Skills-First Approach

Dimension: Capability · Type: Foundation

A career strategy that organises around named skills rather than job titles, and prioritises the skills the labour market is actively rewarding right now.

Introduced by Mirek Pospisil (LinkedIn), Rathan Kinhal (EY Switzerland), and Naria K. Santa Lucia (Microsoft Elevate) at the Upskilling for the Future session of the UN Inter-Agency Career Week 2026, on 6 May 2026. Extended in the The Skills Shift session by Olga Lehtinen and Matt Valente (UNICC). The argument behind it cites LinkedIn Economic Graph research and the broader skills-based hiring literature.

The framework

Job titles are labels. The work underneath any title is a bundle of skills. The market for those skills is moving faster than the market for the titles. The skills-first approach treats the skill, not the title, as the unit of career strategy.

When to use it

• When you are designing your career narrative and tempted to anchor it on the job titles you have held.
• When updating your CV or LinkedIn profile and wondering what to surface and what to drop.
• When your current title does not match the work you actually do, and you cannot see how to make a lateral move.
• When the labour market is shifting and you are unsure which skills to invest in next.

The data behind the case

LinkedIn data, presented in the session, makes the case concrete:

• Workers matched by skills qualify for over 3x the number of roles compared to workers matched by title.
• Over the last 10 years, the skills required for an average role have shifted by about 25%.
• By 2030, up to 70% of the skills required for any given role could be different from today.
• More than 10% of professionals hired in current jobs hold titles that did not exist in the early 2000s.

The implication is structural, not motivational. If you organise your career around titles, you are tracking a slower-moving variable and missing the faster-moving one.

Steps

1. List your skills explicitly. Not in your head; on paper or in a CV section. Include technical skills, domain knowledge, and human skills (leadership, communication, negotiation, facilitation, coaching).
2. Show skills in use. When writing a CV bullet, follow the Skills-in-Use CV Pattern: “Because of skill X, I delivered Y in Z context.” This is what makes the CV recognisable to skills-based recruiters.
3. Audit and decide what to keep, evolve, or drop. Use the Skills Self-Audit at least every 12 months. Skills age; the audit catches obsolescence early.
4. Stack adjacent skills deliberately. A single career today is becoming a portfolio of careers, and a portfolio of careers requires a portfolio of skills. When investing in learning time, choose skills that compound with what you already have rather than orthogonal ones.
5. Show your skills on LinkedIn. Recruiters increasingly use the skills section as a signal, especially when titles do not match. The LinkedIn Skills Signal Report 2025 confirms that workers who add skills to their profiles, especially disruptive tech and people skills, find jobs faster.

Three current skill clusters worth investing in

LinkedIn’s 2025 fastest-growing clusters, drawn from both demand-side and hire-rate signals:

• People skills. Leadership, communication, collaboration, change management. Rising as teams adapt faster.
• AI implementation. Beyond basic literacy. Real workflow integration, prompt engineering, AI strategy, agent building.
• Risk and compliance. Less obvious but increasingly valued as regulation accelerates across sectors.

A fourth cluster worth surfacing: green skills. Professionals who list any of the recognised green-skill categories (environmental policy, sustainable development, pollution prevention, sustainable finance, environmental protection, plus roughly twelve others) are hired at a higher rate than the broader market, even for roles that do not explicitly require them. If you have any honest exposure, list them.

These clusters will age. Re-check the published lists every year. The discipline is to stay current, not to memorise the 2025 set.

Inflating vs deflating skills

Day 5 Session 4 added a sharper filter on top of the three current clusters: AI is accelerating a divergence between skills inflating in value and skills deflating in value. Treat the filter as a quarterly check on where to invest learning time and where to delegate.

Inflating in value (invest here).

• Judgement under ambiguity.
• Sense-making across complex, contradictory inputs.
• Stakeholder navigation, especially across political, organisational, and cultural lines.
• Ethical scanning of AI-assisted outputs.
• Orchestration of AI agents and AI-augmented workflows.
• Diplomacy and human-to-human collaboration in high-stakes contexts.

