Context is the bottleneck, not typing speed
When people first add an AI agent to their workflow, they expect the win to come from raw output speed. It rarely does. The agent can produce a function in seconds — but it spends most of its value guessing at context a human already knew.
The hidden tax of scattered context
Every time an agent has to reconstruct what a project already decided, you pay a tax:
- Conventions re-derived instead of remembered.
- Past fixes re-discovered instead of reused.
- The same explanation typed again into a fresh chat.
Multiply that across a team and several agents, and the bottleneck is obvious: it was never typing speed.
Put context where the work is
The teams that get leverage keep decisions, prompts, and history attached to the work itself — the ticket, the board, the linked PR — so the next agent (or teammate) starts with what the last one knew.
Fast output on the wrong context is just confident rework.
That’s the bet behind Flowie: shared memory and visible handoffs so the context never has to be rebuilt from scratch.