Prompt engineering training: the same tool, ten times better results
Full day (about 7 hours) Up to 10 people On site in Istanbul or online 49.900 TL + VAT
Prompt engineering
What is this program?
Prompt engineering training is a full-day, hands-on program in which teams learn on their own work how to get consistent, high-quality results from AI tools: describing the task correctly, giving context and examples, defining the output format, building multi-step flows and evaluating the output. The program ends with a shared prompt library for the team's recurring tasks.
Of two people using the same tool, one gets a usable result and the other gets rubbish. The difference is not the tool but the description. The rise of searches such as "prompt training price" and "what is prompt training" shows this is starting to be understood. Prompt engineering is not magic. It is a learnable discipline of description.
The program is based on the seven-part pattern I use in my free prompt library: identity, task, what you need to know, method, output, self-check, rules. The team applies this pattern to its own work and leaves at the end of the day with a tested prompt library for every recurring task.
Who is it for?
Teams already using AI
Those getting inconsistent or mediocre results from the tool and wanting better.
Departments that want to set a standard
Teams that want shared templates for tasks everyone currently asks in a different way.
Teams preparing for automation
Those who will later turn a prompt into an agent or an automation.
Program flow: six modules
Talking takes at most a fifth of the day. The rest is hands-on production on your own files, each module ending with a piece of real work.
Why a prompt does not work
The five causes of a bad result: no context, no role, no format, no example, no constraints. Diagnosis through the team's own failed prompts.
The seven-part prompt pattern
Identity, task, what you need to know, method, output, self-check, rules. Each participant converts a task from their own work into this pattern.
Giving context and examples
Feeding the tool with company documents, tone examples and past output. Few-shot teaching, system instructions, project context.
Multi-step flows
Breaking a large task into steps, each step's output becoming the next step's input, checkpoints.
Evaluation and improvement
Trying the same prompt in different models, scoring the output, improving the prompt through iteration.
The team prompt library
A tested, versioned and shared library for recurring tasks. The rule for who updates what.
Real work scenarios
The kind of tasks the day is built around. Yours replace these after the discovery call.
A mediocre email draft
Fixing an email prompt the team constantly corrects so that it gives the right result in one pass.
A report summary
Locking a summary that arrives in a different format every time into a fixed format.
The company tone
A content prompt fed with tone examples that produces output resembling the brand.
A five-step analysis
Chaining the steps of data collection, cleaning, analysis, interpretation and presentation.
Model comparison
Trying the same prompt in ChatGPT, Claude and Gemini and choosing the most suitable tool.
A department library
Building a tested prompt set for a department's 15 most frequent tasks.
Tools used
Skills come before tools. The current model comparison with prices is on the AI models page.
What the team leaves with
- The seven-part prompt pattern applied to the team's own work
- A method for giving context and examples
- The skill of building multi-step flows
- An output evaluation and improvement loop
- A tested team prompt library for recurring tasks
Format and what is included
- Discovery call: your industry, the team's daily work and the three targets of the day
- Content built on your own files, not a generic slide deck
- Full day (about 7 hours) hands-on, on site in Istanbul or online
- Team playbook with everything built during the day
- 30 days of Q&A support after the training
- Certificate of participation
Scopes beyond the standard package (more than 10 people, several locations, half-day or multi-day formats, integration work) are quoted separately.
The same standard package for every program.
How it works
15-minute call
We talk about the team, the work and whether this program fits. No commitment.
Discovery and preparation
A short session with the team lead. The day is built on your real tasks.
Training day
Everyone on their own laptop, on their own work, the whole day.
30 days of support
Questions that come up while actually using AI at work get answered.
Your trainer
Sefa Aydın
AI trainer and consultant. Years of producing design, advertising and software for the Türkiye projects of world-renowned luxury brands, founder of the agency Rebel Co. Group. I use these tools on real client work every day, and I teach what I use.
About me →Frequently asked questions
What is prompt engineering training?
It is the discipline of describing a task correctly to get consistent, high-quality results from AI tools: role, context, format, examples, constraints and evaluation. This program teaches this discipline hands-on, on the team's own work. For a conceptual introduction, see the article on what prompt engineering is.
Who can take prompt training?
Anyone already using AI. No technical knowledge is needed. The program gives the best results in teams that have been using ChatGPT or Claude for at least a few weeks. For teams that have never used them, the literacy training comes first.
How much does prompt engineering training cost?
The standard package is a full day for up to 10 people at 49,900 TL plus VAT. The discovery call, content preparation based on the team's work, the team prompt library and 30 days of Q&A support are included. Multiple departments are scoped by proposal.
Why is training needed when there is a free prompt library?
The library offers 70 ready prompts and is open to everyone. The training teaches the team to write, test and improve prompts for its own work. The library is the fish, the training is fishing.
Is prompt engineering still relevant now that models are smarter?
As models got smarter, the importance of the prompt dropped for simple tasks and rose for complex, recurring ones. In agent tasks the task description directly determines the result. The program is updated for the 2026 models.
Can the prompts be turned into automation after the training?
Yes, the program lays exactly that groundwork. A tested prompt is the starting point for handing over a process in the AI agents program.
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Guides on this topic
Last updated: 14 September 2026
Request a proposal for your team
Tell me the team size and what you want to solve. I reply the same day.