Course · AI for Productivity
Master prompting with ChatGPT, Claude, and Gemini — structured prompts, chain-of-thought, and real work automation.
Free to start — your first lesson is 5 minutes.
No credit card · 1 free lesson every day · cancel anytime
Looking for AI Prompt Engineering for your business?
Learn in your language
Your interface, explanations, and conversations with Kai adapt to your language. Learn the techniques in familiar words, then apply them to prompts in the language your work requires.
Why prompting feels inconsistent
Useful once, unreliable twice
A prompt works in one chat, then produces vague or inconsistent output when the task changes.
Prompt lists without principles
You save templates from posts and courses, but nobody explains how to adapt them to your own work.
Too much theory, too little practice
You know terms like few-shot and prompt chaining, yet struggle to turn them into a dependable workflow.
Different models, different results
The same instruction behaves differently in ChatGPT, Claude, and Gemini—and you do not know what to adjust.
Your path to mastery
A short placement skips what you already know. From there, daily five-minute lessons build the next skill you need, from clearer requests to reliable agentic workflows.
Which description sounds most like you today?
Today
You use AI occasionally, but your prompts are mostly short requests followed by several corrections.
In 1 month
You can move toward clear, specific prompts that define the task, context, constraints, and expected output.
At mastery
You can design, test, and maintain model-aware prompt systems and agentic workflows for real work.
Find your current level and practice the prompt decisions that improve real outputs.
How Kampster works
You do not repeat material you can already demonstrate. The course keeps adapting beyond each plateau until you reach the top of the proficiency scale.


Practice, not passive watching
Each lesson asks you to make concrete choices: add context, set constraints, supply examples, split workflows, or evaluate an output.
Hands-on prompt exercises
Write and revise prompts for summarization, analysis, research, content, and workflow tasks. See how each structural change affects the result.
Worked prompt comparisons
Compare weak and strong versions of the same request, including structured R-TCC-COE prompts, few-shot examples, and reasoning scaffolds.
Scenario practice with Kai
Roleplay a stakeholder, analyst, editor, or security reviewer. Kai responds in character, identifies ambiguity, and corrects you without rushing.
Quality-scoring quizzes
Spot missing context, conflicting constraints, injection risks, and weak outputs. Apply the BPQR rubric instead of relying on whether an answer merely sounds good.
Spaced-repetition review
Revisit prompt structures, model-specific tactics, and evaluation rules shortly before they fade from memory.
Custom lessons on demand
Describe a real task and create a focused lesson in about 30 seconds—such as refining a research chain, hardening a system prompt, or adapting a workflow for Gemini.
Built around your gaps
You are not pushed through the same sequence as everyone else. The Kampster engine uses your performance and goals to select what comes next.
The Kampster engine
Your demonstrated skills
Placement and lesson performance reveal whether you need prompt fundamentals, better examples, stronger evaluation, or advanced automation.
Your retention
Prompt frameworks and quality criteria return at the point you are likely to forget them, not on a fixed review calendar.
Your questions and mistakes
Kai adjusts explanations, hints, and practice when you confuse constraints, over-specify a task, or build a fragile chain.
Your real workflows
Examples can reflect the documents, decisions, research, content, or automations you actually handle.
6 modules · 56 lessons
The curriculum covers first results, R-TCC-COE prompt structure, few-shot and reasoning techniques, prompt chaining, BPQR quality scoring, GPT–Claude–Gemini optimization, injection defense, and persistent agentic workspaces. You will not receive all 56 lessons as a pile of homework. Each topic arrives when your assessed level shows you are ready for it.
First Real Results
Write a plain-language prompt that produces a useful, specific output on the first try.
Anatomy of a Prompt
Construct a fully structured R-TCC-COE prompt that consistently outperforms unstructured equivalents.
First Real Results
Write a plain-language prompt that produces a useful, specific output on the first try.
Anatomy of a Prompt
Construct a fully structured R-TCC-COE prompt that consistently outperforms unstructured equivalents.
Reasoning and Examples
Apply Few-Shot and Chain-of-Thought techniques to solve multi-step problems accurately.
Prompt Chaining and Quality
Decompose a complex workflow into a reliable prompt chain and score it against the BPQR rubric.
Reasoning and Examples
Apply Few-Shot and Chain-of-Thought techniques to solve multi-step problems accurately.
Prompt Chaining and Quality
Decompose a complex workflow into a reliable prompt chain and score it against the BPQR rubric.
Model-Specific Optimization
Engineer prompts tailored to GPT, Claude, and Gemini strengths while defending against injection attacks.
Agentic Automation
Build a persistent agentic workspace that autonomously executes a multi-step research or automation workflow.
Model-Specific Optimization
Engineer prompts tailored to GPT, Claude, and Gemini strengths while defending against injection attacks.
Agentic Automation
Build a persistent agentic workspace that autonomously executes a multi-step research or automation workflow.
Your work becomes the lesson
In about 30 seconds, turn a specific situation into a custom lesson. Practice prompts such as “Improve my customer research prompt,” “Build a reliable report-writing chain,” “Adapt this workflow for Claude,” “Test my system prompt for injection,” or “Design an agent for weekly market research.” Still stuck? Ask Kai and keep refining it.
Whatever’s coming up — the lesson exists before your coffee’s ready.
Questions, answered
No. You begin with plain-language prompting and progress from there. Advanced lessons may involve agentic workflows, but the course introduces each concept through guided examples and practice.
The roughly two-minute placement checks your current capability. Anything you demonstrably know is skipped, so you can begin closer to prompt chaining, model optimization, security, or automation.
Yes. You learn shared prompting principles and how to adapt prompts to the strengths and behavior of GPT, Claude, and Gemini. You also practice evaluating outputs rather than assuming one model is always best.
Five minutes is enough to complete a typical interactive lesson and maintain a consistent habit. Complex skills still require repeated practice over time, so the course continues adapting until you demonstrate mastery.
Yes. Kai can answer questions, correct prompts kindly, and roleplay relevant scenarios. You can also create a custom lesson for a specific real-life task in about 30 seconds.
It reflects skills you have demonstrated through assessment. It is verifiable and shareable, and it is based on capability rather than videos watched or time spent in the course.
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AI Prompt Engineering leaderboard
The live leaderboard recognizes learners advancing furthest through assessed prompt-engineering skills—from structured prompts to reliable agentic workflows.
Olena
100 / 100
Marina
100 / 100
Сергій
100 / 100
Take the short placement, skip what you know, and start with the next skill that will improve your work.
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