The cost of context switching has been studied for decades, but the AI tools we use every day have made it newly expensive. Each new chat is a blank slate. Each session starts by re-explaining the project. Each new tool needs to be told what we already told the last one.
Where the tax shows up
It shows up in three places. First, in the time it takes to reload context. pasting summaries, attaching files, recalling decisions. Second, in errors of memory: the prompt you used last week is gone, so you write a worse version of it. Third, in inconsistency: the explanation you give to ChatGPT diverges from the one you give to Claude, and the outputs diverge with it.
None of those costs are necessary. They're side effects of a product category that hasn't solved memory yet.
What gets it back
The cheapest fix is structural. Decide what about a project deserves to be carried forward. the summary, the active decisions, the prompts that worked, the citations you'll defend. and write it down once. Not in a chat sidebar. In something that survives the session.
That “something” is project memory. Shelvia is built to be that something. But you don't need Shelvia to start. A Markdown file in a repo, a Notion page, a single living doc. they all beat reloading from scratch every Monday.
The compounding effect
The reason this matters more than it used to: AI tools compound. The prompt that produced something useful last quarter is leverage you can use again. The decision you made and the source behind it are defensible artifacts in a future review. Without memory, that leverage stays invisible. With memory, it becomes a moat.
The work you do inside AI tools deserves to compound. Stop letting Mondays start over.
