{"id":743876,"date":"2026-05-25T17:34:33","date_gmt":"2026-05-25T14:34:33","guid":{"rendered":"https:\/\/eba.com.ua\/?post_type=tribe_events&#038;p=743876"},"modified":"2026-06-04T15:30:35","modified_gmt":"2026-06-04T12:30:35","slug":"online-programa-rozvytku-shi-agenty-dlya-biznesu-avtomatyzatsiyi-ta-kreatyvu-2026-05-25-17-34","status":"publish","type":"tribe_events","link":"https:\/\/eba.com.ua\/en\/event\/online-programa-rozvytku-shi-agenty-dlya-biznesu-avtomatyzatsiyi-ta-kreatyvu-2026-05-25-17-34\/","title":{"rendered":"[:ua]Online-\u041f\u0440\u043e\u0433\u0440\u0430\u043c\u0430 \u0440\u043e\u0437\u0432\u0438\u0442\u043a\u0443: \u0428\u0406-\u0430\u0433\u0435\u043d\u0442\u0438 \u0434\u043b\u044f \u0431\u0456\u0437\u043d\u0435\u0441\u0443, \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0437\u0430\u0446\u0456\u0457 \u0442\u0430 \u043a\u0440\u0435\u0430\u0442\u0438\u0432\u0443 [:en]Online-Development Programme: AI Agents for Business, Automation, and Creativity [:]"},"content":{"rendered":"<p><\/p>\n<p><span class=\"NormalTextRun SCXW22785106 BCX0\">The programme is built around the following principle: explanation \u2013 examples \u2013 template \u2013 practice \u2013 result. Theory is kept to the minimum necessary, while the <span class=\"NormalTextRun AdvancedProofingIssueV2Themed SCXW22785106 BCX0\">main focus<\/span><span class=\"NormalTextRun SCXW22785106 BCX0\"> is on the practical creation of agents and applying this logic to real work-related tasks.<\/span><\/span><\/p>\n<p><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW245767990 BCX0\">EBA<span class=\"NormalTextRun SCXW245767990 BCX0\"> Management Development Centre team, together with<\/span><\/span><span class=\"NormalTextRun SCXW245767990 BCX0\"> <\/span><strong><span class=\"NormalTextRun SCXW245767990 BCX0\">Mykhailo Patsan<\/span><\/strong><span class=\"NormalTextRun SCXW245767990 BCX0\"><strong>,<\/strong> <\/span><span class=\"NormalTextRun SCXW245767990 BCX0\">invite you to <span class=\"NormalTextRun SCXW245767990 BCX0\">participate<\/span><span class=\"NormalTextRun SCXW245767990 BCX0\"> in the<\/span><span class=\"NormalTextRun SCXW245767990 BCX0\"> <\/span><\/span><strong><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW245767990 BCX0\">Online-Development<span class=\"NormalTextRun SCXW245767990 BCX0\"> <\/span><span class=\"NormalTextRun SpellingErrorV2Themed SCXW245767990 BCX0\">Programme<\/span><\/span><\/strong><span class=\"NormalTextRun SCXW245767990 BCX0\"><strong>: AI Agents for Business, Automation, and Creativity<\/strong>.<\/span><\/p>\n<p><strong>Target audience: <\/strong>everybody who is in the process of creating or working with AI-agents.<\/p>\n<p><strong>PROGRAMME<\/strong><\/p>\n<p><b>Module 1. What AI Agents Are and How They Work<\/b> &#8211; <b>June 25, 17:00\u201319:00<\/b><\/p>\n<p><b>Objective<\/b><\/p>\n<p>To give participants a clear understanding of what an AI agent is, how it differs from a regular chatbot or prompt, what its architecture looks like, and where agents can deliver real business value.<\/p>\n<p><b>Topics for discussion:<\/b><\/p>\n<ul>\n<li>What an AI agent is, explained in simple terms.<\/li>\n<li>The difference between a chatbot, an assistant, automation, and an agent.<\/li>\n<li>Why an agent is a system with a role, memory, tools, action logic, and a controlled outcome.<\/li>\n<li>Which tasks should be delegated to agents, and which are better left to a person or classical automation.<\/li>\n<li>Typical risks of working with agents: hallucinations, unclear data, weak quality criteria, and lack of control.<\/li>\n<li>AI Agent Architecture<\/li>\n<\/ul>\n<p><strong>Tools<\/strong><\/p>\n<table data-tablestyle=\"MsoTableGridLight\" data-tablelook=\"1696\">\n<tbody>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Tool<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p><b>What We Use It For<\/b><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Claude<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Reasoning, analysis, texts, documents, methodologies, business logic, and agent workflows.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Codex<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Code, scripts, integrations, technical agents, automation, and working with repositories.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>OpenClaw<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Building agent architecture, launching multiple agents, task routing, and systematic agent workflows.<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><strong>Session Practice:<\/strong><\/p>\n<ul>\n<li>Each participant selects one real task from their own work.<\/li>\n<li>They describe it using a simple framework: input data, performer, expected result, risks, and quality criteria.<\/li>\n<li>Together, we determine whether this task is suitable for an AI agent.<\/li>\n<\/ul>\n<p><b>Module 2. Creating AI Agents for Functional Areas &#8211; <\/b><b>July 2, 17:00\u201319:00<\/b><\/p>\n<p><b>Objective<\/b><\/p>\n<p>To teach participants how to design agents for specific business functions: sales, marketing, HR, finance, operations, support, legal, analytics, and management.<\/p>\n<p><b>Methodology for Selecting Tasks for Agents:<\/b><\/p>\n<p>A task is well suited for an AI agent if it is repetitive, has a clear input, a clear output, quality criteria, and can be reviewed by a human at the final stage.<\/p>\n<p>The task is performed regularly.<\/p>\n<ul>\n<li>There is clear input data: text, documents, spreadsheets, correspondence, CRM, call recordings, and tasks.<\/li>\n<li>There is an expected result: a report, conclusion, table, action, recommendation, or file.