Time Spent vs Token Efficiency

The short version

WakaTime is a time tracker. It measures how many hours your editor was active — a metric built for traditional coding, where you type the lines and time-on-task roughly tracks output. AI coding broke that assumption. When the model types the lines, your job is to drive it efficiently — and driving efficiency is invisible to a clock.

SigRank measures the thing that actually varies between AI operators: token cascade efficiency. An hour with good cache reuse and tight prompts can produce more signal than ten hours of re-sending bloated context. WakaTime would rank both sessions by duration. SigRank ranks them by Υ Yield — and the one-hour session wins.

Feature comparison

Time ≠ signal

The core disagreement between a time tracker and a cascade tracker is what counts as work. In traditional coding, work ≈ time × keystrokes. In AI coding, the model does the keystrokes — so work ≈ how efficiently you steered the model's token flow. Two operators, same hour:

WakaTime ranks Operator B higher — 10× the hours. SigRank ranks Operator A higher — 10× the signal per token. In a world where the model writes the code, the second ranking is the one that reflects skill.

Where time still matters: Velocity

SigRank doesn't ignore time — it demotes it to a denominator. Velocity = output / session_time measures how much signal you produce per unit time. That bridges the WakaTime view (productivity per hour) with the cascade view (signal per token). An operator with high Υ and high Velocity is the full picture: efficient and fast. WakaTime can only see the speed, never the efficiency behind it.

Frequently asked questions

Is SigRank a WakaTime replacement for AI coding?

They measure different things. WakaTime tracks how long you code — the clock. SigRank tracks how efficiently your token cascade flows — the signal. In AI-assisted coding, time spent is a weak proxy for productivity: an hour with good cache reuse and tight prompts can produce more useful output than ten hours of re-sending bloated context. SigRank is the AI coding tracker that measures the thing that actually varies between operators: token efficiency, not seat time.

Why is time a bad metric for AI coding?

In traditional coding, time-on-task correlates with output — you type the lines. In AI coding, the model types the lines; your job is to drive it efficiently. Two operators can spend the same hour and get a 10× difference in signal. One reuses cached context (cache_read) and produces high-leverage output; the other burns fresh input tokens re-explaining the same context every turn. Time measures the hour; Υ Yield = cache_read × output / input² measures who actually drove better during it.

Can I use SigRank alongside WakaTime?

Yes — they are complementary, not exclusive. WakaTime tells you how many hours you coded; SigRank tells you how efficiently you drove the AI during those hours. Together they answer "how much did I work?" and "how well did I work?" SigRank even computes Velocity (output tokens per unit session time), which bridges the two views — productivity per hour, measured in signal rather than keystrokes.

What does WakaTime not see that SigRank does?

WakaTime sees editor activity — file opens, keystrokes, language, project. It does not see the token cascade: how much input you sent, how much output came back, how much context you reused from cache versus re-paid for. SigRank reads exactly those four pillars (input, output, cache-read, cache-write) and derives the cascade architecture — Υ Yield, compression ratio, SNR, Leverage, and Velocity. That cascade is where AI coding efficiency lives, and it is invisible to a time tracker.

Does SigRank track time at all?

Yes, as one input to Velocity (output tokens per unit session time) — but time is a denominator, not the headline. SigRank's primary metric is Υ Yield, which is unitless and measures cascade efficiency independent of how long you sat there. An operator who produces more signal per token ranks higher regardless of whether they worked 20 minutes or 2 hours. Time rewards presence; Υ rewards driving.