Personal branding · Technology
Every profile in your field now says AI, so yours says nothing at all.
A hiring manager opens fifty profiles that all say AI, and the models you built belong to your employer.
Scope, fee, reporting and term are agreed in writing after we have read your brief and spoken to you.

In one paragraph
A hiring manager opens fifty profiles that all say AI, and the models you built belong to your employer. Personal branding here means proving judgement rather than tools. GullySales interviews you, writes your presence from what you said, and leaves your employer's data out of it.
Also written for
Data scientist, Data analyst, AI engineer, Machine learning engineer.
Where this sits
For data scientists and AI specialists
Where it usually goes wrong, and what we would do.
“The word has stopped carrying weight”
A headline that says AI engineer tells a hiring manager only that you updated it recently. What separates two candidates is one problem described from beginning to end, including the six weeks when the data turned out to be wrong.
“Certificates prove attendance”
A column of course badges is not evidence of anything. The business head who has to trust your model wants to know what you did on the day the result disagreed with what the sales team believed.
“Your training data is not yours”
The dataset, the features and usually the model belong to your employer or to their customer. Publishing a few sample rows to illustrate a point can breach a contract, and where personal data is involved it becomes a much larger problem.
“Nobody writes about the interesting failures”
Drift after launch, the pipeline that broke quietly for a month, the project that should have been a SQL query. Writing about those is how a sponsor decides you are safe to fund again.
What we do
What we deliver for data scientists and AI specialists.
Every deliverable, what it covers for you, and the result it is there to produce. Nothing here is an extra.
A profile about problems rather than tools
Your bio rewritten around the questions you have answered and the decisions that followed them, with the tool list moved down to where it belongs.
Result: A hiring manager reads problems you solved, not another list of the same stack. Before we start we note searches for your name, profile views and invitations received, so you can see what moves.
A conversation on the project you would do differently
The model you would rebuild now, or the result you had to explain three times before an operations team believed it. We write from that call, and the schedule is agreed in writing. We will not write figures, client names or code from your employer's systems, and we will not invent a result you did not have.
Result: Drafts in your words, out of a call taken between stand-ups.
One case study you are allowed to publish
The problem, the approach and the result described in shape rather than in figures, rebuilt on public or synthetic data where the original cannot leave the company. For example, an ML engineer could rewrite a profile around a drift incident: a demand forecast that slowly stopped matching the warehouse, how it was spotted, and what was changed.
Result: Something to put in front of a panel that is not a screenshot of a notebook.
Writing for the people who fund models
Plain pieces for a finance head or an operations head on what a model can and cannot promise, and what it costs to keep running month after month. Sometimes the honest answer is a rule and no model at all.
Result: Pieces your sponsors can read before your next proposal, setting out what a model can and cannot promise.
The peer side of your name
A public repository, notebooks and answers in the places where your field argues, all under one identity instead of three.
Result: One identity that collaborators and reviewers can find, with your repository, notebooks and answers linked from it.
How the result is measured
- Enquiries that name you or came through your profile
- Searches for your name, from Search Console
- Profile views and connection requests from your industry
- Speaking invitations, press enquiries and podcast requests
- Posts published against posts planned, and what held up the rest
Recorded as a baseline before work starts, so every later report has an honest comparison.
How it works
How the work runs for data scientists and AI specialists
The work itself, in order. How an engagement starts, from your brief to a written scope, is set out on our method page.
- 1
Work out whether this is even your bottleneck
The first conversation covers how enquiries reach you today. If the company's own site is the weaker link, that comes first, and we say so.
- 2
Search your own name with you
We look at what a buyer sees today: every profile, old listing and photograph. Some of it you will want taken down, and some of it only you can take down.
- 3
Agree what you will and will not say
The subjects you know cold, the ones that belong to your clients, and the lines your regulator or association draws. Written down before anything is published.
- 4
Rebuild the profiles
The bio page, LinkedIn and the directories that matter in your field, done once and done properly.
- 5
The routine
Interview, drafts, your approval, publication. The interview is the only part that needs you, and it is the part that cannot be skipped.
- 6
Hand it over
The subject list, the drafting notes and the calendar are yours. If you would rather keep it running yourself, that is a fair outcome.
Before you hire anyone
The first thing to do yourself.
It costs nothing, and it shows what a buyer sees before they ever call you.
- Search your own name and your practice or business name in a private browser window, and list the first ten results.
- Open your profile on each major platform and check that the name, photo, description and contact details agree.
- Ask two people who recently chose you what they looked up first, and write down their answers.
Judge any provider
What to ask any agency or ghost-writer.
Useful whoever you choose, including us.
- Who writes my words, and do I approve everything before it goes out?
- Which of my own details and claims will you need to check with me before publishing?
- What will you not write because of the rules my profession follows?
- Whose account do the profiles and the content sit in, and what happens to them if we stop?
- What do you count as a result, and what will you not promise?
Where this fits
Three pieces of sales work, in this order.
GullySales builds every engagement from three pieces of sales work. This page is not one of them, but the same three steps apply to the business behind it.
Step 1
Sales audit
Find where deals are being lost and what to fix first.
Start here if you cannot say where orders are lost.
Step 2
Sales process design
One written way to sell, from first enquiry to repeat order.
Start here if every salesperson sells differently.
Step 3
Sales management
A target, a review routine and someone who owns the number.
Start here if the team has targets and no routine.
FAQ
Questions owners ask before they call.
Not here? More answers, or ask on WhatsApp.
Will this get me a remote or overseas role?
What about the models I built at work?
Can I not just use an AI writing tool for this?
How much does it cost?
How long is the contract?
How soon will we see results?
Who will actually do the work?
What do you need from us?
What if we are not happy with the work?
Technology
Personal branding for the rest of the technology.
Or start from personal branding.
Your next practical step
Tell us what you are trying to grow, and we will read it before we call.
Eight short steps, mostly taps. Skip anything you would rather answer on the call.