<\/li>\n<li>There are rules or examples of high-quality execution.<\/li>\n<li>The task takes a lot of the team\u2019s time.<\/li>\n<li>The result can be reviewed before use.<\/li>\n<\/ul>\n<p><b>Session Practice<\/b><\/p>\n<ul>\n<li>Each participant creates a concept for their own functional agent.<\/li>\n<li>The group reviews 2\u20133 examples of agents for different areas.<\/li>\n<li>Participants develop the first version of a prompt or technical specification for their own agent.<\/li>\n<\/ul>\n<p><b>Examples of Agents<\/b><\/p>\n<table data-tablestyle=\"MsoTableGridLight\" data-tablelook=\"1696\">\n<tbody>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Example<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p><b>What It Does<\/b><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Sales Agent<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Analyzes managers\u2019 calls, identifies strengths and weaknesses, records the outcome of the conversation, provides recommendations, and prepares a report for the manager.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>HR Agent<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Analyzes candidates\u2019 CVs, compares them with job requirements, determines relevance, and prepares a short conclusion.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Legal Analysis Agent<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Reads a contract, identifies risks for the parties, explains them, and suggests how to reduce those risks.<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><b>Module 3. Creative AI Agents and Launching Your Own Agent &#8211; <\/b><b>July 9, 17:00\u201319:00<\/b><\/p>\n<p><b>Objective<\/b><\/p>\n<p>To show how to create creative agents for content, ideas, visuals, presentations, scripts, advertising campaigns, and communications. At the final stage, participants will build their own agent and test it on a real task.<\/p>\n<p><b>What a Creative AI Agent Is:<\/b><\/p>\n<ul>\n<li>It understands the brand, audience, product, and tone of communication.<\/li>\n<li>It generates ideas but does not stop at raw drafts.<\/li>\n<li>It creates the structure of content, presentations, videos, or advertising campaigns.<\/li>\n<li>It adapts messages for different channels and formats.<\/li>\n<li>It checks the result against the task, style, and quality criteria.<\/li>\n<\/ul>\n<p><b>Session Practice<\/b><\/p>\n<p>Participants create their own agent based on the task they selected during the first session. The final agent structure must be clear enough to be transferred to Claude, Codex, or OpenClaw.<\/p>\n<table data-tablestyle=\"MsoTableGridLight\" data-tablelook=\"1696\">\n<tbody>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Block<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p><b>Result<\/b><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Agent Name<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Ready-made name.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Role<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Clearly described function.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Task<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>What the agent solves.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Input Data<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>What needs to be provided to the agent.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Workflow Algorithm<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Step-by-step logic.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Tools<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Claude, Codex, OpenClaw, or others.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Result Format<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>Table, report, file, text, presentation, code.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Quality Check<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>How a person checks the agent\u2019s work.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\">\n<p><b>Next Steps<\/b><\/p>\n<\/td>\n<td data-celllook=\"0\">\n<p>How to implement the agent in a real process.<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><strong>After completing the programme, participants will get certificattes.<\/strong><\/p>\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>The programme is built around the following principle: explanation \u2013 examples \u2013 template \u2013 practice \u2013 result. Theory is kept to the minimum necessary, while the main focus is on the practical creation of agents and applying this logic to real work-related tasks. EBA Management Development Centre team, together with Mykhailo Patsan, invite you to [&hellip;]<\/p>\n","protected":false},"author":4513,"featured_media":744486,"comment_status":"open","ping_status":"closed","template":"","meta":{"inline_featured_image":false},"tags":[],"tribe_events_cat":[35,32],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Online-Development Programme: AI Agents for Business, Automation, and Creativity  - European Business Association<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/eba.com.ua\/event\/online-programa-rozvytku-shi-agenty-dlya-biznesu-avtomatyzatsiyi-ta-kreatyvu-2026-05-25-17-34\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Online-Development Programme: AI Agents for Business, Automation, and Creativity  - European Business Association\" \/>\n<meta property=\"og:description\" content=\"The programme is built around the following principle: explanation \u2013 examples \u2013 template \u2013 practice \u2013 result. 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