DeNA President Tomoko Namba's Genius AI Prompt Techniques

Rebuilding the Company OS for AI, Not Just as a 'Convenient Tool'

As of July 2026, DeNA's official executive page lists Tomoko Namba as 'President and CEO.' Since she appeared as 'Executive Chairman' in lectures and articles from 2025 to early 2026, this article will organize her insights as 'DeNA President Tomoko Namba' based on her public speaking engagements while aligning with her current title. In her representative message on the DeNA official website, Namba positions DeNA as a 'permanent venture,' stating that their core business is the 'challenge of creating new Delight' across various sectors like gaming, sports, live communities, taxis, and urban development.

Specific AI tool names appearing in public information will generally be replaced with 'AI.' The important thing is not which tool to use. The essence of the Namba style is not using AI to make work faster, but changing the flow of work, the organization, talent allocation, and business creation itself to be AI-first.

I am providing a roadmap for earning 500,000 yen per month through AI x client work.

This includes AI x corporate training, CPP for official AI tools, and more.

Send 'Guide' to the link below to receive the benefits.

https://docs.google.com/document/d/1LRXiSARp2K9ffNoUlXIRSaKLyl3-GXB1muzz2G8-5e8/edit?usp=sharing

1. The Essence of Namba-style AI: 'Use it Yourself to Move the Organization'

The most important aspect of Namba's AI utilization is that the top management interacts with AI personally. In a 2025 DeNA lecture, Namba stated that dramatic productivity improvements require reorganizing operations around AI, which is a reform that involves pain. She emphasized that managers should not just give orders to 'use it because it's important,' but must use AI themselves, be moved and excited by its potential, and turn that passion into energy for reform.

This is where it differs from many companies. Typical AI implementation involves IT or DX departments choosing tools, distributing training, and tracking usage. The Namba style is the opposite. First, the top management becomes convinced that 'this changes the quality of work.' Next, they involve key people on the ground to create success stories. Finally, they change personnel evaluations, business flows, new business ventures, investments, and organizational design.

In short, Namba-style AI utilization is this:

It is not AI implementation. It is rebuilding management on an AI premise.

2. DeNA's 'AI All-in' is Not Just About Efficiency

DeNA declared it would go 'All-in on AI' in 2025. At the time, Namba discussed a vision where current operations run by approximately 3,000 people would not only be maintained but grown with half the staff, allowing the remaining talent to be redirected to new businesses. Furthermore, she explained the strategy of attacking with 10-person teams to mass-produce unicorns.

Do not misunderstand this. This is not about 'wanting to reduce headcount,' but about liberating humans from shallow tasks and moving them to creative work. Namba drew a parallel to how the transition to the cloud freed engineers from server maintenance to focus on creative work; the AI shift will free all employees from work done according to instructions, allowing them to focus on creative tasks.

This thinking is genius. Many companies see AI as a 'cost-cutting tool.' The Namba style is different.

Reinvest the time freed by AI into future businesses.

The goal of AI utilization is not 'to make things easier.' It is to use that ease to take on bigger challenges.

3. Personal AI Use: Changing 'Before, During, and After' Meetings

As an executive, Namba says she has many meetings and meets new people almost every week. She uses AI to prepare by gathering essential articles, videos, and social media posts about the person, feeding them into the AI, and interacting with the AI while traveling to understand the person's recent thoughts and interests. During meetings, she leaves recording and organizing to AI (with permission) and obtains minutes and ToDo lists immediately afterward. She also uses AI for thorough preliminary research before investment decisions.

This usage is not just 'time-saving.' It changes the quality of the meeting itself.

Meeting preparation without AI usually looks like this:

• Look at the person's company site.
• Read a bit of their social media.
• Read a few news articles.
• If there's no time, meet somewhat unprepared.
• Understand the person's story while listening during the meeting.
• Write notes from memory afterward.

The Namba style is this:

• Understand the person's philosophy, achievements, interests, and recent posts with AI before meeting.
• Ask the AI pinpoint questions while traveling.
• Focus on dialogue, not note-taking, during the meeting.
• AI organizes minutes and ToDos after the meeting.
• Use AI for additional research for the next decision or investment review.

The difference is huge. Meetings change from 'places for information gathering' to 'places for decision-making.'

