How to use AI for your job search in 2026

How to use AI for your job search in 2026

I've run a lot of 1:1 sessions lately where the brief is the same: "I'm job hunting. Help me use AI properly." Not "tell me about AI." Not "show me ChatGPT." Actually help me land a role.

So we build a stack together. Five pieces. By the end of the hour, the person has a working system that does most of the grunt work of a job search for them. The bit that used to eat entire weekends.

This is what we build. If you're applying for jobs right now and you're still copy-pasting your CV into ChatGPT and asking it to "make it better", you're leaving the best tools on the table.

Start with a prompt that describes the role, not the CV

Most people open ChatGPT, paste their CV, and ask it to help with their job search. That's backwards.

The first thing we do is write a prompt that describes the job you actually want. Role title. Seniority. Salary band. Location or remote. Industry filters. Must-haves and deal-breakers. Companies you'd never work for. Companies you'd move for.

Spend 15 minutes on this. It's the single highest-impact thing you can do, because every other step in the stack takes this prompt as its input. Garbage in, garbage out. A vague prompt gives you a vague shortlist.

A prompting hack I use in sessions: write me a prompt. Literally type "Write me a prompt to use with an AI agent to search for jobs that fit this description" and paste in your rough thoughts. The AI will structure it better than you will on your first try. Then you edit.

Here's the shape I end up with most of the time. Steal it, fill in the brackets.

I'm looking for a new role. Here's the brief:

Role title: [e.g. Senior Product Manager]
Seniority: [junior / mid / senior / director]
Salary band: [£X to £Y]
Location: [London / remote / hybrid, days per week]
Industry: [fintech, b2b saas, healthtech, etc.]
Must-haves: [list 3 to 5]
Deal-breakers: [list 3 to 5]
Companies I'd love to work for: [list]
Companies I'd never work for: [list]
A bit about me: [2 to 3 lines of relevant experience]

Whenever I ask you to do something with this brief, treat it as the context.

Save this somewhere. A note, a doc, anywhere you can copy it quickly. You're going to reuse it every time you run the stack.

Hand the search to a browser agent

This is where it stops being a chat and starts being a tool.

Most AI models can write about jobs. A few can actually go and find them. I'm talking about browser agents. AI that drives a web browser on your machine. ChatGPT Atlas and the ChatGPT Agent mode will do it. Claude for Chrome will do it. They open tabs, run searches on LinkedIn and Indeed, read the results, and come back with a shortlist.

In a recent session we did the following. Gave the agent the job search prompt, then followed it with this:

Using my job search brief (above), open LinkedIn and Indeed and search for roles posted in the last 14 days that match it.

Return a list of 15 roles with:
- Job title and company
- Location and remote policy
- Salary if listed
- One line on why it fits the brief
- Direct link to the posting

Sort by best fit first. Skip anything older than 14 days or that doesn't match my must-haves. If you can't find 15, tell me what you tried and where you got stuck.

Then we hit go and made a cup of tea.

Ten minutes later, we had a formatted shortlist. Not perfect — some of the matches were loose, and a few were postings from three months ago. But it had surfaced four roles the person hadn't seen in their own manual search. One of those felt strong enough to chase the same evening.

The shift here is that you stop being the search engine. You write the brief once, then you get the output as a document you can skim. You can do this every morning before coffee.

One thing worth being clear about. Don't leave a browser agent running unsupervised on the open web. The risk isn't logins or pop-ups — modern browser agents handle those fine. The risk is prompt injection. A page can contain hidden instructions that the agent reads as commands. Treat it like a junior assistant you trust with a defined task, not an autonomous worker you let loose on your machine. Watch the tab while it runs, especially the first few times. That's the only real caveat.

Audit your LinkedIn and Indeed profile the way a recruiter sees it

The other job of a browser agent is to look at you.

Recruiters and in-house talent teams use LinkedIn and Indeed search in very specific ways. They filter by title, by keyword, by location, by years of experience. If your profile doesn't match the filters they're running, you don't exist to them. It doesn't matter how good your CV is — they never get that far.

So in the session we run a profile audit. Here's the prompt:

Open my LinkedIn profile at [URL].

Pretend you're a recruiter searching for [target role title] in [location]. You've got 100 profiles to get through today.

Answer these:
1. Would I come up in the searches you'd typically run for this role?
2. What's your first impression from the headline and the first 300 words?
3. What reads like filler?
4. What's missing that a recruiter would expect to see for this role?
5. Give me a prioritised list of edits that would take under 2 hours total.

Be blunt. Don't soften the feedback.

Same prompt, Indeed URL, run it again. The two platforms rank profiles differently, so the feedback diverges in useful ways.

Claude for Chrome is good for this because it genuinely reads the page the way a human would. It sees the layout, the order of things, the whitespace. Then it writes you a critique.

The critiques are often brutal in a useful way. "Your headline says 'passionate professional'. That's invisible to search. Your most recent role uses three lines of jargon before naming what you actually did. Your skills section has 50 tags, most of which dilute the strong ones." That kind of thing.

You end up with a checklist of profile edits. None of them take more than 20 minutes to make. All of them compound.

