Workflow decomposition
Define tasks, evidence, boundaries, and human responsibility actions before choosing tools.
Proof of capability
Proof: AI workflow product and delivery evidence
This is no longer just a personal portfolio. It shows the workflow decomposition, governance, security, eval, and delivery judgment behind the product experiments.
How the products prove capability
The TOEIC 880→990 library and SEC Filing Radar cover two different AI workflow boundaries: learning content and public-source data research.
Beta validation
TOEIC 880→990 Shorts Library
A quality-checked gallery of original TOEIC 880→990 short drills organized by Part 5, Part 6, Part 7, Listening, and Strategy.
Japan-based TOEIC 880+ scorers aiming for 950 / 990 as a career, promotion, or global-work signal
Live toolSEC Filing Radar
Enter a US ticker, find the SEC filings worth reading, and turn them into Chinese/Japanese source-linked briefs.
Cross-language US equity research, content research, consulting, company research
Design and delivery artifacts
These public-safe docs answer the questions an enterprise AI Agent effort must address before pilot.
Proof
Enterprise AI Agent case studies
Four public-safe cases across legacy browser automation, HR, finance, and operations efficiency.
WorkflowGovernanceMetrics
ProofPRD: HR Policy Inquiry Agent
Defines users, citation rules, human review, escalation paths, and success metrics.
PRDRAGHuman review
ProofADR: Enterprise AI Agent Runtime
A workflow-owned pattern with typed handoffs, least-privilege tools, and human approval gates.
ArchitectureRuntimeAudit
ProofMetrics and Eval Plan
Evaluates agents through business impact, task quality, review outcomes, reliability, and governance.
EvalsRelease gatesOps
Reusable method
The same core flow applies across learning products, public-data research, and enterprise agents.
1
Input
Local folder or public ticker
2
Parse
Structured evidence, source links, risks
3
Review
Human checklists and boundaries
4
Output
Report, brief, CSV, or next intent
Risk governance
Design for prompt injection, data leakage, over-automation, and audit events early.
Product validation
Use sample reports, click intent, beta users, and pricing hypotheses to test demand.
Multilingual delivery
Chinese, Japanese, and English serve different audiences rather than mechanical translation.
Want the latest articles and product thinking?
Posts will keep publishing notes on generative AI, business math, product validation, and AI workflows.