
The capabilities, and the real limitations
How to formulate a prompt so the answer is usable
Working with the interface
Where all of this is heading
Organising tasks and plans
Generating ideas, and help with a decision
Ready prompt templates for recurring work
Examples from ordinary daily use
Business letters, reports, instructions and templates
Analysing information and files
Building your own assistant on top of your own documents
Tuning it to your role, and preparing for meetings
Generating names, slogans and scripts
Content for social media and a blog
Rewriting and adapting text to a required style
Creating images
Finding and structuring information
Summaries, lists and analytical material
Learning a new subject through dialogue
Prompts for developing a skill
Integrating it into everyday processes and apps
Building complex prompts that return precise answers
Non-standard tasks, from writing to strategy
Services already built on top of these models
Defining the requirements for the person you need
Creating an advert that attracts rather than describes
Analysing how the role performs
Improving it from candidate feedback, and comparing with competitors
Improving your own professional profile with AI
Strategies that get a candidate's attention
Developing what makes your offer distinct
Monitoring what candidates actually do
The basics of CV analysis with AI
Identifying the key skills and qualifications
Validating a CV against the requirements
Preparing interview questions directly from what you read
Sourcing techniques and strategies with AI
Practical examples that worked
Writing and improving outreach emails
Using social platforms for the search
Developing communication scripts
Handling responses and next steps
Practising negotiation and objections
Testing what actually gets replies
Optimising the way you run a search
Planning and managing the tasks
Automating what repeats every time
Tracking progress and analysing what happened
Developing questions and scenarios
Assessing a candidate's answers
Post-interview feedback
Analysing the outcome and improving the next one
Creating content that attracts the people you want
Improving visibility on the platforms candidates use
Developing and running the attraction strategy
Evaluating whether the campaign worked
Using AI alongside your other tools
Getting more out of integration
Building your own solutions
The difficulties integration actually causes
Defining the indicators that matter in hiring
Tracking and analysing them
Making decisions from the data rather than the feeling
Producing the report and the presentation
Where each model wins: context window, accuracy, long documents
The interface, the model choice, style settings and memory
Security: what you can and cannot upload about a candidate
The anatomy of a prompt, a job advert in three minutes, and five common mistakes
What a project is, and why it beats starting a new chat each time
Setting one up for a specific role and team
What to put in the instructions and what to upload
Reusing it for the next opening
From boolean search strings to AI-assisted screening
Reading a CV at volume
Scoring against your own criteria
Where the model is unreliable and you must look yourself
Writing outreach that gets a reply
Interview preparation and notes
Rejections that do not damage your name
The offer conversation
Connecting the model to the tools you already use
Working directly in the browser
The shared working mode
Automating a repeated workflow end to end
Written instructions the model follows every time
Skills, and what they replace
Assembling the parts into one working system
What to maintain and what to leave alone
The role of AI in writing SMART goals and objectives
Automating the goal-setting process itself
Generating high-quality goals and key results
The tools that do this, compared
Monitoring performance as it happens
Predictive analytics and spotting a trend early
Automating the actions that improve performance
Automatic feedback generation and productivity analysis
Creating the review form questions with AI
Preparing data so the evaluation is objective
Free and paid tools that run the whole cycle
Synthesising feedback from several sources
Optimising the one-to-one process
Automating the analysis of what the review produced
Performance insights and development recommendations
Personalised feedback and individual plans
Individualising a development plan from actual performance
Building career tracks with AI
Generating the plan rather than writing it
Where the recommendation needs human judgement
Integrating the tools into what you already run
Automating the whole performance cycle
Metrics for assessing what AI actually changed
All-in-one solutions, and when they are worth it
This course contains the use of artificial intelligence.
In a company of thirty people there is no HR department, so all three of its jobs land on you. You do them badly, and you know it.
Three gaps, and no budget to fill them
You hire four times a year, which is exactly the frequency at which nobody gets good at it. The advert is a list of duties, the CVs blur together, and the interview is a conversation you improvise. You have never run a performance review, because nobody ever showed you what one contains and the templates online assume a department that does not exist. And pay is set by feel: the last three salaries were decided by who negotiated hardest and how nervous you were about losing them, which means two people doing the same work are almost certainly on different money and one of them will find out.
What this course covers
Forty-four lessons across the three jobs. The foundation first: what these models can and cannot do, how to write a prompt that returns something usable, working with documents and files, and building an assistant on top of your own material. Then hiring, in full: defining the role, writing an advert that attracts rather than lists, comparing it to competitors, reading CVs against requirements and generating interview questions from them, sourcing and outreach that gets replies, communication scripts and objection handling, preparing the interview and assessing the answers, attracting people before they apply, and the hiring metrics worth tracking. Then the same work in a second tool, because they are not interchangeable: where each model wins, what candidate data you must never upload, projects set up per vacancy, screening at volume, outreach and offers, connectors and browser working, and instructions and skills assembled into a system. Then reviews: goals and objectives written with AI, monitoring performance and spotting a trend early, building the review form and preparing objective data, running the meeting, and development plans generated from real performance. Then pay: job architecture and grading in hours rather than months, market benchmarking across several sources, geographic differentials, the merit matrix from performance against position in range, finding who is underpaid in minutes, a payroll budget in three scenarios, personalising benefits and finding the ones nobody uses, and personal statements of total reward. Finally the rest of it: automating routine questions, analytics and forecasting, learning, implementation, data security, and a readiness checklist.
Written for a company with no HR department
There are a great many AI courses for people who work in HR. This one is for the person who does not, and never intended to — the owner or manager who ended up holding the hiring, the reviews and the pay decisions because there was nobody else. Everything here is chosen because it works without a team, without a budget and without an HR system: a chat window, a spreadsheet and about an hour. The material comes with working templates, prompt libraries and ready projects rather than theory.
Who is teaching this
I am Mike Pritula. I built the people system at Preply as it became a unicorn, and I have worked at Wargaming, iDeals and Alfa-Bank. More than 1.6 million students have enrolled in my courses across 185 countries, and over 150,000 specialists have gone through my programmes. I hold PHRi and SHRM-CP certifications and represent HRCI in more than ten countries.
What is included
Lifetime access to all 44 lessons
Active instructor support in the Q&A section
A Udemy Certificate of Completion
Working material: prompt frameworks by hiring stage, the job advert checklist, CV screening criteria, the model comparison matrix, job architecture and grading scorecards, market pricing and salary structure builders, the pay equity analyser, the budget modeller, benefits segmentation and the total reward statement builder
Two different AI tools taught on the same tasks, so you can tell which one to reach for
Where to start
Write down what you pay your last three hires and why. If any of those "why" answers is "because they asked", that is the specific problem this course solves. Enrol now and start today.