Single-project AI workflows are tractable. You have one CLAUDE.md , one context, one set of decisions. You brief the agent once, keep the session-state current, and it works. Multi-project workflows break this in three specific ways. Context bleed. You've been working on Project A all morning. The auth architecture, the deployment constraints, the open questions — all of that is live in your session. You switch to Project B. The agent carries residual context from A into B. It makes suggestions that would be correct for A but are wrong for B. Re-briefing overhead. You switch projects cleanly, but now you need to re-establish context for B from scratch. Fifteen minutes of re-orientation. You do this every context switch, several times a day. Decision contamination. You've made decisions on Project A that you're tempted to apply to Project B because they're fresh in mind — even though B has different constraints that make those decisions wrong. I run six simultaneous workstreams.…