Designing the Work You Do Every Day
A product designer at Toss Bank transformed her personal task-management routine instead of accepting repetitive manual work as unavoidable. She built an AI-powered desktop widget that collects Slack messages, summarizes them into actionable tasks, preserves their context, and helps her focus on prioritization. What began as a personal solution revealed a broader problem shared across roles and spread throughout her team. ## From Manual Task Tracking to Workflow Design - For two and a half years, she manually copied tasks, feedback, discussion links, and requests from Slack into Notion or Slack lists. - As her responsibilities expanded to three teams, daily tasks grew from roughly 10 to more than 20. - She reframed the issue as a product-design problem: - **User:** herself - **Real goal:** completing the most important work without missing anything - **Main friction:** copying, organizing, and locating context - **Ideal state:** tasks collected automatically, leaving only prioritization to manage - This led to three core requirements: - AI should register tasks directly from Slack. - Each task should retain its source thread and document links. - Priorities should remain visible in an always-present widget. ## Teaching AI to Understand Work Context - Adding a specific emoji to a Slack message sends it to a designated channel. - Claude Code reads the message and converts it into a task with: - A concise summary - The relevant team tag - A link to the original Slack thread - The hardest part was turning long, contextual Slack conversations into one clear action. - For example, a request about an error during a loan-extension application becomes “Check loan-extension error case.” - She created writing guidelines and examples defining: - What qualifies as a good task - How teams should be categorized - Which expressions and sentence structures to use - The goal was for AI-generated tasks to sound like something she would have written herself. - Refining the AI’s output was less about coding than encoding her judgment about what constitutes a real task. ## Designing the Widget Experience - Making the widget feel natural required detailed interaction design and repeated implementation. - She rebuilt the code to refine the expand-and-collapse behavior. - The drag interaction took nearly a week to complete. - Explaining seemingly obvious behaviors to AI forced her to define her own requirements more precisely. - In this sense, working with AI became a process of clarifying thoughts and translating them into explicit language. ## Replacing Anxiety with Prioritization - She no longer needs to open Slack or Notion repeatedly to remember her tasks. - The always-visible widget removed a previously unnoticed source of friction. - AI now handles collecting and organizing work, reducing the mental energy spent on administration. - She can concentrate on deciding what matters most instead of worrying that something has been forgotten. ## A Personal Problem Shared by the Team - Although the widget was initially built for personal use, many colleagues adopted it. - Developers unexpectedly became active users, reporting bugs and suggesting features. - The usual designer–developer relationship reversed: developers raised issues while she fixed and redeployed the tool. - This showed that task collection, prioritization, and context management are common problems across job functions. - The tool spread not because its concept was revolutionary, but because it addressed an existing, widely felt inconvenience. ## Applying the Method - Identify the most frequent “not really work” task from the past week: - Copying information - Searching for context - Organizing lists - Define the problem as a product: - Who is the user? - What are they truly trying to accomplish? - Where is the greatest friction? - What does success look like? - Examine why existing tools do not solve the problem. - Start with the smallest version that can be useful immediately. The practical lesson is to treat repetitive coordination work as something that can be designed away. Instead of searching for a perfect general-purpose tool, build a small solution around the specific context, habits, and judgments that existing products cannot know.
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