Ready-to-use prompt: First-Time Meeting Preparation

1I am meeting the following person for the first time.
2Based on public information, please organize the information I should grasp before the meeting.
3
4# Target
5[Name, Company, Title, URL, Articles, Social Media Posts, etc.]
6
7# Output
81. Recent themes of interest for the person
92. Important statements and claims
103. Past achievements
114. Values the person seems to prioritize
125. Topics that could serve as a point of connection with me
136. 10 questions to ask during the meeting
147. Topics to avoid
158. Introduction for the first 5 minutes

4. The Core of AI Meeting Tech: 'Focus' Over 'Recording'

Many people think of AI transcription as a 'tool to avoid taking notes.' However, the point to note in the Namba style is different.

The true value of having AI record a meeting is that humans can focus on the other person's expressions, the temperature of their words, subtle discomforts, and signs of decision-making.

When you talk while taking notes, human attention is divided. Especially in situations like management, investment, hiring, negotiations, or partnerships, it's important not just what was said, but what wasn't said, where they hesitated, and where they got passionate. If AI handles recording and organizing, humans can return to the job of 'reading the room.'

AI Meeting Prompt

1The following is a transcript of a meeting.
2Please organize it into a format that can be used for the next actions, not just simple minutes.
3
4# Output
51. Decisions made
62. Pending items
73. Interests and concerns of each participant
84. Important numbers and proper nouns mentioned
95. ToDo list: with person in charge, deadline, and priority
106. Things to decide at the next meeting
117. Risks that were not explicitly stated but should be confirmed
128. Follow-up text I should send immediately

Just using AI minutes is something anyone can do. To make it Namba-style, you need to turn minutes into decision-making memos.

5. Moving from 'Planning Documents' to 'Prototypes' with AI

Symbolic of DeNA's AI utilization is the shift from a culture centered on planning documents to one centered on prototypes. Public articles from DeNA explain that in departments that have mastered AI agents, communication has emerged where people say, 'Show me a prototype, not a planning document,' resulting in fewer gaps in understanding and the ability to verify the 'feel' of the product.

This is extremely important. In the AI era, companies that repeat meetings with only planning documents will be slow. This is because with AI, ideas can immediately be turned into something that moves: screens, demos, trials, business flows, dashboards, proposals, videos, LPs, or app mockups.

In strong companies of the future, people will say in meetings:

'I understand the explanation. Use AI to make a prototype and show me.'

In this culture, the discussion changes:

• Judge by touching, not by abstract theory.
• Judge by user reaction, not by preference.
• Judge by the feel of the actual object, not the boss's voice.
• Judge by 'what happened when we tried it,' not 'whether it's possible.'

Prototype-First Prompt

1Please convert the following plan into a prototype proposal that can be verified, rather than a text-based planning document.
2
3# Plan
4[Content of the plan]
5
6# Output
71. Form of the minimum prototype
82. A verification version that can be made in 1 day
93. A verification version that can be made in 1 week
104. Screens, materials, and flows to show users
115. Hypotheses to verify
126. Success metrics
137. What can be learned if it fails
148. List of materials to have AI create

Planning ability in the AI era is not the ability to write a good planning document. It is the ability to turn it into something that can be shown immediately.

6. Reconfiguring Workflows from 'Small Wins'

DeNA's AI utilization follows a policy of accumulating certain success stories in small areas rather than changing the entire company's operations at once. Public articles introduce cases where AI was introduced to part of the distribution screening process, reducing human screening man-hours by 60%, and a process where humans only respond when AI is unsure in external service terms of use reviews, reducing human review man-hours by 70%.

Furthermore, 2026 reports state that in some development projects, AI replaced 95% of the work, and by improving business flows on an AI premise, legal checks were made 90% more efficient. Other media report cases where productivity increased 20-fold with 5% human and 95% AI work, and 60% to 90% efficiency improvements in specific tasks.

What we can learn from this is the order of AI implementation:

1. Don't go 'company-wide AI' immediately.
2. First, find tasks where AI can easily win.
3. Next, separate parts where human judgment is needed from parts to leave to AI.
4. Then, produce results in numbers.
5. Finally, reconfigure the entire business flow on an AI premise.

Business Flow Redesign Prompt

1Please redesign the following business on an AI premise.
2
3# Current Business Flow
4[Write the steps]
5
6# Constraints
7- Do not drop quality
8- Pay attention to legal, security, and personal information
9- Leave final human responsibility
10- Start with a small range that can be tested
11
12# Output
131. Tasks to leave to AI
142. Tasks humans must judge
153. Tasks to escalate to humans only when AI is unsure
164. A small experiment that can be tried in 1 week
175. Success metrics
186. Assumed risks
197. New business flow after introduction
208. Hypothesis of man-hours that can be reduced

In the Namba style, AI is not something to add to existing work. It is something to reconfigure the work itself, assuming AI.

