In a Nutshell:

1. A neural network is not a creator, but a powerful compiler
It is trained on large datasets, finds patterns, and outputs relevant answers. It cannot invent new things and does not learn during your dialogue with it. The model's knowledge is limited to its data cut-off date.

2. What AI can / cannot do

• Can: generate texts, structure briefs, create images, transcribe and summarize meetings, assist with code.
• Cannot: think for a human, guarantee information accuracy (possible "hallucinations" — plausible but false facts), understand context without a clear prompt, safely handle confidential data in public services.

3. Recommended tools
Gemini 2.5/3 Pro, ChatGPT-5, Claude 4, Grok, Deepseek V3, Qwen 3 Max. 

Tip: use the latest versions without mini/fast postfixes.

4. The art of prompting: Role + Context + Task + Format

This scheme is a formula that turns a vague request into a clear instruction for AI, allowing you to get a relevant, structured, and ready-to-use result.

Role (Who are you?) - you assign the AI a specific professional or expert role, e.g., "marketer", "business analyst", "project manager".

Context (For whom? About what? Under what conditions?) - you provide background information, specific details, and constraints.

Task (What needs to be done?) - here you clearly and unambiguously formulate the work the AI must perform. The task is a specific action: "come up with", "write", "analyze", "compare", "generate".

Format (How to present the result?) - you define the form the answer should take (list, table, etc.).

5. Content generation in practice

• Texts: Treat AI like a junior copywriter, provide clear context.
• Briefs: Upload notes, bullet points, thoughts, meeting minutes, ask to structure them.
• Images: Use Gemini Nano Banana for illustrations, Adobe Firefly for editing and rights guarantee. It's better to add text to images separately.
• Presentations: It's more effective to create them step-by-step (text → visuals → assembly) than using auto-generators.

6. Process optimization

• Meeting transcription and summarization: Use specialized services, then upload the text to AI for extracting key agreements.
• Automation within the company at M-Social: 

Implemented an AI agent to analyze 120+ client chats and all corporate emails. The AI agent saves all correspondence to a database and builds a daily report for the manager on each employee: what project agreements were recorded during the past day; what questions from clients or employees remained unresolved; what conflict or tense situations occurred.

An HR AI agent is in development. It assists in onboarding new employees and any staff member can chat with it to get answers to internal questions.

A presale bot is in development. Its goal is to help managers compile lists of questions for client briefs and evaluate projects.

7. Security and legal aspects

• Do not upload to public AI: personal data, confidential briefs, internal documents, NDA materials.
• Copyright: AI-generated results are a "gray area"; there is effectively no legal precedent for such cases. If you need to claim authorship of content, it must be substantially refined after AI generation.
• Do not generate images of characters protected by copyright.
• Do not use images of famous people.

Conclusion

AI is a powerful assistant that saves time on routine tasks but does not replace expertise, strategy, and creativity. The quality of the result depends on the quality of the prompt.