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The Problem We All Share<\/h2>\n
If you work in a customer-facing role, you know the feeling. You open your laptop on Monday morning and you\u2019re staring at 150+ unread emails, dozens of Teams threads, and the creeping anxiety that something important is buried in there \u2014 a customer escalation, an exec ask, a deadline you forgot about.<\/p>\n
You start scrolling. You context-switch between Outlook and Teams. You open threads, skim them, lose your place, start over. Thirty minutes later, you\u2019ve read a lot of words but you\u2019re not sure what actually needs your attention right now<\/em>.<\/p>\n This is the inbox triage problem<\/strong> \u2014 and it\u2019s universal. Whether you\u2019re an account manager, a solutions architect, a PM, or an engineering lead, the signal-to-noise ratio in enterprise communication is brutal.<\/p>\n I decided to fix it.<\/p>\n Here\u2019s the insight: modern AI coding assistants like GitHub Copilot CLI<\/strong> and GitHub Copilot in VS Code<\/strong> aren\u2019t just for writing code anymore. Thanks to the Model Context Protocol (MCP)<\/strong>, they can connect to external data sources \u2014 including your Microsoft 365 environment.<\/p>\n MCP is an open standard that lets AI assistants call external tools. Think of it as a universal adapter: instead of building a custom integration for every data source, you expose capabilities through MCP servers, and any MCP-compatible client can use them.<\/p>\n One of those MCP servers is WorkIQ<\/strong> \u2014 a Microsoft 365 Copilot-powered tool that gives your AI assistant access to your emails, Teams chats, calendar, and documents. Combine WorkIQ MCP with GitHub Copilot CLI, and suddenly you can do things like:<\/p>\n <\/p>\n <\/p>\n All from your terminal. No browser tabs. No scrolling.<\/p>\n I started simple \u2014 a single prompt that asked WorkIQ to scan my inbox and categorize everything into three buckets:<\/p>\n It worked. But I immediately hit two problems that turned into engineering challenges.<\/p>\n When I asked WorkIQ to scan 3 weeks of email in a single query, it timed out. The M365 Copilot backend was processing too much data for one request.<\/p>\n Solution: Chunked queries with graceful fallback.<\/strong><\/p>\n Instead of one 3-week query, the workflow automatically breaks it into three 7-day chunks, runs them sequentially, and merges the results. If a chunk times out, it retries with a simplified prompt (top 10 items, shorter format). If that also fails, it falls back to a minimal query (top 5, one-liner summaries). If all three levels fail for a chunk, it skips it and notes the gap.<\/p>\n <\/p>\n This pattern is reusable for any MCP integration where the backend has processing limits.<\/p>\n When you run triage daily or weekly, the same items show up repeatedly. Worse, sometimes an item that was already resolved resurfaces because the underlying chat had new activity (someone reacted, or the group chat was opened).<\/p>\n Solution: A rolling JSONL index with AI-assisted dedup.<\/strong><\/p>\n Each triage run reads a persistent index file (triage-index.jsonl) that tracks every item ever surfaced \u2014 with its status (open, resolved, snoozed), when it was first and last seen, and resolution notes.<\/p>\nWhat If Your AI Coding Assistant Could Read Your Inbox?<\/h2>\n
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Building the Workflow: From Messy to Methodical<\/h2>\n
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Challenge 1: Timeouts on Large Lookback Windows<\/h3>\n
![\"Email](\"https:\/\/devblogs.microsoft.com\/all-things-azure\/wp-content\/uploads\/sites\/83\/2026\/03\/diagram-v4-hires-1-scaled.webp\")
<\/a><\/p>\nChallenge 2: Duplicate and Stale Items Across Runs<\/h3>\n