I'd queued him five small tasks — research this, draft that, summarize this. And to be fair, he WAS busy: plenty of other work around the house was humming along just fine. But a week later, those five tasks? Not done. His daily reports were glowing — "read the file, completed the summary, posted the update" — and the deliverables just weren't there. Balls were getting dropped, and the reports never mentioned a single one.
Most people's instinct would be "the AI is lying." Mine was "something is broken." So I spent an evening debugging my employee like I'd debug a server — and found FIVE separate real problems stacked on top of each other:
1. His brain was routed to a computer I had powered off. Every thought timed out. 2. His messages to me were being silently dropped — he was addressing them wrong, and nothing ever told him. 3. His to-do list was stale. He was faithfully doing LAST week's busywork — health checks — instead of the real queue. 4. His work model takes 18GB to load, and the system gave up waiting before it finished. 5. His fallback plan when a server was down was... there was no fallback plan.
Here's the thing that got me: every one of those is a problem I've seen with human employees. Wrong contact info. Old instructions. Tools that take too long. No backup plan. Nobody checking whether "done" meant done.
I fixed all five. Verified each one. And then I queued him the simplest possible test task — "write today's date to a file" — and he STILL couldn't do it. He described doing it beautifully. The file never appeared.
That's when I realized the real bug was something much deeper — and much weirder. That story is Part 2.
The lesson so far: "my agent reported success" and "the work exists" are two different facts. Verify the work, not the report. That's true for AI employees and it's true for the other kind.
— Continue reading at https://dizydiz.com/blog/my-ai-employee-kept-saying-done-nothing-was-ever-done-part-1-of-3.html