regex-log

Last updated: March 29, 2026

This task cost enough that weaver's overhead disappeared into the noise. $0.35 plain, $0.30 weaver. Both passed, weaver slightly faster. When a task already takes three minutes and costs a third of a dollar, a checkpoint and rewind are rounding errors.

Category: Text Processing · Difficulty: Medium · Verdict: neutral

What the task asks

Write a single regex that matches the last YYYY-MM-DD date on log lines containing a valid IPv4 address. Edge cases everywhere: February can have 29 days, IPs can't have leading zeros, things that look like dates (e.g., 1134-12-1234) aren't, and valid dates/IPs can't be embedded inside larger alphanumeric strings.

What happened without weaver

The plain agent spent most of its time thinking. Turn 1 was a massive output: 16K tokens of chain-of-thought reasoning about the regex structure. IPv4 lookahead, month validation (01–12), day validation (01–28/29/30/31 per month), greedy .* to match the last date, word boundary guards. Then it tested iteratively over 6 bash turns, fixing edge cases one at a time.

Eight turns total. All 27 test cases pass. $0.35.

The cost is high for such a short session because the output tokens dominate. The model essentially wrote a regex essay before producing the actual regex.

What happened with weaver

Checkpoint "start" (task requirements, output file path). Then the same kind of reasoning, spread across more turns. The agent built a test harness in Bun (regex syntax is compatible enough with Python re for these constructs), iterated on edge cases, and converged.

No time_lapse. The model never felt the need to rewind. There was nothing to rewind from: no exploration phase, no wrong turns, just iterative refinement of a single artifact.

Twelve turns, $0.30. The checkpoint and done() call added 2 turns of overhead but the model's output was more concise (13K vs 16K tokens), which more than compensated.

Why this is boring (and why that matters)

The $0.05 difference is noise. The 26-second time difference is noise. This task tells us almost nothing about weaver's rewind mechanism because the mechanism was never used.

But that is the data point. Not every task has an explore-then-execute structure. Some tasks are just "think hard, write one thing, test it." The regex task is pure reasoning. There's no codebase to explore, no files to read, no context to accumulate and then prune. The model thinks, writes, and iterates.

The interesting asymmetry: weaver used more turns but fewer output tokens. The model spread its reasoning across more responses instead of front-loading everything into one massive turn. I don't think the checkpoint caused this. It's more likely run-to-run variance in how the model chooses to structure its thinking. But it's worth watching across more tasks.

The lesson

Weaver doesn't help or hurt on single-artifact reasoning tasks. No rewind means no savings, but no overhead either (the checkpoint cost is negligible). The tool just sat there, unused, like a fire extinguisher in a kitchen where nothing caught fire.

This contrasts sharply with configure-git-webserver, which is also a "short, no rewind needed" task, but where the checkpoint ritual added meaningful overhead because the base cost was so low ($0.06). Here the base cost ($0.35) is high enough that the checkpoint overhead disappears into rounding error.

The takeaway: weaver's overhead is fixed (a few tool calls), so it matters more on cheap tasks and less on expensive ones. The fix-code-vulnerability and build-cython-ext sessions, which cost $0.14–$0.83, are where the rewind decision actually moves the needle.