ContextSwitch

Stop hunting for context. ContextSwitch reconnects your Slack, docs, and tickets so you always know where you left off.

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Inspiration

The idea for ContextSwitch came from a pattern I kept noticing in my own work and in conversations with friends in consulting, product, and engineering roles: the actual work of knowledge work isn't the hard part — it's finding where you left off. A single project might leave traces in a Slack thread, a Google Doc, a Jira ticket, and an email chain, with nothing connecting them. Every time you step away — for a meeting, a weekend, a different project — you pay a "reload tax" just to remember what you were doing.

I wanted to dig into why this still happens in 2026, when every individual tool has gotten smarter. The answer seemed obvious once I looked for it: each tool is smart within its own walls. None of them know about each other. That gap — not a lack of AI, but a lack of connective tissue between AI-powered tools — is what ContextSwitch is built to close.

What I learned

Researching this idea taught me two things I didn't expect going in:

  • The cost isn't really "time lost," it's cognitive. The productivity research I read points to context-rebuilding after an interruption being more draining than the interruption itself. That reframed the problem for me — this isn't a "save 10 minutes a day" pitch, it's a fatigue and focus problem.
  • The hardest constraint isn't AI, it's trust. Any product that reads across someone's Slack, docs, and tickets is, by definition, asking for a lot of access. Several of the people I talked to about the idea immediately asked "what do you do with my data" before "does it work well" — which told me the real product challenge is as much about read-only, transparent, no-new-habit design as it is about retrieval quality.

How I built it

Since this is an early-stage concept, "building" so far has meant designing the system rigorously enough that it's actually buildable, not just aspirational:

  1. Problem scoping — narrowing from a vague "unify all your tools" idea down to a specific, testable claim: can an AI agent cluster fragments from different tools into one coherent "work thread" without the user manually linking anything?
  2. Architecture sketch — a three-stage pipeline: Connect (read-only OAuth into existing tools), Index (embed messages, docs, and tickets so they can be matched by meaning, not keywords), and Recall (a retrieval step plus an LLM-generated, source-linked summary).
  3. Scope discipline — deliberately deciding what ContextSwitch is not: not a new place to write tasks, not a Slack/Notion replacement, not a tool people have to remember to update. That constraint shaped almost every other design decision, since adoption friction is the main reason similar "unified workspace" tools have struggled.
  4. Validation plan — designing the interview and proof-of-concept plan (starting with just two integrations, Slack + Drive) before any broader build, so the riskiest assumption — that AI clustering across tools actually produces useful results — gets tested early and cheaply.

Note: Built With reflects the proposed technical architecture for this concept-stage submission — no working implementation exists yet.

Challenges I faced

  • Resisting scope creep. The instinct with a tool like this is to integrate everything at once. Forcing the plan down to two tools for an MVP was harder than it sounds — every interview surfaced "oh, but what about email" or "what about Jira," and I had to keep coming back to: prove retrieval quality first, breadth later.
  • Designing for trust before designing for features. It would have been easy to spec out a flashy AI assistant UI first. Instead, most of my design time went into the read-only, source-linked, no-new-data-store approach — because without that, the product never gets past a security review, let alone a user's comfort level.
  • Avoiding the "yet another tool" trap. It's tempting to add a task list, a chat, a dashboard — anything to make the product feel more complete. The real challenge was staying disciplined that ContextSwitch's only job is retrieval and reconstruction, nothing more, because that's the only version of this idea that's actually likely to get adopted.

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