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.