Four months of running my own automations, 1,327 runs, published in full
Most people selling AI have never operated it at scale for longer than a demo. Before I sold a single automation I ran a fleet of them on my own work and life, logged every run, and watched what broke. This is that log, with nothing flattering removed.
Between August 2026 to August 2026, O'Donnell AI's automation fleet logged 1,327 runs across 152 jobs, holding a 95.6% success rate over the most recent 30 days. The record includes a failure spike to 4.4% in August 2026, when a silent backend change broke most jobs before it was caught and reverted. Full live telemetry is public at odonnellai.com/research.
The month it fell apart, and what fixing it proves
Reliability was not a straight line. It is worth showing you the worst month, because how a fleet behaves when it breaks is the only honest measure of whether it is watched.
| Month | Success | Volume | |
|---|---|---|---|
| August 2026 | 95.6% ok | 1,327 runs |
In August 2026 the failure rate hit 4.4%. A backend change had quietly broken most of the fleet, and because the jobs still ran and still logged, nothing screamed. That is the exact failure class that costs a business real money: not a crash you notice, but a system that keeps going through the motions while the work silently stops.
It got caught, the change was reverted, and August 2026 came back to 95.6%. That recovery is the entire pitch for the Operations Watch: every run checked against rules written for your work, so a silent break is a same-day fix instead of a month of quietly lost output.
Automations do not fail the way people fear
Across all 1,327 runs, here is every way a job ended up as something other than a clean success. Most failures are boring and recoverable, which is the point: caught early, they are maintenance, not disasters.
| Failure mode | Count | Share of all runs |
|---|---|---|
| Hard failure, the job errored out | 29 | 2.2% |
| Degraded, ran but the output was below par | 12 | 0.9% |
| Timeout, ran past its time limit | 1 | 0.1% |
A typical substantive run finishes in about 3 seconds. The failures above are why a build without watching is a liability: an expired token or a quiet rate limit will stop real work and never send up a flare on its own.
Not all of it is work. Some of it is just my week.
Inside the fleet is a small set of jobs that have nothing to do with business: they book my golf inside hard money limits, plan our meals, and handle date-night logistics. 15 runs across 3 of these personal jobs. It is the honest preview of what a Personal Fleet looks like when the same discipline points at a household instead of a company.
The method, so you can trust the figures
Every job writes one line to a run log the moment it finishes: what ran, whether it succeeded, and how long it took. This page reads that log at the instant the site is built and recomputes every number above, so what you are reading is never more than a deploy old.
Two honesty notes. First, the 1,327 total includes high-frequency system heartbeats that keep content fresh; strip those out and 1,270 were substantive task runs, which is the number I stand behind. Second, this fleet also runs work I cannot publish, so the personal slice above is named job by job while the rest stays an aggregate. No figure here is estimated, projected, or rounded up to look better.
WINDOW 2026-08-09 TO 2026-08-27
1,327 RUNS · 152 JOBS
RECOMPUTED AT BUILD · AS OF 2026-08-27
LIVE FEED: public telemetry
Questions about the data
How many AI automations does O'Donnell AI actually run?
Between August 2026 to August 2026, the fleet logged 1,327 runs across 152 distinct jobs, of which 1,270 were substantive task executions (the rest are high-frequency system checks). Around 152 jobs are active in any given month.
What is the automation success rate?
All time it is 95.6%, dragged down by one bad month. Over the most recent 30 days it is 95.6%. The gap is the story: reliability is a thing you operate, not a thing you install.
Is this data real?
Yes. Every figure on this page is computed from the fleet's own run log at the moment the site builds, and the live telemetry is public. Numbers are rounded, never rewritten.
Want a log like this for your own work?
That is what the audit finds and the Operations Watch keeps honest. Tell me the job that eats your week and you get a straight answer within one business day.