Loading
0%
Workshop · Hands-on · Team Enablement
AdwebX delivers hands-on training to your teams on prompt engineering, AI tools, and safe usage. We run department-specific workshops and build an internal AI usage policy.
AI's value emerges only when your team uses it confidently. We accelerate adoption with hands-on workshops, department-specific use cases, and a compliant internal usage policy.
Every month you wait, the gap between you and competitors widens.
An AI-fluent employee saves 2-4 hours per day compared to an untrained peer — the competitive gap compounds fast.
Untrained AI use generates rework from bad prompts; the time 'saved' is eaten by corrections.
If your team doesn't learn AI integration now, closing the skills gap 12 months from now costs far more.
Real business outcomes with industry-standard tools.
This is a problem many businesses are living with but have not yet articulated. The company bought ChatGPT or Copilot subscriptions; the team is trying things, but results are inconsistent. Some people produce impressive outputs; others cannot extract value from the same tool. The difference is not in the tool — it is in knowing how to use it.
Three things are needed for AI to generate real productivity in a work environment: knowing how to ask the right question in the right way (prompt engineering), understanding which tool is appropriate for which task, and recognising limits and risks (safe usage). Without all three together, adoption stays at the surface.
How do LLMs work? What can they do, and what can they not do? Why do they sometimes produce incorrect responses (hallucination)? Without answers to these questions, teams either over-trust the tools or keep them at an unnecessary distance. Foundational literacy builds the ground for informed use.
The anatomy of an effective prompt: assigning a role, providing context, specifying output format, guiding with examples (few-shot), walking through reasoning step by step (chain-of-thought). Learning these techniques is not abstract; participants practise on real tasks from their own work. Email drafting, report summarisation, data analysis, content generation, presentation preparation — we work through the most common use cases for each department.
ChatGPT, Claude, Gemini; Notion AI, Microsoft Copilot, Google Workspace AI — what are the differences between these tools, and which excels at which task? A practical guide built around the team's existing toolset.
What happens when company data is entered into an AI tool? Privacy policies, data-processing terms, and corporate security: which information can be shared, which cannot? Employee usage guidelines from a KVKK perspective. This module protects both individual employees and the company from risk.
The accounting team, the sales team and the legal team each use AI differently. Giving everyone the same generic training is inefficient. We design training by department: which tasks benefit from AI immediately, which are not yet reliable, how to perform quality control.
The most concrete output of the training is the policy document: how AI is used in the company, which tools are approved, which data types cannot be shared, how outputs are verified, and who is responsible. This document remains as an internal guide for the team.
Half-day workshop, full-day intensive or a modular programme spread across multiple sessions — the format is shaped by company size and scheduling. In-person (Istanbul) or remote options are available. Participant numbers can range from five to fifty; for larger groups, simultaneous parallel tracks are run.
Works well: the team has been exposed to AI tools but is getting inconsistent results; leadership wants to accelerate adoption; team readiness is needed before an AI initiative.
Expectation management: one training session does not turn the team into AI experts. Adoption takes time; the practical outcome is the formation of consistent, informed usage habits. We say this plainly.
A short preliminary conversation is enough to define the training scope: how many people, which departments, the current toolset, and the primary objective. With this information we propose a training plan and a draft agenda. Fill in the form at /en/analysis for information and a proposal, or message us on WhatsApp.
Yes. The training proceeds through business use cases without a heavy technical vocabulary. No programming knowledge is required. The foundational literacy module is designed for those starting from scratch.
Workshop materials (a practical prompt library, tool comparison guide) and a company-specific internal AI usage policy draft are delivered.
It most often starts with a single workshop. We then recommend a short follow-up session three months later: what the team learned, where they got stuck, which scenarios need updating. An ongoing programme is optional.
Yes. Accounting, sales, legal, marketing — content and examples are customised for each department. Sessions can run consecutively on the same day or on separate days.
The core prompt and safe-usage modules are fixed; use cases and example tasks are shaped by sector. Different scenarios are available for retail, finance, legal, healthcare and manufacturing.
Basic AI workshops (half/full-day) range from ₺5,000 to ₺15,000. Comprehensive team programs (multi-session + playbook + follow-up) start at ₺30,000. We tailor scope in your free call.
We don't publish fixed price lists — quoting without scoping the project doesn't serve you. A free discovery call lets us understand your needs and present a project-specific proposal.
Let's define the project-specific investment together in a free discovery call.