7. Developing AI Talent through Evaluation Systems, Not 'Grit'

DeNA does not leave AI utilization only to a few experts. It combines AI introduction for all employees, support from an AI expert team, and unique AI skill evaluation indicators. Public articles explain that the AI expert team evaluates AI from perspectives such as business impact, quality, security, legal, data governance, usability, cost, and support systems, and publishes the results internally. They have also introduced a unique indicator to visualize AI utilization ability from levels 1 to 5, reflecting the actual contribution to individual and organizational results in evaluations, rather than just knowing about AI.

This is very practical. Companies that end AI utilization with 'let's do our best' will fail. People find it hard to continue actions that are not evaluated. Therefore, in the Namba style, being able to use AI is defined as a skill, and whether it led to results is monitored.

If you apply this to individuals, it's good to create your own AI utilization levels:

• Level 1: Can ask AI questions.
• Level 2: Can use it for writing, summarizing, translating, and minutes.
• Level 3: Can AI-fy part of one's own business flow.
• Level 4: Can change the way work is done on an AI premise.
• Level 5: Can improve the results of the entire team, not just oneself, with AI.

AI Utilization Level Diagnosis Prompt

1Please diagnose my AI utilization level.
2
3# My Job Content
4[Job content]
5
6# Current AI Utilization
7[Write situations where you use it]
8
9# Perspectives for Diagnosis
101. Is it staying at just time-saving?
112. Are you able to change the business flow?
123. Is the quality of the output improving?
134. Are you able to roll it out to the team?
145. Is it leading to results that are evaluated?
15
16# Output
17- Current level
18- What is being done well
19- What to improve
20- 3 AI uses to try from tomorrow
21- State to aim for in 1 month

Talent evaluation in the AI era is not 'did you use AI?' It is 'did you change results with AI?'

8. AI-fying the CEO's Thinking

DeNA's public articles also introduce a mechanism where the thoughts of the president and business heads are learned by AI so that employees can ask questions at any time. The president is always busy, and it's difficult for all employees to ask questions directly at the same time. However, if there is an AI that has learned the president's way of thinking, employees can ask questions without hesitation, and the consistency of management policy can be improved. A president of a subsidiary who introduced this also shared that in the process of putting their thoughts into AI, they realized how unorganized their thoughts usually were.

This is not just an internal chatbot. It is the infrastructuralization of management philosophy.

In strong organizations, the top's judgment criteria permeate the field. In weak organizations, the field hesitates every time, wondering 'what would the president think about this?' With AI, the top's philosophy, past statements, management policies, judgment criteria, customer views, hiring views, and product views can be made available for reference at any time.

However, this also has risks. AI does not make the final judgment instead of the president. AI is an auxiliary line to organize 'how should we think in this company,' and humans must take responsibility.

Management Philosophy AI Prompt

1Based on the following materials, please organize my judgment criteria.
2
3# Input Materials
4- Past internal messages
5- Management policies
6- Hiring policies
7- Product policies
8- Promises to customers
9- Past decision-making cases
10
11# Output
121. Values I prioritize
132. Criteria prioritized in decision-making
143. Things not to do
154. Judgment principles for when employees are lost
165. FAQ collection
176. Range AI is allowed to answer
187. Range that always requires personal confirmation

What to see in the Namba style is that AI is used as a tool to distribute organizational knowledge, not as a 'replacement for employees.'

9. AI Era Business Strategy: Targeting the 'Application Layer'

Namba divides the industrial structure of generative AI into chips, computing infrastructure, foundation models, development tools, and the application layer, stating that DeNA will target the application layer. The reason is that the application layer is where you can directly touch end-users, receive specific use cases and needs, and turn them into added value.

This can be applied directly to individuals. What is valuable in the AI era is not just making giant models. Rather, the winning path for many people and companies is to understand the detailed pains of the field and create applications that solve them with AI.

In B2B, Namba emphasizes the AI agent area that goes deep into specific industries and tasks, stating a policy to start from areas where DeNA has business knowledge and operational assets, such as sports, facility management, healthcare, and medical. In B2C, she shows interest in areas related to entertainment, community, solving loneliness, and games—areas involving immersion and human emotion.

