Making Slack Less Overwhelming
The Basics at a Glance
• Otter.AI
• Adobe Suite
• Google Workspace
• x1 Sr. Slack engineer
• x1 ML engineer
• No access to Slack's internal company data or resources
I've felt the weight of information overload
• 100% (5/5) test users successfully created a channel summary in under 60 seconds
• 80% (4/5) of participants said it would help reduce overload in their workflows
• Slack released a similar AI summaries feature 9 months later (early 2024)
Focus Restored: Turning Channel Noise into Actionable Signal
80% of users could see themselves using this daily & Slack launched a similar tool x9 months later
Before: Endless Scrolls
Hours spent scrolling through unstructured chatter and notifications to find project moving info.
After: Concise Summaries
Key updates, action items and files distilled and delivered in seconds so users can get back to work.
Validated by the Market: Slack Launched a Similar Solution as a Core Feature
Slack Users Were Drowning In Noise...
The avg. knowledge worker spends one day a week hunting for updates or the right person to help.
High-volume channels bury decisions in chatter. Power users send over 1000 messages daily.
Problem: From a User's POV
• Constant context-switching kills focus.
• Anxiety rises over missing key updates.
• Catching up feels like a second job.
Problem: From the Business POV
• The brand promise of productivity is threatended.
• It devalues the platform by creating more work
• It creates a major opening for competitors.
Meet Tanner, a Busy Product Manager
STEP 1: He fires up Slack: Introducing AI Channel Summaries!
STEP 2: He Can Choose Up to x5 Channels to Summarize
STEP 3: General Summary + Action Items Come Preselected
STEP 4: He Selects the Timeframe
STEP 5: He Pops Over to the Summary Inbox
STEP 6: He Shares Targeted Info (Not Adding to the Noise)
Want to see this feature set in action?
View Prototype >
Slack Overload Hits Job Roles Differently
& understand what was going on with AI (early 2023)
My Pragmatic Research Approach
Without access to Slack’s internal data, I relied on interviews, public research, and expert consults.
My 10+ years of scrappy, "figure it out as you go" freelance industrial design experience really helped me shine here.
I'm very comfortable working in low context environments finding the info I need to get to the next step and iterating my way forward.
INTERVIEWS (x5)
• How do different roles experience overload?
SECONDARY RESEARCH
SWOT - Competitor Analysis - Industry Trends
• Where's the business opportunity?
EXPERT TECHNICAL CONSULTS (x2)
• Is AI viable and what are the limitations?
Key Discoveries
Constant context-switching was killing focus time and mental clarity.
Users hacked together personal notes and screenshots because Slack search wasn’t cutting it.
of Channel Activity
Senior execs craved high-level reports that distilled channel activity without the deep dive.
Users were willing to try AI but doubted accuracy and seamless integration.
A Deep Dive: Raw Interview + Research Insights
The Perfect Storm: Key Trends Validating the Need
In early 2023 while 42% of companies were still just exploring AI, the launch of ChatGPT signaled a massive shift proving the tech was ready for mainstream business application.
SOURCE: IBM Global AI Adoption Index: 2023
A 2022 report found that 62% of companies lacked clear asynchronous-first policies, creating a major communication gap for teams spread across different locations and time zones.
SOURCE: Buffer, 2022 State of Remote Work Report
By 2022, 70% of organizations came to rely on workstream collaboration tools as their primary means of communication, leading to information overload and lost productivity.
SOURCE: CIO Magazine, 2021
“It quickly gets overwhelming. Setting up channels for specific projects / topics or DMs for specific convos helps, but I find that no matter what I do,
it becomes a chore to keep up with everything. ”
- Jesse K. / comment G2.com: Slack product review page
Strategy: Prepping to Explore Both AI & Conventional Solutions
The goal here was to create a versatile, strategic foundation before ideation. Using the Jobs-to-be-Done (JTBD) framework as you see below, I translated my research insights into sets of clear plans that would allow me to rigorously explore both AI-powered and conventional solutions to the problem. (Showing a brief example below)
(Story Maps = Research Insights --> Jobs to Be Done --> Loosely Defined Feature Sets)
Activities & outputs
Going Wide Exploring Ideas & Reducing Risk
Flexing Superpowers: From Dozens of Sketches to x2 Viable Concepts
This led to two promising directions:
1. AI CHANNEL SUMMARY TOOL: An on-demand tool allowing users to actively manage channel overload
2. "WELCOME BACK" DASHBOARD: An automated dashboard for users to passively catch up after time away
Technical Validation: De-Risking the AI Direction
To ensure my concepts were viable, I consulted two experts. A Sr. Slack Engineer confirmed the feature was feasible within their architecture. The ML Engineer provided key insights into model limitations, giving me valuable design context.
The Decision: Why an AI Solution Was the Right Path
• USER-DRIVEN: It directly solved the core user need for on-demand information filtering.
• TECHNICALLY VIABLE: Early engineering consults had already confirmed it's feasibility.
• BUSINESS SMART: It strategically positioned Slack as a leader in the emerging AI productivity space.
• EEXECUTIVE VALIDATED: It fulfilled a direct request from an executive for "daily channel reports" providing a clear north star.
