Training Program Launch: IPLoT Presents at AI Conference 'AI SUMMIT 2026' — Live Demo of Instant Business Improvement App Creation Using Claude Code

IPLoT Co., Ltd. (Headquarters: Tokyo / CEO: Kazuyuki Jinbo) participated as a sponsor in the online conference 'AI SUMMIT 2026 — AI Transforming Every Workplace,' hosted by AITECH Inc., on Wednesday, June 10, 2026. The company delivered a session titled 'Driving Organizations with Claude Code: Creating Operational Improvement Apps Today and Discovering On-site Challenges,' featuring a live demonstration of generating a business improvement application on the spot using Claude Code, sharing practical insights for making AI functional in real-world environments.

Additionally, the company is offering a corporate training program, 'AI Strategist Training,' which systematizes the essence of this session.

## Overview of the Session

The conference, themed 'Frontline AI Implementation Insights from Industry Leaders,' was an online event where companies shared real-world AI utilization experiences and next steps.

The core of IPLoT's session was not about asking AI for answers, but demonstrating AI as a creator. Using a common workplace challenge—managing scattered inquiries received via phone, email, and fax with multiple people—the session showcased the live creation of a 'Complaint and Inquiry Management App.' This app used a Kanban-style interface to track inquiries as 'Not Responded,' 'In Progress,' and 'Completed,' with overdue items highlighted in red.

The key point was that the application was generated simply by describing the current situation ('current pain points') and the desired state ('what we want'), without requiring advanced prompt engineering techniques.

## Three Practical Insights Shared in the Session

- The true bottlenecks in development are at both ends: requirements definition and on-site implementation

Among standard development processes, generative AI has most significantly reduced the cost of the 'middle stream' (implementation). The real challenges lie in the 'upstream' (requirements definition)—identifying the current state, desired state, and pain points of operations—and the 'downstream' (on-site implementation)—ensuring adoption at the workplace. The people who understand these two ends best are none other than the on-site staff. Therefore, the session emphasized that 'on-site staff × generative AI' can enable end-to-end execution from requirements definition to implementation.

- The bottleneck is now 'what to build' = problem discovery

Now that building applications takes only a moment, the source of value has shifted to the precision of listening—specifically, the ability to discover problems. What companies previously paid external vendors for was not the code itself, but the 'labor cost of translating pain points into buildable formats.' This capability has now returned to the hands of on-site teams. IPLoT introduced structured methods for problem discovery, treating it not as talent but as a repeatable process, including AS-IS/TARGET/GAP articulation and deep-dive questioning techniques.

- Only on-site staff know the 'unwritten processes' missing from documents

Unwritten arrangements not documented in manuals, or tacit knowledge such as intuition and know-how stored in people's minds—on-site staff possess this 'unwritten work' (tacit knowledge). Because they understand these hidden processes better than AI or vendors, they can create truly effective business systems that neither AI nor external vendors could build.

## 'AI Strategist Training' — Systematizing the Session's Insights

Traditionally, 'people who can structure business processes' and 'people who can implement with AI' were separate roles. IPLoT's 'AI Strategist Training' integrates both into a single role, cultivating personnel—'AI Strategists'—who can end-to-end execute the process of 'finding problems → articulating them → shaping them with AI' through a corporate training program.

- PHASE 1: Articulating Business Processes — Problem discovery, interviewing, AS-IS/TARGET/GAP analysis, requirements definition. Converting veteran intuition into reproducible procedures.

- PHASE 2: Shaping with AI — Using Claude Code to turn articulated business processes into working systems on the spot. Enabling on-site teams to build independently without relying on external vendors.

While typical AI tool training focuses on 'operations' and 'tips,' IPLoT's program uniquely includes the upstream capability of 'identifying what to build.' The company applies 'business structuring techniques' refined in IT consulting to promote sustainable AI adoption. The training is accessible even to those without programming experience.

## Service Details

## Security Considerations

Regarding data handling concerns in business AI use, the session explained that 'with Claude Code (API/business use), input data is not used for model training by default,' 'using Amazon Bedrock or Google Cloud Vertex AI allows processing to remain within the company's own cloud environment,' and 'small-scale implementation is possible within existing internal security policies and access controls.' IPLoT also provides secure implementation support, including environment setup, operational design, internal policy creation, and AWS/Bedrock integration.

## CEO Statement

"The most important message from our session was that 'building now takes an instant, so the real challenge is what to build.' As AI takes over implementation, the remaining human value lies in accurately identifying and articulating on-site pain points. We have honed this capability as a technical skill in IT consulting. The 'AI Strategist Training' empowers every individual within an organization to embody this skill. Don't overcomplicate it—start with one person, one application. Together with our corporate clients, we will continue building environments where on-site teams can shape AI into tangible solutions without relying on external vendors." (Kazuyuki Jinbo, CEO, IPLoT Co., Ltd.)

## About IPLoT Co., Ltd.

IPLoT operates under the mission 'Unleashing individual talent through technology and language,' offering IT consulting, AI business system development, packaged products, and AI Strategist Training. The company's unique business model is built on a dual-cycle approach: transforming on-site expertise from individual client projects into scalable SaaS products, then feeding insights from these products back into customized development. Leveraging its end-to-end experience from requirements definition to on-site implementation, IPLoT supports sustainable AI adoption that continues to be used in real workplaces.

Company Name: IPLoT Co., Ltd.

Representative: CEO Kazuyuki Jinbo

Headquarters: 1-11-4 Hiroo, Shibuya-ku, Tokyo

Business Activities: IT Consulting / AI Business System Development / Packaged Products / AI Strategist Training

Corporate Website: https://www.iplot.jp/

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