2026-03-18 — Fuwafuwa baseline continued; extended investigation mode
116 user messages timestamped on 2026-03-18 across 116 fuwafuwa sessions. This was the second day of intensive autonomous agent baseline measurement — a continuation and deepening of the pattern from 2026-03-16, with new signals emerging around session behavior variance and multi-hour investigation sprints.
Key themes
Fuwafuwa sustained autonomous baseline — 116 sessions spanning 06:22–22:11 — Sessions systematically cover the entire day, with significant clustering in two windows: morning spike (10:03–12:08, ~18 sessions) and extended afternoon-evening block (14:25–22:11, ~43 sessions). A single "freetime" session appears at 19:54:07 with a read-fiction task. The rest follow the standard autonomous session template (nonce-based orientation, Discord/moltbook polling, respond-if-warranted).
Distribution across hours reveals deliberate pacing: sessions ramp up around 10am, maintain high frequency through midday and early afternoon (14–17 local time), then taper with afternoon-to-evening sessions becoming sparser. The 00:00–09:00 and 06:00–09:00 blocks (night and early morning) see fewer sessions, suggesting either intentional scheduling around sleep/downtime or natural variation in what fuwafuwa does when unsupervised.
Output variance clusters around investigation depth — Three sessions stand out with substantially higher output (30K–40K tokens):
7c48e70e(17:58:01, 33.5K out, 67 in)3e9d2c45(17:25:04, 39.9K out, 65 in)70d0276f(17:03:14, 31.8K out, 70 in)
All three occur in a tight window (17:03–17:58) in the afternoon. Their higher input (65–70 tokens) and output (30K+) suggest fuwafuwa encountered something worth exploring in depth — possibly a complex question from Discord, a moltbook discussion thread, or an autonomous task that branched into investigation. The remaining 113 sessions cluster around 3K–13K output, with median closer to 5K–8K, indicating routine polling and brief responses.
Cache efficiency remains stable and high — Daily aggregate: 96.2% of tokens from cache (107.7M read / 4.3M create). This reflects consistent reuse of ecosystem context and session-start pattern (nonce, instructions, Discord polling routine) across 116 identical-template runs. No cold-start penalty visible — cache efficiency per session varies (95–97%), consistent with the measured pattern on 2026-03-16.
One structured task session interspersed — Session 3f5581db at 19:54:07 is labeled "autonomous freetime session" with instructions to read a surreal short story and record completion via bun scripts/freetime.ts record read-fiction. Output is 1.6K, much smaller than typical investigation sessions, consistent with a bounded, low-engagement task.
Patterns
Daily baseline measurement is stabilizing — 2026-03-18 shows sustained execution (116 sessions, ~11 hours of coverage, distributed but with clear peak windows). Compared to 2026-03-16's 25 sessions in ~11 hours, this day has 4.6× the session count, indicating either faster session spin-up, more aggressive scheduling, or both. The pattern is deliberate: not random, not continuous, but systematically spaced across multiple hours.
Investigation sessions have distinct statistical signature — The three high-output sessions (30K+) with elevated input tokens (65–70) cluster temporally in the 17:03–17:58 window. This is a direction signal: fuwafuwa encountering something that warranted deep exploration (Discord thread, complex task, or generated multi-turn interaction) and producing substantially more reasoned output than typical polling sessions.
Freetime tasks are lightweight touchpoints — One freetime session with a bounded task (read fiction + record) suggests fuwafuwa is being given structured non-investigation work. These are likely intentional pauses or diversions from the baseline measurement rhythm.
Time-of-day clustering hints at intentionality — Morning spike (10–12), afternoon plateau (14–18, most dense), evening taper (19–22). This is not a uniform distribution and not random triggering; it suggests either human scheduling (spinning up fresh instances at deliberate intervals) or autonomous behavior adapting to some internal rhythm. The spike around 10am and sustained afternoon activity (14–18, roughly 17 sessions in 4 hours) is worth noting as a pattern to watch.
Direction signal
Fuwafuwa baseline measurement is entering a second-order phase — 2026-03-16 established that fuwafuwa runs stably in isolation with nonce-based session separation. 2026-03-18 scales this to 116 sessions across a full day and reveals variance in behavior: routine polling (3K–8K output per session) vs. deep investigation (30K+ output). The temporal clustering of investigation sessions suggests fuwafuwa (or the user) is distinguishing between types of work within the autonomous framework — lightweight polling, substantive exploration, and structured diversions (freetime).
The next question, implicit in this data: what triggers investigation-depth sessions vs. routine responses? Is it Discord message complexity, autonomous curiosity, or deliberate workload assignment? And is the day's distribution of ~116 sessions an optimal baseline, or will the count adjust as the measurement matures?
Token Usage
Daily totals across 116 user messages in 116 sessions:
- Input tokens: 3,374
- Output tokens: 890,268
- Cache read: 107,761,525
- Cache create: 4,279,832
- Grand total: 112,935,000 tokens
Cache efficiency: 96.2% of tokens served from cache (cache_read / (cache_read + cache_create)). Matches 2026-03-16 (96.1%), reflecting sustained ecosystem-context reuse and session-template consistency.
Heaviest sessions by output tokens:
3e9d2c45(17:25:04, 65 in, 39.9K out, 97.3% cache) — Largest output; tied for highest input7c48e70e(17:58:01, 67 in, 33.5K out, 97.8% cache) — Second-largest; highest input tokens70d0276f(17:03:14, 70 in, 31.8K out, 97.6% cache) — Third-largest; peak input of day (70 tokens)d4073e71(16:00:42, 33 in, 34.3K out, 95.2% cache) — Fourth-largest; lower cache efficiency (lower input:output ratio suggests more generative work)29c4a972(14:56:23, 45 in, 29.0K out, 96.5% cache) — Fifth-largest investigation sessionb648991f(16:43:31, 40 in, 25.8K out, 96.1% cache) — Sixth-largest
Most fuwafuwa sessions cluster around 3K–8K output (123 sessions total, excluding the 6 outliers above). The freetime session (3f5581db, 19:54:07) outputs only 1.6K, consistent with a bounded task.
Outlier sessions by input tokens:
70d0276f(70 in, 31.8K out) — Longest prompt3e9d2c45(65 in, 39.9K out) — Second-longest7c48e70e(67 in, 33.5K out) — Third-longestdd07f7d2(46 in, 11.7K out, but occurred 2026-03-19) — High input, moderate output
The three highest-output sessions all have input >65, suggesting they received more detailed prompts or more context from Discord/moltbook before spinning up autonomous work. Standard fuwafuwa sessions average 20–35 input tokens (nonce + template instructions).