“From a senior leadership level, I would have just liked daily reports on each channel. I wish there was a better way for Slack to report back to me at the end of the day.”
- Erin T. / Startup COO
Activities & outputs
Usability Testing: Validating a New AI Interaction
Concept to Clickable Test with x5 Users
I built a mid-fi prototype and ran remote usability tests with x5 Slack users to validate x3 key hypotheses:
• LEARNABILITY: Could users quickly grasp this new Al interaction?
• INTEGRATION: Does the feature feel seamless within the existing Slack experience?
• VALUE: Would it actually reduce overload, or was it just adding more noise?
Most Impactful Testing Change: Targeted Info Forwarding Options
The most significant core change I made was the approach to shareable summary content.
BEFORE: The prototype allowed users to forward a link to an entire summary.
AFTER: Sharing was restricted to only targeted sections, like a list of action items.
RATIONALE: During testing, I realized that forwarding an entire summary risked recreating the original problem: sending colleagues more noise. The project's core goal was to reduce information overload, not just shift it. Restricting sharing to high-value, targeted content ensures the feature remains a tool for clarity.
Other Key Updates From Testing
FINDING: The initial onboarding pop-up was a single, dense block of text, which 60% of users found overwhelming.
RATIONALE: This directly contradicted the project's core goal of reducing cognitive load, so I split the explainer into two shorter pop-ups.
FINDING: During testing, "Action Items" was the most sought-after and asked for information.
RATIONALE: To speed up the workflow and deliver immediate value, I made "Action Items" a pre-selected default, as voiced by of 60% of testers.
(80% Helped)
FINDING: 80% of users expressed anxiety about missing key information. My testing also revealed a need for an easily scannable inbox.
RATIONALE: To address this, I added Al-generated keywords under each summary, allowing users to quickly triage and find relevant content at a glance.
Key Testing Wins
Every tester (5/5) generated a summary with no errors, in under a minute proving the feature was highly efficient and had a low learning curve.
This represents a massive time savings vs. having to scroll through multiple channels.
4/5 testers responded extremely enthusiastically and expressed interest in using this daily as part of their Slack work ritual.
Users were responding positively and genuinely felt that a feature like this could help them.
Activities & outputs
From an Individual Problem to a Teamwide Challenge
One Tester Comment Changed How I was Framing the Problem
This was a critical "systems thinking" moment (one of my superpowers). Erin’s feedback reframed the problem from a personal productivity issue to a collective cultural one, rooted in the interconnected patterns of team communication.
“The big thing for me with AI is, if it becomes flat, and I can't push it forward to the next person, it's not as helpful if only I can engage with it.”
- Erin T. / Interviewee
Sanity Restored: Channel Summaries Buy Back Time
Key Results at a Glance
60 Seconds
Every tester (5/5) generated a summary with no errors, in under a minute proving the feature was highly efficient and had a low learning curve.
This represents a massive time savings vs. having to scroll through multiple channels.
Slack Releases a Similar AI Product
9 months after this project wrapped, Slack launched its own AI channel summaries feature (2024).
This confirmed the problem was a strategic priority and validating the relevance of my design direction.
80% of testers were excited at the prospect of actually using this feature in their day to day Slack workflow.
This was a direct tie back to the business goal of restoring confidence in Slack's brand perception of saving time.
9 Months Later: Slack Launches Their AI Summaries Feature in Early 2024
Slack AI channel summaries were announced months after I wrapped my project.
This was proof I had identified a relevant business and user need!
"Being able to pull your team's action items, share them, you're just eliminating such like a communication backlog..."
"It just saves you so much time from having to find all of those action items, write the email, send it out, etc."
- Erin T. - Startup COO
“I immediately see how this would impact me, I've got 14 channels and 50 messages each all with threads in those channels..."
"Having a tool that can capture the action items, and then summarize them would be super helpful.”
- Andrew T. - Product Manager
I Learned a Ton, Creating a New Feature End-to-End Working my Way Through a Big Ambiguous Problem
Overall Wrap Up
This project sharpened my ability to validate early, scope intelligently, and keep users at the center of every decision.
In my next role, I’ll bring that same approach to designing features that solve the right problems and deliver measurable value to both the business and the people using the product.
Lessons Learned
Speaking with a tester, Erin, reframed my understanding of the problem.
This led to a key change: users can now only forward targeted parts of summaries. This focuses on our core goal of reducing team-wide noise.
It's best to get a tangible product in front of invested stakeholders as early as possible.
Early convos with a Slack engineer and an ML engineer gave me the confidence and information to move forward with a solution that aligned with Slack's goals and would actually work.
Future Focus: Next Steps & Measurement
If launched, I’d track weekly feature adoption, summary creation frequency, and user satisfaction scores.
A/B testing summary formats and sharing options would help improve task success rates over time, ensuring the feature delivers measurable productivity gains.
I’d give users simple tools to rate the quality and relevance of each summary, creating a steady feedback loop.
Over time, this data could train the AI to surface more accurate and context-aware results, directly addressing evolving user needs and improving overall satisfaction.
Feel free to email blutjens@gmail.com or connect on Linkedin.
Check out my other work!
