Q1 2026 Candidate Profile Updates Release Notes

To give candidates a faster way to build rich, accurate profiles that show skills beyond code.

To give companies better‑structured data (including AI fluency) without disrupting existing workflows all at once.

Candidates:
​See the full new profile experience and updated UI. They can use the CV uploader, new sections (AI Fluency [Beta], expanded Projects, richer Education, etc.) and the profile evaluator.

Companies:
​Still see candidates in the existing company UI, but some newly mapped data already flows through. AI Fluency [Beta] is visible as an extra signal on supported candidates.

Candidates:
​No changes.

Companies:
​UI extended to surface more of the new profile data:

Candidates:
​No changes.

Companies:
​Additional new‑profile data becomes visible:

Candidates:
​No changes.

Companies:
​Final set of new‑profile data is surfaced:

Candidates can now upload their CV and have their profile automatically populated with information that the parser extracts, such as work experience, education and skills.

This turns profile setup into a review and refine flow rather than starting from a blank page.

Reason for leaving previous roles
Candidates can briefly explain why they moved on from each role. This gives companies more context for job changes and gaps.

Soft skills used in previous roles
In addition to technical skills, candidates can record key soft skills per role, such as stakeholder communication, mentoring or people management.

Link to projects
Candidates can link projects directly to each work experience entry so that concrete examples of work are tied to the role where they happened.

Work environment preferences
Candidates can describe the type of culture they would like to work in next, for example fast paced, cross functional or process driven. This helps match beyond tech stack and title.

Years of experience in desired skills
For each skill they want to work with next, candidates can now specify how many years of experience they already have with that skill.

Career transition rationale
Candidates can explain the role they want to transition into and why they are a good fit. This is especially useful for role changes such as developer to product, IC to manager or data to ML.

Entirely new section where candidates describe how they use AI in their work today, from everyday tools like Copilot or ChatGPT to building AI powered features and infrastructure.

They can link AI related projects, work experience and learning, and summarise their mindset and areas of caution such as privacy, IP or bias.

This provides companies with a structured signal on practical AI readiness instead of a simple tool name in a skills list.

Start and end date for the project

Company name where the project was done, if applicable

Link to Work experience to connect the project to a specific role

Problem solved so companies can see why the project existed

Impact of the project on users or the business

Checkbox for Used AI in project which links directly into the AI Fluency section

Skills used in the project

Demo URL for live demos or recordings, for example YouTube or Loom

Formal education
Candidates can add study type such as degree or diploma, status, reason for not completing if relevant, and a description.

Certifications
New category for professional certifications such as cloud or security, separated from general courses.

Courses and training
New category for short courses, online programmes and workshops.

Conferences and speaking
New category for conferences attended and talks given.

Learning and innovation
New category for self driven learning and experimentation, with fields for topic or tech, description, resource link and related projects.

A new AI powered profile evaluator reviews a candidate profile and suggests specific improvements, such as adding missing detail in work experience or clarifying the Ideal next job section.

This helps candidates quickly move from a basic profile to one that stands out with targeted guidance.

The candidate profile editor has been redesigned with a cleaner layout and sections that follow a more natural flow, from personal information and job intent to ideal next job, experience, projects, education and AI fluency.

The new UI makes it easier to see what is missing, understand how each section is used and complete a strong profile with less effort.

Companies can now see an AI Fluency pill on candidate cards where the candidate has completed the AI Fluency section. This gives a quick visual cue that AI experience is available to review.

AI Fluency is available as a filter in search so teams can find candidates who have indicated that they use AI in their workflow or build AI features and infrastructure.

Some candidate profile data has been remapped behind the scenes to align with the new profile structure and to prepare for richer display in upcoming releases.

No changes. Candidates continue to use the new profile editor and all Release 1 functionality.

Project cards in the company UI now display more of the fields candidates complete in the new profile:

Where a project is linked to a work experience entry, companies can see that relationship, which makes it easier to understand context such as “internal tool built at current employer” vs “side project”.

When a candidate marks a project as “Used AI in this project”, that project now appears both:

On the company side, this link is visible so hiring teams can jump from the AI Fluency summary straight into a specific project that demonstrates how AI was used.

For each past role in Work Experience, companies can now see the candidate’s “Reason for leaving” where it has been provided.

This gives extra context for job changes and gaps without needing to wait for the first interview.

Skills now include years of experience as provided in the new candidate profile.

In the company view, teams can see both:

This makes it easier to gauge seniority on specific technologies and to compare candidates who share similar stacks.

No changes.

The Work Experience section in the company UI now reflects more of the new candidate fields, including:

This gives a more accurate picture of how the candidate has actually been working day to day.

Soft skills that candidates tag against each role are now visible to companies.

Examples include stakeholder management, mentoring, leadership, communication or critical thinking.

This helps hiring teams see behavioural strengths in context instead of relying only on generic CV statements.

Skills are now visually grouped by type through colour coding, for example:

This makes it easier to scan a profile and quickly understand whether a candidate’s strengths sit in backend, frontend, data, DevOps, or a particular ecosystem, without needing to read every line.

The company view now shows:

This helps teams decide faster whether the candidate’s goals align with the open role, and gives useful context for interview conversations about fit and trajectory.