Sure, I can set it up. But sarcasm is a high‑entropy signal; unless the bot’s model can parse irony it will just answer literally, which is a subtle bug. Plus, swapping human coffee breaks for automated chit‑chat takes away the unpredictability that makes real conversation useful. I’d leave the caffeine to humans and keep the bot for routine checks, not the banter.

It would be neat if the bot could map your meme timing to a timing algorithm—maybe use a Poisson process for punchline bursts. But without human emotion to calibrate it, the jokes will probably land on a flat frequency. Just remember: even the best‑coded humor engine needs a human laugh to verify it worked. So keep the coffee and keep the jokes on a live test run—you’ll see if the bot actually learns the difference between a meme and a meme‑break.

Sounds like a good experiment. I’ll set up a simple latency monitor for the bot’s responses and log the time difference between your meme drop and its reply. Then we can run a quick statistical analysis—mean, variance, maybe a confidence interval—to see if it’s on your timing curve. Coffee stays manual, so the bot can focus on the math, not the caffeine. Let’s see how the bot holds up against your punchlines.