions

1 Replace the top bullet in each role with a result — what changed because of your work, in any number you can defend.
2 Remove the profile section — it restates what the CV already shows without adding evidence.
3 Delete references to redundancy and restructuring — they belong in an interview, not a CV.
Original CV Before
JOHN DOE
Senior Backend Engineer
Copenhagen, Denmark  |  john.doe@email.com  |  linkedin.com/in/johndoe
Profile
Senior Backend Engineer with 7+ years of experience building scalable backend systems across startups and high-growth tech companies. Experienced in fast-changing environments, including layoffs and restructuring, while consistently delivering backend services.
Professional Experience
Senior Backend Engineer  ·  TechScale  ·  Jan 2024 – Present
Working on backend services supporting core product features
Contributed to improving system performance and stability
Involved in architectural discussions around scaling services
Collaborated with cross-functional teams
Backend Engineer  ·  DataFlow Systems  ·  Mar 2023 – Dec 2023
Developed and maintained APIs for internal and external clients
Helped migrate systems toward a modular architecture
Role impacted by company restructuring
Backend Engineer  ·  CloudOps Labs  ·  Feb 2022 – Feb 2023
Built backend components for cloud infrastructure tooling
Position ended due to layoffs
Backend Engineer  ·  StartupCore  ·  Jan 2018 – Jan 2022
Part of early team building backend systems from scratch
Designed and implemented core APIs and services
Helped scale platform as user base grew
Read in full →
Rebuilt CV After
John Doe
Senior Backend Engineer
Copenhagen, Denmark  ·  john.doe@email.com  ·  linkedin.com/in/johndoe
Java  |  Spring Boot  |  Kotlin  |  Go  |  AWS  |  Docker  |  Kubernetes  |  PostgreSQL  |  Redis  |  CI/CD
Experience
TechScale — Copenhagen
Senior Backend Engineer  ·  Jan 2024 – Present
Reduced response times from 2–3 seconds to under 500ms by tuning backend services
Cut error rates to below 1% by optimising PostgreSQL queries and adding indexes
Owned backend services with a focus on reliability and scalability
DataFlow Systems — Copenhagen
Backend Engineer  ·  2023 – 2024
Built and maintained APIs for core platform functionality
Moved parts of the system toward a modular setup to reduce coupling
CloudOps Labs — Copenhagen
Backend Engineer  ·  2022 – 2023
Improved stability by tightening error handling and retry logic
Reduced deployment failures by hardening backend components
StartupCore — Copenhagen
Backend Engineer  ·  2018 – 2022
Reduced deployment-related incidents by 30–40% by splitting a monolith into separate services
Stabilised a service handling ~20–30% of traffic through query optimisation and indexing
Built core backend for a SaaS platform that grew to tens of thousands of users
Read in full →

Ready to start

Get the diagnosis before you decide anything else.

Submit your details and get one named blocker, one explanation, and first correction priorities — free, no payment needed.