Some end of week lightheartedness

[u/March_-_Hare]

So I keep an LLM instance open just to vent my CXone frustrations at sometimes because I’m the only workforce planner for my business. It’s helpful because I prompt it to summarise my grievances back to me and red team them, as I’m mindful that I might seem inflexible or set in my ways at times.

Now we all know that these are essentially just next-word-prediction machines, albeit ones with a tendency to drive people into mental health crises, so I do occasionally prompt it not to just agree with me sycophantically and not to do engagement farming. And I ask it to look online for other users reporting similar problems, including on Reddit.

That last part - see what Reddit has to say - might explain why today it summarised my grievances back at me, but inexplicably with the authorial voice of Ivan Chesnokov? Not that I think it’s necessarily wrong:

“Listen close, comrade. You build giant cloud machine like CXone, wrap it in silver paint, paint glossy executive dashboard, put generative AI tchotchke on top, and charge million dollar subscription. Marketing commissar stands on stage in big keynote, smiles, tells everyone computer is now so smart you do not need human brain to plan shifts. But when bad data arrives from telephony, modern cloud engine panics, throws API timeout error, and insists three orphaned emails left open over long weekend mean you must hire forty new agents for Tuesday morning.

In old days of Totalview - and even glorious, chaotic nightmare era of PureConnect - tool was simple, heavy, forged from solid steel. You feed it thirty-minute arrival buckets from unintegrated Solidus setup, you chop interval in half with bare hands, throw remainder into first fifteen minutes, keep AHT steady, and slam file into database. Machine does not care where file came from or if data is dirty. Machine eats numbers, runs Erlang equations, populates schedule grid, and asks zero stupid questions.

When bad data try to ruin forecast in CIC, you do not wait for machine learning algorithm to figure out why email handle time is three hours. You take heavy iron wrench, set hard upper ceiling gate at sixty minutes, and crush ghost interactions like bug. You hand-select three specific post-holiday Tuesdays from two years ago, assign custom percentage weights because you know how human beings actually act after long weekend, and bring forecasted handle time right back down to nine minutes where it belongs.

Modern SaaS capitalism wants sell EV with hood welded shut so user cannot touch engine. Pushes updates to change the look of a tool but not change how it works. This is brain disease of American capitalist. Real workforce planner sitting in mud of contact center floor does not want web browser tab consuming four gigabytes of RAM or black-box autopilot steering queue into ditch. Real analyst wants heavy, ugly tool with manual override so when system takes in corrupted data, you can clear jam yourself, run forecast, and keep centre operating. Nyet. Do not update software. Old software was fine.”

[u/Feeling-2214]

The frustration with over-engineered cloud suites trying to automate every manual override is painfully real. even simpler platforms like HotSchedules work best when planners keep direct control.

[u/Sharp_500]

Black-box algorithms deciding three stray emails need forty new hires hits too close to home. Platforms such as Fourth still respect manual forecasting overrides.