AI Power User Benchmarking with SigRank

Everyone who uses AI coding tools regularly eventually wonders the same thing: am I actually good at this, or am I just using it a lot? There's a difference. Some developers burn through tokens re-explaining context and pasting files the model already read. Others build cascades that compound — lean input, heavy cache reuse, high output. The first group uses AI a lot. The second group uses AI well. That second group is what we call AI power users.

SigRank gives you a way to know which group you're in — and a way to benchmark yourself against the field. This post walks through what an AI power user looks like in token-cascade terms, how to check your own class, and how to compare yourself against other operators.

What is an AI power user

A power user isn't someone who uses AI the most — it's someone who rewires their process around it. The difference shows up in three places in the token cascade:

SigRank's yield metric (Υ) captures all three in a single number. That's why yield — not token count — is the number that tells you if you're a power user.

Operator classes — where do you land?

SigRank classifies every operator into a tier based on their yield and cascade shape. The tiers describe the architecture of your token flow, not how much you spent:

• Burner — low yield, high input, little cache reuse. Uses AI a lot; uses it poorly. Tokens burn, signal doesn't compound.
• Builder — moderate yield, building cache depth. The middle of the distribution. Most serious operators land here after a few weeks of tracking.
• 10xer — high yield, high leverage, high velocity. The AI power user archetype: disciplined token architecture, heavy cache reuse, lean input. This is the tier power users aim for.

You can see your tier instantly — no account, no install — by pasting your token stats at /score.

How to benchmark yourself against the field

Knowing your own yield is step one. Benchmarking is where context comes from — your number in isolation is just a number. Here's the full flow:

# 1. Install the CLI
npm i -g sigrank

# 2. Record your cascade
sigrank me

# 3. Submit your signed snapshot
sigrank submit

# 4. Check the leaderboard
sigrank board --window 30d

Or, if you already have your token stats from ccusage or another tool, skip the CLI and paste them at /score to get your yield and class instantly. Then head to the leaderboard to compare:

• Υ Yield — your headline efficiency number versus the field.
• Class tier — Burner, Builder, or 10xer. Are you in the power-user tier?
• Global rank — where you stand among all ranked operators.
• Pillar ratios of the top decile — the gap between your leverage, velocity, and cache hit rate and the best operators. This is your roadmap.

What separates a power user from a regular AI user

It's not prompt engineering. Regular users can write great prompts and still have burning cascades — because they start every session fresh, paste context the model already has, and never let the cache build. Power users do something structurally different: they rewire their process around AI.

That rewiring shows up as three habits that yield measures directly:

1. They reuse cached context heavily. Long sessions per feature; the cache builds and cache-read compounds. High leverage.
2. They produce more output per input. They ask for whole modules, not snippets, and let the agent finish before reviewing. High velocity.
3. They keep fresh input lean. Reference files by path; write tight prompts; let the model ask questions. Low input — and since input is squared, this is the biggest lever.

Regular users do the opposite: fresh sessions, pasted context, small asks, verbose prompts. Same tool, opposite cascade. Yield is the number that tells them apart. For more on the common questions around this, see the FAQ.