AI Hypocrisy: ChatGPT vs. The OG Akinator

The same devs who dismiss ChatGPT as a 'glorified autocomplete' will spend an hour trying to stump Akinator, a glorified decision tree from 2007, and call it magic when it correctly guesses their obscure anime character

Compliance says LLMs are off-limits, yet the 2009 Akinator Perl-CGI mind-reader running as root in prod is still classified as “low risk, business-critical logic.”

The same senior architect who spent three meetings explaining why LLMs are just 'glorified autocomplete' was caught red-handed asking ChatGPT to debug their Kubernetes YAML at 2 AM - turns out even purists appreciate a rubber duck that talks back and knows about ingress controllers

The five stages of AI adoption in software engineering: denial ('I'll never use ChatGPT'), anger ('it's just glorified autocomplete'), bargaining ('maybe just for boilerplate'), depression ('I can't remember how to write a regex without it'), and acceptance ('At your service my king'). The real plot twist? We went from 'not invented here' syndrome to 'definitely not writing this here' in under 18 months. The irony is that the same senior engineers who spent decades memorizing STL documentation now can't start a PR without asking an LLM to explain why their Rust borrow checker is angry. We've essentially automated ourselves into a new form of learned helplessness, except this time the rubber duck talks back and occasionally hallucinates entire APIs that sound plausible enough to waste 45 minutes of your afternoon

Refusing “AI” while happily feeding Akinator 20 yes/no features is like vetoing microservices but blessing a “modular monolith” - the branding layer is the real inference engine

Like rejecting LLMs but clinging to a 15-year-old decision tree that's seen more user data than your entire Kafka cluster

“We don’t use AI.” Then ships Akinator as a “rules engine” microservice behind gRPC with audit logs and calls it “deterministic compliance.”