Beyond 'Make it look good': Transitioning from AI Operator to AI Director with New Training Program
DXHR Inc. has launched the 'AI Direction Skill Improvement Training,' a program designed to evolve users from AI operators to AI directors who take responsibility for output quality. The curriculum focuses on management essentials—defining requirements, evaluating results, and providing feedback—rather than mere prompt engineering, aiming to cultivate talent capable of achieving tangible business results.
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- 📰 Published: May 27, 2026 at 13:00
- 🔍 Collected: May 31, 2026 at 23:14 (106h 14m after Published)
- 🤖 AI Analyzed: June 2, 2026 at 01:07 (25h 53m after Collected)
DXHR Inc. (Headquarters: Shibuya, Tokyo; CEO: Kazunari Maeda) has announced the launch of its new AI utilization training program, 'AI Direction Skill Improvement Training.' This 11-chapter practical program aims to help professionals evolve from the 'AI Operator' stage—using generative AI as a convenient tool—to the 'AI Director' stage, where they take responsibility for output quality and command results. The training focuses not on how to write prompts, but on how to manage work with AI, systematically teaching three core skills: requirement definition, evaluation, and feedback. Since the emergence of ChatGPT in 2022, knowing 'correct prompts' was considered the key to AI utilization, leading to a proliferation of 'spell' collections. However, with the rapid evolution of models like GPT-4, Claude, and Gemini, natural language understanding and reasoning capabilities have improved dramatically, rendering 'spell-like' techniques such as 'think step-by-step' increasingly obsolete. Meanwhile, as AI performance rises, new challenges have emerged. Since anyone can instantly create 80-point outputs, the value of simply 'being able to use AI' is rapidly commoditizing. The source of differentiation has shifted to the 'instructional' and 'editing' skills required to polish AI output from 80 to 100 points. Against this backdrop, DXHR has developed a training program that systematizes the process of working with AI rather than just prompt techniques. The program applies the essence of management—defining requirements, evaluating deliverables, and providing feedback—to AI utilization, much like delegating tasks to subordinates. By mastering 'how to work with AI' rather than just 'how to use AI,' the program cultivates talent capable of delivering real results in business settings. The program consists of 11 chapters combining lectures, demo videos, and individual exercises to help participants master AI direction skills based on specific business scenarios. Feature 1: Learning 'how to delegate' rather than 'how to write prompts.' The training teaches three business skills essential for delegating tasks to AI: requirement definition, evaluation, and feedback. These are fundamentally the same as the management skills required for guiding subordinates, making them versatile skills applicable to team management as a whole. Feature 2: Systematically training thinking processes, from articulating tacit knowledge to creative collaboration with AI. Asking AI to 'make it look good' only yields average results. This training updates the entire thinking process, including techniques for formalizing tacit knowledge, task decomposition to identify AI's capability boundaries, decision-making to seek 'options' rather than 'the correct answer,' and Socratic dialogue to deepen thinking through interaction with AI. Feature 3: 'Unlearning' old habits from the search era and acquiring new habits for the AI era. Participants will let go of old habits like searching with keyword lists, passively accepting AI output, and seeking the shortest path to a single answer. Instead, they will acquire four new habits: 'speaking as if instructing a subordinate,' 'continuing the dialogue,' 'acting as a Director,' and 'seeking options.' This training is ideal for companies and professionals facing challenges such as: companies stuck at the 'make it look good' level of AI usage; teams experiencing inconsistent quality and frequent rework; professionals who have studied prompt books but see no practical results; management struggling to deploy AI across departments; and managers wanting to improve both subordinate management and AI skills simultaneously. The content is suitable for all professionals who want to use generative AI as a business weapon, regardless of industry or job function. Moving forward, DXHR plans to build a tiered training system for AI talent, including industry-specific AI training (real estate, nursing, etc.) and comprehensive packages combined with AI security training. From 'being able to use AI' to 'achieving results with AI,' we aim to elevate the AI utilization capabilities of every business person and contribute to the productivity and competitiveness of companies.
FAQ
What is the main challenge for Japanese companies in AI adoption?
Companies often struggle with inconsistent AI output quality and the inability to translate prompt engineering knowledge into tangible business results.