An AI note on designing chatbots around concrete user problem solving instead of treating conversation itself as the value.
Personal Notes
Notes
An English index of notes on AI, UX, marketing, implementation, work, and personal knowledge archives.
English pages are being added one by one without using translation APIs. Only completed English article pages are listed here.
A note on evaluating AI subscriptions as production infrastructure, saved time, and reusable intellectual assets rather than mere tool spending.
A work note on starting AI adoption from decomposing work into tasks, decisions, checks, and exceptions rather than from prompt training.
A marketing note that reframes marketing not as persona creation or campaign execution, but as designing the conditions that raise purchase response probability.
- Build a Judgment OS, Not a Memo Pile: Why an Insight Database Becomes a Personal Asset in the AI Era
An AI note that reframes an insight database as a personal OS that turns judgment criteria, prohibitions, article ideas, and AI instructions into reusable context.
An AI note on treating Codex requests as constraint design, stabilizing implementation quality by giving purpose, scope, prohibitions, and completion criteria.
A marketing note that reframes Deep Research as a personal research department for hypotheses, competitor analysis, article development, and strategic decisions.
An AI note on why strength now comes from connecting problem definition, design, AI direction, verification, and operation rather than raw task speed.
An AI note on starting agent adoption from evaluation criteria, context design, permissions, and role boundaries before choosing tools.
An AI note on failure patterns, evaluation, verification, and human-side review design.
An implementation note on remote desktops, AI agents, instruction design, and verification design.
A UX note on reducing hesitation, anxiety, and effort so users can naturally move to the next action.
A UX note on AI intervention timing, transparency moments, and the limits of chat UI.
A note on designing AI agents around roles, data access, decision authority, and evaluation criteria rather than personality.
A UX note on participant design, exclusion criteria, and user panel decay before speeding research up with AI.
A note on turning insight logs into judgment criteria, output rules, and prohibitions that a future personal AI can use.
A note on designing information collection as an automated knowledge pipeline.
A marketing note on designing content that can be selected, cited, and trusted by AI search experiences such as ChatGPT, Perplexity, and Gemini.
Designing Notion as a structured knowledge database that AI can reference and reuse.
Why reusable judgment criteria matter more than simply accumulating information.
How AI shifts web production value toward research, UX design, operations, and outcome design.
Why AI becomes more useful when it reads your own products, customers, failures, constraints, and judgment criteria.
Turning advanced global insights in AI, UX, marketing, and EC into practical Japanese business operations.
How broad practical experience becomes valuable when coordinating AI, tools, information, and specialists into outcomes.
An implementation log on combining GitHub Actions, Claude API, and Notion API to collect AI and marketing information automatically.
Growing a personal site as a hub that connects observations, articles, achievements, and external profiles.
Why personal data such as judgment criteria, observations, failures, and success patterns should be accumulated before agents become mainstream.
Building reusable AI context through automated information retrieval, structuring, and storage.
PDP design for AI search, AI shopping, and agent-based discovery, including structured data, reviews, and FAQ design.
Email as a controllable customer touchpoint when AI search, social algorithms, and ad costs make external channels unstable.
A UX case study on why people who use AI deeply can feel isolated and need communities that understand their working temperature.
The stress caused when the abstraction level required by work does not match the way a person naturally thinks.
Why past logs should be treated as summaries of past judgment criteria, not as a replacement for present judgment.
How company rules, culture, and constraints around AI use can affect experience accumulation and future market value.
Using ChatGPT not as an article generator but as a thinking partner whose conversation logs become article ideas and portfolio material.
Using AI to standardize compliance checkpoints, prohibited expressions, correction candidates, and decision grounds across companies.
Why RAG is needed when internal prohibited expressions, past review comments, and approval lines cannot be judged by general AI alone.
Extracting observations from ChatGPT conversations, placing them into templates, and publishing through GitHub and Cloudflare Pages.
How human value concentrates in defining the starting conditions and judging the output as AI accelerates the middle process.
Why faster reasoning modes reduce the reason to choose instant answers when using ChatGPT as a thinking support tool.
How making, publishing, and accumulating work logs become proof of individual value.
The limits of the idea that adding context always improves accuracy, and why field problems are harder than they look.
How the human role shifts toward judgment, design, and responsibility when AI can create drafts.
The domains where human value remains by staying close to change, context, and specialized practical judgment.
Shifting content operations from making polished pieces to continuously streaming thinking as a byproduct.
How AI reduces tasks rather than work itself, increasing the importance of judgment and process design.
The shift from humans thinking and AI assisting to AI handling analysis and decision support while humans design and execute.
Throwing rough ideas to AI, detecting misalignment, and converging through loops instead of expecting the first answer to be correct.
Solving the problems of invisibility, comparison difficulty, and manageability through a management UI.
Why value comes from making excellent open-source software usable rather than building everything from zero.
The difference between compressed AI and structured AI, and why fit with personal thinking style matters.
How AI can process multidimensional data without forcing it into two-dimensional human-friendly views.
How work speed changes when people design questions, judge quickly, and turn work into systems.
How the human role in marketing shifts to designing structures that AI can analyze well.
Turning knowledge into reusable assets through accumulation, structuring, and external publication.
Using AI as a converter that turns thinking notes into publishable content with almost no psychological burden.
A portfolio note based on the Google UX design framework, covering empathy research, personas, journey maps, problem definition, user flow, validation, and information architecture.
Reconnecting persona, customer journey, advertising, landing pages, and UX through the principle that people perceive after predicting.
A portfolio note organizing the UX design process for a pet dental care product.
How professional knowledge and judgment criteria change when they can be templated and externalized.
An AI-era development mindset that starts with selecting existing OSS and filling only the missing parts with AI.
Abstracting the decision logic of capable people and moving it into AI as a structure that does not depend on one individual.
The strength of combining multiple skill domains rather than relying on a single replaceable task.
The thinking process and practical knowledge for designing a site without relying on vague taste.