Sefism.Layoffs and AI

Tauseef Fayyaz

A to Z

Glossary

Every concept in this sheet, plus the smaller terms it uses. Select a concept to open its card.

Adjacent skills: Growing skills that sit next to what you already know, such as AI features for a backend developer or data pipelines for an analyst.
AI adoption at work: Using AI tools in your daily work as a normal part of how you build, test and review.
AI-washing: Naming AI as the reason for layoffs that are mainly about cost, over-hiring or weak sales, because it sounds better to investors.

Brag document: A running list of what you did, why it mattered and the evidence, updated every week.
Bridge work: Short contract or freelance work taken during a long search to pay bills and keep skills current.
Building with AI: Engineering that puts models into products: model calls, retrieval over company data, agents that call tools, and the cost, security and reliability around them.

Checking a company's stability: Researching whether the next employer is likely to cut soon: results, funding, recent layoffs and how close your team is to revenue.
Collective consultation: In the UK and EU, a required period of consultation with employee representatives before large redundancies.
Company AI policy: Your employer's rules on which AI tools you may use and what data may go into them.
Company warning signs: Signals that often come before cuts: missed results, a failed funding round, new leaders brought in to simplify, reorganisations, cancelled projects and talk of efficiency.
Cost centre and profit centre: A profit centre earns money, such as a product customers pay for.
Cutting staff to fund AI: Reducing headcount in some areas to pay for heavy spending on AI data centres, chips and teams.

Deskilling: Losing a skill because a tool always does it for you.
Domain knowledge: Understanding the business your code serves: how money flows, what customers need and which rules apply.
Doomscrolling: Reading bad news for long periods, often on social media, without acting on any of it.

Emergency fund: Savings kept only for a loss of income or a real emergency, in an account you can reach within days.
Evals: Tests that check whether an AI feature gives good answers, using a set of example inputs and a way to score the outputs.
Evidence on AI productivity: Studies that measure how much AI tools really change developer speed, as opposed to how fast people feel.
Experience and relieving letters: Letters common in Pakistan and India confirming your dates, title and that you have been released from your duties.
Exposure audit: An honest score of your role on four things: how close your work is to revenue, how much of your week AI can do, how replaceable you are, and whether your impact is written down.

Final settlement: Everything owed when you leave apart from severance: salary to the last day, notice pay, unused leave where paid out, earned bonus and expenses.
Fixed costs: Bills that arrive whether you earn or not: rent, instalments, loans, subscriptions.
Flattening: Removing layers of management so each manager has more reports, and some managers become individual contributors again.

Global capability centre: A company's own office in another country, often India, that does engineering, operations or support for the global business.
Gratuity and provident fund: In Pakistan and India, a lump sum based on years of service, and a retirement fund built from employee and employer contributions.

Hiring freeze: A stop on hiring, often including backfills, which means people who leave are not replaced.
How layoff lists are made: Most layoffs go from a cost target, to products, teams and locations, and only then to individual people, using reviews, cost and skills.

Job scams: Fake job offers that try to take money or personal data, often aimed at people who have just been laid off.
Job search pipeline: A tracker of every opportunity and its stage: researched, applied, referred, recruiter call, interviews, offer.
Judgement skills: Skills that decide whether code and designs are right: critical review, debugging across systems, performance reasoning and choosing what not to build.

Layoff rumours: Unconfirmed talk of cuts, in anonymous forums, group chats or the office.
Layoff trackers: Sites and reports that count announced layoffs, such as layoffs.fyi for tech companies and Challenger, Gray and Christmas for all US employers.
Learning system: A small, regular routine for learning: daily use, a weekly read, a monthly experiment, a quarterly deeper project.

Master CV: A long version of your CV with every achievement, kept current, from which you cut a short version for each application.

Non-compete and non-solicit: Terms that limit working for competitors, approaching clients or colleagues, or criticising the company after you leave.

Open to Work: A LinkedIn setting that tells recruiters, or everyone, that you are looking, with an optional green photo frame.
Option exercise window: The time you have after leaving to buy vested stock options, often 90 days.
Outcomes over tickets: Taking responsibility for the result the business wanted, such as fewer failed payments, not just closing the ticket that asked for a change.
Outside work clause: Contract terms that limit work outside your job or give your employer ownership of what you build.

Performance improvement plan: A formal document listing what must improve, by when and how it will be measured.
Performance signals: The signs of how your work is rated: the kind of work you are given, how specific feedback is, whether you are included in planning.
Personal employment documents: Documents about you, not the company: contract, offer letter, payslips, appraisal and promotion letters, equity grants, tax and visa papers.
Portable proof of work: Evidence of your skills that lives outside your employer: public projects, talks, write-ups, open source contributions.
Proof of AI skill: Evidence that you use AI well: a measured improvement at work, a shared setup, or a small project with an honest evaluation.

Reference: A person, usually a former manager or senior colleague, who confirms your work to a future employer.
Referral: An employee recommending you for a role at their company, usually through an internal system.
Release of claims: A clause in a severance agreement where you give up the right to bring legal claims against the employer.
Reputation: What colleagues say about you when you are not there, often one sentence such as "always delivers" or "hard to work with".
Revenue-critical work: Work that earns money, keeps paying customers happy, or is required by law, such as billing, the core product, security and compliance.
Runway: How many months you can keep going on your savings and other money before it runs out.

Search routine: Fixed working hours for the search, plus sleep, exercise, time off and people to talk to.
Second income stream: A small extra income from freelancing, a product, teaching or content, alongside your job.
Severance: Money an employer pays when it ends your job, often in exchange for signing an agreement.
Skill gap: The skills that job ads for your target role ask for most often and that you cannot yet prove.
Skip-level meeting: A one-on-one with your manager's manager, often once a quarter.
Soft layoff: Pushing people to leave without a formal layoff, for example through strict return-to-office rules, forced relocation or harsher reviews.
Standing Orders (Pakistan): Pakistan's main employment rules for covered workers: written termination, one month's notice or pay instead for permanent staff, gratuity, and last in, first out within a category.
Substitute versus complement: AI substitutes for work when it can do the task instead of a person; it complements work when it makes a person faster or better at a task that still needs them.

T-shaped engineer: An engineer with deep skill in one area and working knowledge of several around it.
Task exposure: How much of a job is made of tasks that AI tools can already do well, such as boilerplate code, first drafts of tests and simple fixes.
Team and personal signals: Quieter signs closer to you: a project losing its sponsor, a vague roadmap, work moved elsewhere, being left out of planning, or sudden requests for handover notes.
The bench: At services companies, the time an employee spends between client projects, still paid but not billed to a client.
The junior squeeze: The drop in hiring of early-career engineers since 2022, linked in research to AI doing more entry-level tasks.
The layoff meeting: The short meeting, often with HR, where you are told your job is ending.

Unemployment benefits: Government payments to people who lost their job, available in the US, UK and much of Europe under conditions.

Visa grace period: The limited time a work visa holder has after a job ends to find a new sponsor, change status or leave.
Visible impact: Impact that is written down where decision makers can find it: updates, write-ups, review notes and names on launches.

Warm network: People you have stayed in touch with and who would answer your message, as opposed to connections you never speak to.
WARN Act: A US law requiring employers with 100 or more employees to give 60 days' written notice of a plant closing or mass layoff.

Yearly market check: Doing a real or practice interview and checking pay data once a year, even when you are not looking.
Your layoff story: Two calm, factual sentences explaining the layoff, followed by what you did next and what you want.