Build a CV and cover letter workflow with Gems or Projects

This is the part that usually saves people the most time.

The old way: you see a job ad, you open your CV, you read the ad, you try to remember which bits of your CV to emphasise, you rewrite the profile summary, you half-write a cover letter, you second-guess yourself, you move on. The whole thing takes 45 minutes per application. You apply to five a week and you're exhausted.

The new way is a workflow that sits inside Gemini Gems, ChatGPT Projects, or Claude Projects. Pick one. They all work. I usually use Gems with clients because it's free with a Google account, and Gemini is strong at instruction-following.

Quick aside on what these are, in case you've never used one. A Gem or a Project is a saved bundle of context — a system prompt and a set of reference files — that travels across every chat you start inside it. Normal chat threads are amnesiac: when you close one, everything you taught the model is gone. A Gem or Project is the opposite. You set it up once with your master CV, your voice guide, and your instructions, and every new thread inside it already knows all of that. You just paste the job description and go. That's the whole reason this part of the stack works — you stop re-explaining yourself every time.

Here's the system prompt I use inside the Gem or Project:

You are a CV and cover letter writer for [your name].

I'll paste you a job description. You return two things:

1. A tailored one-page CV, based on the master CV below, with bullets rewritten to emphasise the experience most relevant to this specific role.
2. A tailored cover letter, max 300 words, in the voice described in the voice guide below.

Rules:
- Never invent experience I don't have. If you would normally invent a detail (a metric, a company, a project) to fill a gap, flag it as [ADD DETAIL] instead.
- No corporate buzzwords. Follow the voice guide strictly.
- Make the cover letter specific to the company and role. If the role mentions a product, reference it. If the company has a public mission, reference it. Generic filler fails this brief.
- Don't open the cover letter with "I'm excited to apply". Ever.

Master CV:
[paste full master CV here]

Voice guide:
[paste voice guide here, see step 5]

Example cover letters I'm happy with:
[paste 2 to 3 examples here]

That "flag instead of invent" line matters. LLMs will hallucinate achievements if you don't stop them. Telling them to flag instead of invent is the difference between a CV you can send and a CV you'd be embarrassed by.

Once the Gem is set up, the workflow is: paste job description, get tailored CV and cover letter, edit lightly, send. The 45 minutes becomes five.

Train the AI to write in your voice

This is the last piece, and it's the one most people skip.

If you use the CV and cover letter workflow without a voice guide, everything you send sounds like AI. You can feel it. Hiring managers can feel it. They read a hundred of these a week. They know the pattern.

So before we wire up the workflow in step four, we build a voice guide. Not a corporate one. A personal one that describes how you actually write.

The process is short. We take three or four pieces of writing the person already has. An old cover letter they liked, a LinkedIn post, a good email to a boss, a paragraph from a personal essay. Then we run this prompt:

I'm going to paste 3 to 4 pieces of my own writing below. Analyse them and produce a one-page voice guide I can give to another AI so it writes like me.

The guide should cover:
- Average sentence length and rhythm
- Phrases I use often
- Phrases or structures I never use
- Favourite words and words I avoid
- How I tend to open a piece
- How I handle transitions between ideas
- Level of formality
- Anything else distinctive

Don't flatter me. Be specific and honest. If my writing has a quirk, name it.

Writing samples:
[paste 3 to 4 pieces here]

The output is usually a one-page doc with rules like "short sentences, avoids corporate buzzwords, uses contractions, prefers concrete examples over general claims, never opens with 'I'm excited to'". That doc goes into the Gem.

The best bit: the voice guide improves every other piece of the stack too. You can use it when you're writing the prompt in step one, when you ask Claude for Chrome to audit your profile, when you reply to recruiter messages. One artefact, used everywhere.

And in a job search where half the applications are written by an AI that didn't get a voice guide, sounding like a human is a real edge.

Putting it together

The full stack looks like this:

1. A job search prompt you've written once, saved, and reuse
2. A browser agent that brings you a shortlist every morning
3. A profile audit from that same browser agent, run every couple of weeks
4. A Gem or Project that tailors your CV and cover letter to any job description in five minutes
5. A voice guide that trains every AI you use to sound like you

Set up properly, this takes one 60-minute session. After that, you run it yourself, every day, at about 10% of the effort a manual job search takes. None of it replaces the human bit — the conversations, the follow-ups, the networking. It just frees up the time to do that bit well.

Want the stack built with you?

The job search system is one of the five fixed tasks in the Power Hour. £199, 60 minutes, on Zoom. We set it up together using your real CV, your real target roles, your voice — and you leave with it running on your machine. That's the right call if you've read this post and you want this exact stack.

If you don't know yet what you want AI to do for you — career, business, side project, no clear brief — that's a different conversation. The 90-minute Deep-Dive at £699 is the session where we figure that out together. Different product, different purpose. Don't book it just to get more time on the job search stack — the Power Hour already does the whole stack.

Not sure which one fits? Message me. I'll tell you honestly.

If you're weighing up a course instead, I wrote about the difference. Short version: courses teach theory. This builds your actual system.