
• The difference between AI systems, prompts and agents
• Agent components: LLM, triggers, memory, actions
• Platforms to build on (Mindset AI, Flowise, ChatGPT GPTs, Borderless, Bardeen)
• Case studies: how an agent differs from a simple chatbot
• Practice: build a simple agent in GPTs
Tools in this lecture
Ready to use on the slides (5)
Services and apps shown in this lecture (1)
• Examples: HireBorderless, Metaview AI, Wade & Wendy
• Use cases: screening, responding to applicants, writing offers
• Limitations and risks (bias, context)
• Integration with ATS (Lever, Greenhouse)
• Practice: test an agent on a fake candidate
Tools in this lecture
Ready to use on the slides (3)
Services and apps shown in this lecture (1)
• Examples: own GPT helpers, Mindset agent for onboarding
• Use cases: FAQs, tasks to newbies, onboarding quests
• Integration with Notion, Trello, Slack
• Practice: create an agent for adaptation based on ChatGPT
Tools in this lecture
Ready to use on the slides (4)
Services and apps shown in this lecture (3)
• Examples: Docebo AI Coach, LearningStudio AI, Cerego
• What they can do: customized tracks, knowledge validation, lesson generation
• The difference between an AI Coach and an LXP
• Practice: select and test an AI Coach
Tools in this lecture
Ready to use on the slides (2)
Services and apps shown in this lecture (3)
• Examples: Mesh, Peoplebox, Effy AI, Marissa AI
• Use cases: 1:1 analysis, goal tracking, coaching
• Applications in OKR, review, development plans
• Practice: do a review with an AI agent
Tools in this lecture
Ready to use on the slides (4)
Services and apps shown in this lecture (2)
• Examples: Leena AI, Talla, HR Bot for MS Teams
• Use cases: chat support, feedback gathering, policy clarification
• AI as an “emotional assistant”
• Practice: implement an agent in Slack/Telegram
Tools in this lecture
Ready to use on the slides (1)
Tools in this lecture
Services and apps shown in this lecture (6)
Models and methods explained (1)
Tools in this lecture
Ready to use on the slides (3)
Services and apps shown in this lecture (15)
Tools in this lecture
Ready to use on the slides (3)
Services and apps shown in this lecture (11)
Tools in this lecture
Ready to use on the slides (12)
Services and apps shown in this lecture (5)
Tools in this lecture
Ready to use on the slides (12)
Services and apps shown in this lecture (6)
Tools in this lecture
Ready to use on the slides (1)
Services and apps shown in this lecture (3)
Tools in this lecture
Services and apps shown in this lecture (4)
Models and methods explained (2)
Tools in this lecture
Services and apps shown in this lecture (1)
Models and methods explained (2)
Tools in this lecture
Ready to use on the slides (1)
Services and apps shown in this lecture (2)
Tools in this lecture
Ready to use on the slides (9)
Services and apps shown in this lecture (10)
Models and methods explained (1)
Tools in this lecture
Ready to use on the slides (8)
Services and apps shown in this lecture (4)
Tools in this lecture
Ready to use on the slides (3)
Services and apps shown in this lecture (2)
Tools in this lecture
Ready to use on the slides (4)
Services and apps shown in this lecture (3)
Tools in this lecture
Ready to use on the slides (3)
Services and apps shown in this lecture (6)
Tools in this lecture
Ready to use on the slides (1)
Services and apps shown in this lecture (6)
Tools in this lecture
Ready to use on the slides (13)
Services and apps shown in this lecture (1)
Tools in this lecture
Ready to use on the slides (12)
Services and apps shown in this lecture (3)
Models and methods explained (2)
Tools in this lecture
Ready to use on the slides (13)
Services and apps shown in this lecture (2)
Models and methods explained (2)
Tools in this lecture
Ready to use on the slides (2)
Services and apps shown in this lecture (2)
Tools in this lecture
Ready to use on the slides (1)
Services and apps shown in this lecture (1)
Tools in this lecture
Ready to use on the slides (9)
Services and apps shown in this lecture (1)
Models and methods explained (1)
Tools in this lecture
Ready to use on the slides (1)
Services and apps shown in this lecture (1)
Tools in this lecture
Ready to use on the slides (8)
Tools in this lecture
Ready to use on the slides (1)
Services and apps shown in this lecture (1)
• Examples: Jatana, Vibe AI, CrystalKnows
• Predicting burnout, employee care, manager tips
• How to train on internal data (risks and warnings)
• Practice: model a retention forecast
Tools in this lecture
Ready to use on the slides (2)
Services and apps shown in this lecture (1)
Models and methods explained (1)
• Platform selection: ChatGPT GPTs, Mindset AI, Flowise
• Agent architecture: target, memory, actions, APIs
• Building a custom HR agent for one HR task
• Final project: create your personal HR-agent
Tools in this lecture
Ready to use on the slides (1)
Services and apps shown in this lecture (1)
Models and methods explained (1)
This course contains the use of artificial intelligence.
184 tools for AI agents in HR in one course: 114 ready-to-use AI prompts, templates, question lists, procedures and checklists, 59 services and apps shown on screen, and 11 models and methods.
Open a lecture, take the prompt or the procedure, set up the agent.
Why HR stays busy with routine
Candidates wait for an answer. New hires ask the same ten questions. Managers skip one-to-one meetings because preparation takes time. Most of this work repeats every week, and a prompt typed into a chat each time does not remove it. An agent does: it has a goal, a memory, a set of actions and instructions, and it does the same task the same way every time.
What changes after this course
You can describe an agent without a developer: what it is for, what it remembers, what it does and what it connects to. You build a GPT for candidate screening, an onboarding assistant, a helper for one-to-one meetings and a first retention prototype. You have ready prompts and documents for the rest of the employee lifecycle and know which services already do the job.
What is inside: 184 tools, counted lecture by lecture
You do not have to take this number on trust. Open any lecture and read its description: every tool inside is listed there by name.
Where the tools are
What this course is not
It is not a programming course: there is no Python and no API code. The agents are built in ChatGPT with instructions, knowledge files and ready prompts.
Who is teaching
I am Mike, the #1 HR instructor on Udemy, with 1,800,000+ course enrollments from 170,000 students, and the author of about 200 books on Amazon. I built the people system at Preply as it became a unicorn and worked at Wargaming, iDeals and Alfa-Bank across 20 years in HR. I hold PHRi, SHRM-CP and HCI sHRBP certifications and represent HRCI in Eastern Europe.
I once helped a startup that was developing a chatbot for employees to describe its functions. Back then nobody called them agents. I described about 50 of them: what each one does, what it relates to and how it should talk to the user. The developers then built everything from my description. More recently I built a GPT for PHRi exam preparation: it takes a question from its knowledge base, offers answer options, explains why the answer is right or wrong, and gives a simpler explanation when a student asks for one.
How to use the course
Start with the first section and build one agent with the GPT agent creation procedure. Then go to the function you work in: recruiting, onboarding, learning, performance or retention. Use the two large sections as a library: open the lecture for your task and take the prompts and documents. Section and lecture titles show how many tools are inside, and each lecture description lists them by name.
What is included
Where to start
Take one question that new hires ask you every month. Open the first lecture, follow the GPT agent creation procedure and give the agent your onboarding document. Enrol now and start your first lesson today.