These are the skills that are difficult to put into an LLM, especially without enterprise embedding. They are also the skills that an organisation’s “real” decisions still depend on.

Deflating in value (delegate, do not invest).

• Routine drafting from existing inputs.
• Information retrieval and synthesis from public sources.
• Formatting, polishing, formal-tone editing.
• First-draft analysis on structured data.

These are the skills AI does well at scale. Investing learning time here is investing against the trend.

The filter is not “do not draft” or “do not analyse”; it is “do not invest your learning time on routine drafting”. Continue to do these tasks where the work requires them, but use AI to accelerate, and direct your learning effort upward.

The four skill clusters above (people skills, AI implementation, risk and compliance, green skills) all sit on the inflating side. They are not in tension with the inflating/deflating filter; they are specific instances of it.

Worked example

A UN programme officer with twelve years of experience, currently a P-3 specialist in WASH (water, sanitation, hygiene), updates her LinkedIn profile after running this framework.

• Old presentation. Title-anchored: “P-3 Programme Officer, WASH” with a dated job description in bullet form.
• New presentation, skills-first.
  • Headline: “Programme management and behavioural change in WASH and adjacent public-health contexts. M&E, partner negotiation, results-based management.”
  • Skills section, populated with 25 named skills across three buckets: technical (WASH design, M&E, results-based management, donor reporting, risk frameworks), domain (public health, gender mainstreaming, climate adaptation), human (multilingual stakeholder negotiation, team facilitation, cross-cultural project leadership).
  • Three CV bullets rewritten using the Skills-in-Use CV Pattern, each opening with a specific skill applied to a measurable outcome.
  • Two skills she had not surfaced: green skills (sustainable water systems) and AI implementation (built a Power BI dashboard for partner reporting).

The job-search funnel changed. Recruiters reaching out about adjacent climate-adaptation, gender-and-public-health, and INGO programme-management roles, none of which her old title-anchored profile was surfacing.

Pitfalls

• Listing skills without evidence. A skills section on a CV is just a list until each skill maps to a worked achievement. Use BASIC entries to keep the evidence retrievable.
• Padding the skills list with claims you cannot back up. Recruiters will ask. Better fewer, well-supported skills than many thin ones.
• Treating “skills-first” as a one-off update. The list ages. Run the Skills Self-Audit at least annually.
• Confusing skills-first with abandoning your specialism. Specialism is a stack of skills, not the absence of one. The point is to articulate the stack, not to dilute it.
• Ignoring human skills. AI is making them more valuable, not less. The most marketable professionals are the ones bridging technical and human capabilities.

When not to use it

When you are applying inside a UN system that still requires title-anchored CVs and exact-language matching to vacancy notices. In those contexts, build the skills-first profile externally (LinkedIn, your own narrative), but on the application itself, mirror the JD’s language and use the JD vs Profile Comparison. The session was explicit that internal UN recruitment systems are still behind on skills-based hiring; the workaround is storytelling that fits within the existing forms.

A note on the source

The data points come from Mirek Pospisil’s LinkedIn presentation. The storytelling and skill-stacking layer is Rathan Kinhal’s. Naria K. Santa Lucia (Microsoft Elevate) added the AI dimension, including a free resource for the UN system: Microsoft Elevate for Changemakers. The inflating-vs-deflating filter and the link to AI screening are Olga Lehtinen’s and Matt Valente’s contribution from Day 5 Session 4.

How I use it

Personal note pending. Davide to fill.

Related frameworks

• Skills Self-Audit, the recurring practice that keeps the skills list current.
• Skills-in-Use CV Pattern, the writing structure for skills-first CV bullets.
• Capability + Outputs + Evidence, the rewrite formula for AI-screened applications.
• Capability Frontier, the AI-specific maturity scale that tells you where to focus the inflating-side investment.
• AI Use as a Skill, the four-signal framework for the AI dimension of skills-first practice.

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Notes compiled by Davide Piga. Last updated 2026-05-09.