The Namba-style business idea derived from this is:

• Don't compete with the model itself.
• Ride on top of AI.
• Get close to the customer.
• Find industry-specific hassles.
• Rebuild workflows with AI.
• Make deep business knowledge a competitive advantage.

AI Business Idea Discovery Prompt

1Please find areas in my industry that can be commercialized as AI applications.
2
3# Industry
4[Write the industry]
5
6# Our Strengths
7[Customer touchpoints, data, business knowledge, sales channels, brand, etc.]
8
9# Output
101. Tasks customers struggle with daily
112. Industry-specific challenges hard to solve with existing AI
123. Tasks that can be replaced by AI
134. Tasks where human judgment should remain
145. Small AI product to make first
156. Differentiation from competitors
167. Revenue model
178. 3-month verification plan

New business in the AI era starts not from 'amazing technology,' but from specific pain in the field.

10. 'Speed' Becomes a Qualification for Products

At the 2026 DeNA AI Day, Namba reportedly looked back on the year AI agents became democratized, stating that the work of development engineers has changed significantly and that a harsh reality is being presented to 'half-baked expertise' and 'products without a sense of speed.'

This is tough but realistic. AI increases the speed of development, document creation, analysis, customer support, sales preparation, legal confirmation, and hiring PR. When that happens, you cannot participate in the competition just by 'doing your best' or 'doing it carefully.' The company that sees the customer's reaction, fixes it immediately, releases it immediately, verifies it immediately, and fixes it again will win.

In the product competition of the AI era, the following powers become important:

• Build fast.
• Test fast.
• Discard fast.
• Learn fast.
• Fix fast.
• Return to the customer fast.

However, speed alone is dangerous. Namba-style speed is not 'releasing sloppily.' It separates the roles of AI and humans, using AI to accelerate work while humans handle responsibility, value judgment, customer understanding, ethics, and brand.

Speed Diagnosis Prompt

1Please diagnose whether our product development is responding to the speed of the AI era.
2
3# Current Development Flow
4[Flow of planning, design, development, review, release, verification]
5
6# Output
71. Bottlenecks that are slowing things down
82. Processes that can be shortened with AI
93. Processes humans should spend time on
104. Parts that can be prototyped
115. Causes of decision-making clogs
126. Things that can be improved in 1 week
137. Organizational habits to change in 3 months

Speed in the AI era is not work speed. It is learning speed.

11. AI Does Not 'Steal Jobs,' It Erases 'Thin Work'

Namba says that even in a future where AI moves as instructed, the starting point is human, and the will to make things happen, the power to be absorbed, and desires are important. Since thin work will be left to computers, the 'starting power' to begin something with intent becomes crucial.

This is a very sharp career theory for the AI era. What is easily replaced by AI is not just simple labor. Work that was handled somehow according to past patterns even if the purpose was vague will be replaced. Conversely, what increases in value is the work of posing questions, finding customer pain, involving colleagues, taking responsibility, and starting from a strong will.

The more AI can do, the 'thicker' the work remaining for humans becomes.

Therefore, in Namba-style AI utilization, people who have what they want AI to do are stronger than 'people who can use AI.'

Starting Power Prompt

1I want to increase the value of my work in the AI era.
2Based on the following information, please organize the 'starting point' I should have.
3
4# My Experience
5[Experience]
6
7# Things I feel anger or discomfort toward
8[Awareness of issues]
9
10# Things I can get absorbed in
11[Interests]
12
13# Assets I can use
14[Skills, customers, data, network, brand]
15
16# Output
171. Themes I should start with
182. Tasks to leave to AI
193. Value I should bear as a human
204. How to start small
215. Path to commercialization/career development

What is needed in the AI era is not just the power to command AI. It is the power to decide what to start.

12. If You Create an AI Expert Team, Don't Make It a 'Convenient Tool Introduction Desk'

At DeNA, the AI expert team supports each business department, handling AI evaluation, utilization support, and knowledge database construction. Evaluation perspectives include business impact, quality, security, legal, data governance, usability, cost, and support systems.

Replacing this in a general company, the role of an AI promotion team is not 'introducing recommended AI tools.' Instead, it is finding use cases that lead to business results, entering the field, changing business flows, managing risks, quantifying results, and rolling them out to other departments.

