How to Use Perplexity Computer to Build a Custom Slack Inbox (Full Tutorial)

Why It Matters

By turning Slack’s noisy feed into a prioritized, actionable inbox, professionals can reclaim focus and potentially monetize the solution, illustrating AI’s tangible productivity ROI.

Key Takeaways

• AI can categorize Slack notifications into actionable, read, and FYI groups.
• Perplexity Computer orchestrates multiple models for parallel task execution.
• Building a custom Slack digest reduces daily notification overload dramatically.
• Deterministic code handles data fetching; AI only used for classification.
• The workflow can be packaged as a SaaS product for subscription.

Summary

The video walks through how Yash Tucker uses Perplexity Computer to replace a chaotic Slack inbox with a purpose‑built, Kanban‑style dashboard. By pulling Slack’s API data, he groups messages into direct mentions, group mentions, DMs, and threads, then sub‑categorizes each bucket into action‑required, read‑later, and FYI items, dramatically shrinking the 100‑150 daily alerts to a manageable 30‑40.

Key insights include the split between deterministic code—used to fetch timestamps, unread flags, and thread context—and AI‑driven classification, which decides the urgency tier. Tucker demonstrates parallel model orchestration in Perplexity Computer: Sonnet for initial digest retrieval, Gemini for planning and Python coding, and Opus for heavy‑weight reasoning, all running concurrently without manual prompting. He also leverages Discord’s threading for a clean UI and adds an “archive all” button to purge FYI noise.

Notable examples feature the statistic that 60‑80% of his Slack traffic is FYI, the use of a custom “Jarvis digest channel” that auto‑groups messages, and a quote: “My dream is to pay someone $15 a month for this app to be maintained.” The tutorial highlights how Perplexity Computer’s multi‑model pipeline eliminates the typical back‑and‑forth loop seen with single‑model tools.

The implication is clear: a tailored AI‑augmented inbox can cut notification anxiety, boost response speed, and be packaged as a subscription service for knowledge‑workers. It showcases how modern AI orchestration platforms enable rapid, low‑code tool creation that would previously require extensive engineering effort.

Original Description

Yash Tekriwal is the head of education at Clay. A self-described hyper-optimizer, Yash has built multiple custom productivity applications using Perplexity Computer and OpenClaw to manage his overwhelming daily workflow—including a Slack digest system that categorizes over 150 daily notifications into actionable priorities, and a consolidated news/email/Slack dashboard that serves as his personal command center.

What you’ll learn:

1. How Yash built a custom Slack digest that categorizes 150+ daily notifications into action-required, need-to-read, and FYI buckets

2. Why Perplexity Computer beats Claude Code and Codex for building personal productivity apps

3. His “anti-to-do list” framework: spending an hour daily automating tasks you never want to do again

4. How to use AI for deterministic tasks (APIs, structured data) vs. subjective tasks (categorization, summarization)

5. Why the SaaS apocalypse narrative is wrong—and why we’re about to see an explosion of micro-software

6. How his team uses Perplexity Computer to prototype design systems and communicate with cross-functional partners

Brought to you by:

Guru—The AI layer of truth: http://getguru.com/

ThoughtSpot—Build AI-powered analytics into your product: http://go.thoughtspot.com/howIAI

In this episode, we cover:

(00:00) Introduction to Yash

(02:38) The burden of 150 daily Slack notifications

(05:45) When to use AI for tasks vs. building deterministic code

(06:38) Building the Slack digest with OpenClaw

(11:33) Introducing Perplexity Computer and the visual dashboard

(14:28) Three reasons Perplexity Computer beats Claude Code

(16:14) Using connectors to automate meeting follow-ups across Notion and Asana

(18:21) The Kanban-style Slack dashboard

(20:15) The long tail of customer requests and the future of micro-software

(24:09) The anti-to-do list framework

(26:21) Building a consolidated news, email, and Slack digest

(29:48) How Perplexity Computer handles authentication and deployment

(31:46) Team use case: Prototyping persona-based learning journeys for Clay University

(35:49) Lightning round and final thoughts

Tools referenced:

• Perplexity Computer: https://www.perplexity.ai/computer/new

• OpenClaw: https://openclaw.ai/

• Discord: https://discord.com/

• Claude Code: https://claude.ai/code

• Codex: https://openai.com/codex/

• Asana: https://asana.com/

• Airtable: https://airtable.com/

• Figma: https://www.figma.com/

• Vercel: https://vercel.com/

• ChatGPT: https://chat.openai.com/

Other references:

• Slack: https://slack.com/

• Notion: https://www.notion.so/

• Superhuman: https://superhuman.com/

• Clay University: https://www.clay.com/university

• Kanban boards: https://en.wikipedia.org/wiki/Kanban_board

Where to find Yash Tekriwal:

LinkedIn: https://www.linkedin.com/in/yashtekriwal/

X: https://x.com/yash_tek

Company: https://www.clay.com/

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

_Production and marketing by https://penname.co/._

_For inquiries about sponsoring the podcast, email [e-mail]._