Personal AI Workflow Timeline

Track your yearly AI workflow experiments and see which skills the models have already absorbed

Problem

AI users' stacks change fast: prompt engineering two years ago, agent workflows last year, MCP and Skills this year. But hard-won usage experience quickly becomes a default model capability, making it hard to see which personal investments still hold long-term value.

Solution

A local-first tool where users log the AI tools, tricks and workflows they rely on each quarter, auto-generate a personal AI skill timeline, and cross-reference model changelogs to flag which practices are now native and which remain worth keeping.

Users

Deep AI users, indie developers, AI evangelists in tech teams, and workflow-tinkering productivity enthusiasts

MVP

Local entry of tools/tricks/workflows with timestamps; auto-generated timeline view; simple status labels (obsolete / still useful / watch); export to Markdown or shareable cards

Revenue

Free local tier + paid cloud sync and team edition (for team AI capability audits), around $5/month

Why now

Rapid model iteration makes personal AI skills depreciate fast, many people feel they cannot keep up, and a lightweight tool can clarify ROI without any model API dependency