A bad AI promotion team looks like this:

• 'This AI is convenient.'
• 'Please take the training.'
• 'Let's increase the usage rate.'
• 'We'll distribute a prompt collection.'

A strong AI promotion team moves like this:

• 'This task can be cut by 60% with AI.'
• 'Let's have AI do the primary check and only escalate to humans when it's unsure.'
• 'Let's roll out the success story of this department to legal and HR next.'
• 'This AI is convenient, but it cannot be used due to data governance.'
• 'This use case has a small business impact, so we won't prioritize it.'

AI Promotion Team Design Prompt

1I want to create an AI promotion team in the company.
2Please design the team to be directly linked to business results, not just tool introduction.
3
4# Company Information
5[Industry, number of people, main business, issues]
6
7# Output
81. Mission of the AI promotion team
92. Necessary roles
103. Support methods for each department
114. AI tool evaluation criteria
125. Rules for security, legal, and data management
136. How to create success stories
147. 3-month roadmap
158. Evaluation indicators

AI promotion is management reform, not IT implementation.

13. 'Daily Pattern' to Apply DeNA-style AI to Individuals

Applying the Namba style to an individual's day looks like this:

• In the morning, have AI read today's schedule.
• Have AI research first-time meeting partners.
• Have AI create points of discussion and questions for each meeting.
• Brainstorm with AI while traveling.
• Leave recording to AI during meetings and focus on dialogue.
• Create ToDos and follow-up texts with AI after meetings.
• Use AI for additional research before decision-making.
• At the end of the day, have AI organize 'today's learnings' and 'tomorrow's priorities.'

Namba-style Daily Operation Prompt

1Based on today's schedule, I want to maximize productivity and work quality using AI.
2
3# Today's Schedule
4[List of schedule]
5
6# Output
71. Purpose of each appointment
82. Things to prepare in advance
93. Things to research with AI
104. Questions to ask in meetings
115. Outputs to create after meetings
126. Today's most important decision
137. Tasks to stop
148. Tasks that can be moved to tomorrow

Just by doing this every day, AI becomes the command center of work, not just a 'convenient tool used occasionally.'

14. '90-Day Roadmap' to Apply DeNA-style AI to a Company

In March 2026, DeNA held an event to show the results of one year since the 'AI All-in' declaration, publishing AI utilization cases in multiple areas such as development, quality control, business reform, games, sports, demand forecasting, and HR. The event page explained it as a place to show the results of pursuing both efficiency and creativity through AI and proceeding with transformation from the depths.

If a normal company were to imitate this, they would proceed like this in 90 days:

Days 1-30: President and Executives Use it Thoroughly

First, the management team uses AI every day. Use it for meeting preparation, minutes, research, hiring, sales, legal, management planning, and prototyping. The important thing here is for the president to truly feel that 'this is convenient.' Namba also says that companies where the top feels the potential and convenience of AI and gets excited will proceed with transformation faster.

Days 31-60: Create Small Wins

Don't roll it out company-wide immediately; choose three tasks where AI is effective. For example, minutes, inquiry classification, legal review, sales material creation, hiring candidate research, expense checks, or quality control. The goal is not 'we used AI,' but to show numbers like 'man-hours reduced by X%,' 'remands reduced by X cases,' or 'lead time shortened by X days.'

Days 61-90: Incorporate into Business Flows and Evaluation Systems

If successful, incorporate AI utilization into business flows rather than individual effort. Make using AI the standard procedure and design it so humans only look when AI is unsure. Furthermore, evaluate people who produced results with AI. The point that DeNA visualizes AI skills and reflects contributions to results in evaluations can be applied to general companies.

90-Day Roadmap Generation Prompt

1Please create a 90-day roadmap to change the company into an AI-premise organization.
2
3# Company Information
4[Industry, number of employees, main business, current issues]
5
6# Conditions
7- Management uses it first
8- Create small success stories
9- Change business flows
10- Reflect in evaluation systems
11- Protect security and legal
12- Design so the field can continue using it
13
14# Output
151. What to do in days 1-30
162. What to do in days 31-60
173. What to do in days 61-90
184. Success metrics
195. Points where failure is likely
206. Necessary structure
217. What the president should check weekly

15. Seriously Aiming for '10-Person Unicorns' in New Business

Namba says that in the AI era, we are in a time where one person can do the work of ten. She also touches on the vision of mass-producing unicorns with 10-person teams, M&A of AI startups, and support for independence of internal businesses.

