Kefiw

Archived noindex page. Kefiw's public focus is Property decision help.

Archived page

This older Kefiw page is kept for reference, marked noindex, and removed from the primary sitemap. The current Kefiw experience is focused on property decisions: cost, quotes, damage, buying, selling, owning, and packets.

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What Task Switching Tax Calculates

Retention = 0.80^(n-1). Every context after the first costs 20% of remaining capacity.

Task Switching answers one question: how many of your day's hours survive the context overhead?

Every additional concurrent context costs 20% of remaining capacity, compounding. One task = 100%. Two = 80%. Three = 64%. By five, only 41% of the hours survive. Task Switching Tax shows the CPU split between productive work and the OS of juggling.

Quick answer

Task Switching answers one question: how many of your day's hours survive the context overhead?

What you are trying to do
Retention = 0.80^(n-1). Every context after the first costs 20% of remaining capacity.
Limit to remember
Treat this as a practical aid for the task, not a replacement for professional judgment.

Key points

  • Formula: retention = 0.80^(n-1). Loss = 1 - retention. Multiply by workday hours.
  • The 20% figure is a rough heuristic (Weinberg 1992 and later attention research) — exact percentage is domain-dependent but the geometric-decay shape is consistent.
  • When overhead ≥ 45%, you are running the OS, not the application. At n=4, 39% is already gone.
  • Batching crushes the tax. Consolidating 5 contexts into 2 time-boxed windows recovers ~40% of your day.
  • The tax is multiplicative, not additive. Two contexts at 50% each is NOT the same as one context at 100% — it is 80%.

Examples

  • n=4, 8h day
    Retention 51.2% → 4.1h effective, 3.9h switching tax.
  • n=2, 8h day
    Retention 80% → 6.4h effective, 1.6h tax.
  • n=6, 8h day
    Retention 32.8% → 2.6h effective, 5.4h tax. More than half the day is overhead.

When to use which tool

▸ Operational Thresholds
  • CYAN · STABLERetention above 64% (n ≤ 3) — overhead manageable, output matches hours.
  • GOLD · GUARDEDRetention 41-64% (n = 4) — tax significant; batch aggressively tomorrow.
  • MAGENTA · CRITICALRetention under 41% (n ≥ 5) — running the OS not the app; drop a context.
▸ Pivot
Fewer switches? Now measure the deep-work window that survives.
Deep Work Capacity · Focus Horizon →

Related

Frequently asked questions

Why 20% per task? Troubleshooting

Rough heuristic from attention research. The exact number varies by domain and individual, but the geometric-decay shape (each extra context costing a percentage of remaining capacity, not a fixed amount) is consistent across studies.

Does batching really help?

Massively. Consolidating 5 contexts into 2 time-boxed windows recovers ~40% of your day. This is why time-blocking works and Slack does not.

What counts as a "context"?

A distinct project, client, channel, or decision domain that requires loading different mental state. Email is not a context; email across 4 projects is 4 contexts.

How should I use a decision framework in real life? How-to

Use a decision framework to expose the tradeoff, not to outsource the decision. Write down the inputs, compare the output with your constraints, then ask what would change the answer. The strongest use is scenario testing: base case, conservative case, and failure case.

Is this financial, legal, or tax advice? Trust & accuracy

No, this is not legal, financial, tax, medical, or professional advice unless the page explicitly says that use case is supported. It organizes assumptions so you can inspect them. Verify high-stakes choices with qualified people who can review facts, contracts, regulations, and downside risk.