In DeNA official news from June 2026, it was announced that DeNA would have Namba speak and host a booth at IVS2026, and a side event was announced where startup entrepreneurs can pitch directly to Namba and receive business brainstorming. Furthermore, networking events for entrepreneurs and startups in the AI field are also prepared.

What can be seen from this is that DeNA is not closing AI to 'internal efficiency.' It lightens current operations with AI and flows the surplus power generated there into startups, M&A, spin-outs, and new businesses. This is the idea of changing the entire organization into a venture creation device.

10-Person Unicorn Vision Prompt

1Please think of a vision to create a large business with a team of 10 or fewer people, assuming AI.
2
3# Area
4[Industry/Theme]
5
6# Team Strengths
7[Member skills, customer touchpoints, data, business knowledge]
8
9# Output
101. Customer issues to target
112. Tasks that can be made 10x more efficient with AI
123. Initial product proposal
134. Role design for 10 people
145. Tasks to leave to AI
156. Expertise humans should have
167. Revenue model
178. MVP to make in 3 months
189. Growth scenario to aim for in 1 year

Small teams in the AI era will no longer find having few people a weakness. A 10-person team that uses AI thoroughly is faster than a large organization that cannot use AI.

16. 7 Principles of Namba-style AI Utilization

Principle 1: The President Uses it Thoroughly First

AI implementation is not left to the field. The president, directors, and department heads use it every day. Use it for meeting preparation, document creation, decision-making, investment judgment, hiring, sales, legal, and prototyping. AI reform where the top is not excited will not convey heat to the field.

Principle 2: Reconfigure Workflows on an AI Premise, Don't Just Add AI to Existing Work

'Making current work a bit faster with AI' is insufficient. AI makes the primary judgment, and humans look at exceptions and final responsibility. AI creates materials, and humans put in intent and judgment. AI researches, and humans decide. Reconfigure business flows into this division.

Principle 3: Produce Prototypes, Not Planning Documents

In the AI era, competing with only long planning documents is slow. Use AI to make screens, demos, LPs, dashboards, business flows, proposal materials, and trials. In meetings, produce 'things that can be touched' rather than explanations.

Principle 4: Produce Small Wins in Numbers

'We are using AI' is meaningless. Show results in numbers, such as 60% man-hour reduction, 70% review reduction, 90% check efficiency, or 95% development replacement. When numbers come out, the atmosphere in the company changes.

Principle 5: Include AI Skills in Evaluation

In organizations where people who can use AI are not evaluated, AI utilization will not take root. Evaluate people who improved their own results with AI, people who improved team results, and people who changed business flows.

Principle 6: Shift Human Value from 'Work' to 'Starting Point'

AI makes work faster. Therefore, humans must have what should be done, whose pain should be solved, and what kind of future they want to create. In the AI era, people who start with intent will increase in value.

Principle 7: Don't End with Efficiency; Reinvest in New Business

Don't use the time freed by AI only for breaks; invest it in future businesses. Lighten existing businesses and redirect talent and capital to new businesses, startup collaboration, M&A, and spin-outs. This is the DeNA-style 'AI All-in.'

17. Ready-to-Use Namba-style Prompt Collection

1. For Presidents/Executives: Today's AI Chief of Staff Prompt
``
You are my AI chief of staff.
Based on today's schedule, please maximize the quality and speed of my work.

# Today's Schedule
[List of schedule]

# Output
1. Purpose of each appointment
2. Information to read in advance
3. Important points of discussion for each partner
4. Questions to ask in meetings
5. Things to decide
6. ToDos after meetings
7. Tasks to leave to AI
8. Judgments I should make directly
``

2. Preliminary Research Prompt for First-Time Partners
``
Please organize the information I should grasp before meeting the following person.

# Partner Information
[Name, company, title, URL, articles, social media posts, etc.]

# Output
1. Career history
2. Recent activities
3. Important statements
4. Values/Interests
5. Points of connection with me
6. Conversation starters
7. Questions to ask
8. Discussion points to avoid in the meeting
``

3. Investment/Partnership Judgment Prompt
``
I am considering investing in or partnering with the following company.
Please organize the materials necessary for decision-making.

# Target Company
[Company name, URL, materials]

# Output
1. Business overview
2. Market size
3. Customer issues
4. Competitors
5. Strengths
6. Weaknesses
7. Business risks
8. Discussion points for the management team
9. Additional questions to confirm
10. Hypotheses for investment/partnership judgment
``

4. AI Business Reform Prompt
``
Please rebuild the following business on an AI premise.

# Current Business
[Business content]

# Current Issues
[Takes time, many mistakes, dependent on specific individuals, etc.]

# Output
1. Tasks that can be left to AI
2. Tasks where AI can make primary judgments
3. Tasks humans should make final judgments on
4. Exception handling
5. New business flow
6. Necessary rules
7. Hypothesis of man-hour reduction
8. Experiment to try in 1 week first
``

5. Prototype Generation Prompt
``
Please turn the following plan into a prototype that can be shown in a meeting.

# Plan
[Content of the plan]

# Output
1. Minimum prototype to make in 1 day
2. Screen configuration
3. User usage scenarios
4. Hypotheses to verify
5. Success metrics
6. Questions to ask users
7. Functions to make next
``

6. AI Utilization Evaluation Prompt
``
Please evaluate my or the team's AI utilization.

# Current Utilization Status
[Situations where it's used]

# Results
[Time reduced, quality improved, outputs created]

# Output
1. Current AI utilization level
2. Parts staying at just time-saving
3. Parts where business flow has been changed
4. Success stories that can be rolled out to the team
5. Skills to improve next
6. 30-day improvement plan
``

7. Management Philosophy Organization Prompt
``
Based on my past statements and materials, please organize the judgment criteria to be conveyed to the organization.

# Input
[Management policies, internal messages, hiring materials, past decision-making, etc.]

# Output
1. Values I prioritize
2. Judgment criteria when lost
3. Priorities
4. Things not to do
5. Principles for employees to judge autonomously
6. Answers to FAQs
``

8. New Business Exploration Prompt
``
Please explore new businesses we should tackle, assuming AI.

# Our Strengths
[Customers, data, industry knowledge, technology, talent, brand]

# Market
[Target market]

# Output
1. Issues customers are strongly struggling with
2. Tasks easily solved with AI
3. Points where existing services are insufficient
4. Small product proposal to start with
5. Team configuration of 10 or fewer people
6. How to get initial customers
7. 3-month verification plan
8. Expansion scenario if successful
``

9. Internal AI Camp Prompt
``
Please design a 1-day camp to boost the department's AI utilization power at once.

# Target Department
[Department name, number of people, business content]

# Goal
- Don't end with just touching AI
- Create actual business improvement plans
- Produce a prototype at the end

# Output
1. Timetable of the camp
2. Advance assignments
3. Exercises on the day
4. Prototypes to create
5. Format of result presentation
6. Follow-up for 30 days after the camp
7. Result indicators
``

10. Prompt to Train Starting Power
``
I want to find the starting point I should have as a human in the AI era.

# My Discomfort
[What I think is wrong in society, industry, or work]

# My Experience
[Experience]

# My Strengths
[Strengths]

# Output
1. Theme I should seriously tackle
2. Why it makes sense for me to do it
3. Tasks to leave to AI
4. Value I bear as a human
5. First step
6. Goal in 1 year
``

Conclusion: Namba-style AI Utilization is Not About 'Taking it Easy' with AI, but 'Taking the Next Gamble' with AI

If you were to summarize DeNA President Tomoko Namba's AI utilization techniques in one sentence, it would be this:

Reduce work with AI and move humans to future work.

• Use AI for preliminary research on first-time partners.
• Brainstorm with AI while traveling.
• Leave meeting records and ToDos to AI.
• Leave preliminary research for investment decisions to AI.
• Create prototypes with AI instead of planning documents.
• Reconfigure business flows on an AI premise.
• Evaluate employees' AI skills.
• Distribute the president's philosophy to the organization with AI.
• Produce small wins in numbers.
• Redirect freed-up talent to new businesses.

Only by doing all this can it be called 'AI utilization.'

What's amazing about the Namba style is that she doesn't see AI as a 'convenient tool.'

She sees AI as a power to rebuild the company's OS.

She sees AI as a power to lighten current operations.

She sees AI as a power to liberate humans from thin work.

She sees AI as leverage for a 10-person team to create a large business.

And what remains at the end is human will.

What do you want to do?

Who do you want to please?

Which issue do you want to solve?

What can you get absorbed in?

It is not humans who will be eliminated in the AI era.

It is work without intent.

The essence of Namba-style AI utilization is not efficiency.

It is taking back time with AI and betting that time on the future.