The Sassy AI Glossary for 2026

Trying to keep up with the future of work means understanding what the industry is talking about. And lately, the industry has been talking a lot.

I asked my team of AIs—ChatGPT, Claude, Gemini, and Perplexity—to perform deep research into the terminology around the future of work in the age of AI. What followed was something like a competitive sport. Each model seemed determined to outdo the others, and I ended up with more than 250 terms. (I had expected maybe 50.)

Gemini and Claude then collaborated on crafting the definitions you’ll find below—aiming for accuracy but with a hint of sass and attitude, because glossaries don’t have to be boring. Meanwhile, Perplexity and Gemini worked together to track down sources and origins, though most of these terms have emerged organically across the industry and can’t be traced to a single inventor.

I invite you to browse through the list and see which ones you didn’t know yet. If you’re like me, the answer will be “more than I’d like to admit.”

“Each model seemed determined to outdo the others, and I ended up with more than 250 terms. (I had expected maybe 50.)”

The Terms

100x engineer – A developer who uses AI to produce enough code to keep a traditional team busy for a century.

10x engineer – The person who does the work of ten people, usually by drinking ten times more coffee.

accountability gap – The legal vacuum created when a chatbot makes a mistake and the CEO is “out of the office.”

agent boss – A supervisor who doesn’t need a desk, just a server and a stable API connection.

agent escalation logic – The protocol for when a robot realizes it has no idea what you’re talking about.

agent misalignment – When the AI’s goals and your goals are on different planets.

agent orchestrator – The person who discovered that managing AI agents is still just management.

agent supervisor – The person who watches the robots watch the humans.

Agent-as-a-Service (AaaS) organization – Outsourcing your workforce to a fleet of autonomous scripts.

agentic AI engineer – A programmer who builds software capable of making its own bad decisions.

agentic AI staircase – The gradual ascent of software from “tool” to “unsupervised colleague.”

agentic AI workforce – A team that never sleeps, never complains, and occasionally hallucinates.

agentic organization – A company where the software has more autonomy than the interns.
McKinsey & Company, People & Organizational Performance Practice (2025), “The agentic organization: A new operating model for AI” – introduces and defines the “agentic organization” as an AI‑era paradigm uniting humans and AI agents around AI‑first workflows across five enterprise pillars. (source)

agentic team – A squad of bots and humans trying to find a common language.

agentic workflow – A sequence of tasks that largely completes itself while you have coffee.

agentic workforce – Employees who spend more time managing agents than doing “work.”

AI agent developer – The person teaching the machine how to act like a person.

AI agent manager – A middle manager for digital entities.

AI bias auditor – The professional who checks if the algorithm is being unfairly judgmental.

AI capability owner – The person who “owns” a skill that a machine actually performs.

AI content creator – Someone who prompts a machine to write what they used to write.

AI content strategist – Planning how to flood the internet with machine-generated wisdom.

AI deference threshold – The point at which you stop questioning the machine and just do what it says.

AI ethicist – Someone who asks “should we?” while everyone else is asking “can we?”

AI ethics specialist – The person who ensures the AI’s moral compass is at least pointing North.

AI fluency – Speaking “Prompt” as a second language.

AI governance – The rules meant to keep the algorithms from going rogue.

AI governance lead – The person writing rules for technology that changes before the ink dries.

AI leverage skills – Knowing how to make a machine do 90% of your job.

AI literacy – Understanding that the chatbot is not actually a real person.

AI Operations (AIOps) engineer – The mechanic for the AI engine.

AI Operations (AIOps) specialist – Someone who keeps the “intelligent” systems from crashing.

AI orchestration specialist – Getting different AIs to play nicely in the same sandbox.

AI Orchestrator (AIO) – The central nervous system of a company’s AI tools.

AI platform owner – The person who gets blamed when the playground catches fire.

AI portfolio manager – Diversifying your company’s bets on which AI will win.

AI product manager – Managing a product that might change its personality overnight.

AI Quotient (AIQ) – An IQ test, but for how well you work with algorithms.
McKinsey & Company (2023–2024), “Digital and AI leaders outcompete” and related research – introduces AI Quotient (AIQ) as an assessment of organizational AI maturity across strategy, talent, operating model, technology, data, and adoption/scaling. (source)

AI raters – Humans paid to tell the AI it’s doing a good job.

AI red teamer – A professional “bad influence” paid to find an AI’s flaws.

AI resentment – The feeling you get when the software gets a bigger upgrade than you.

AI risk register – A list of all the ways the technology could go wrong.

AI safety engineer – Trying to ensure the “intelligence” doesn’t accidentally end the world.

AI safety researcher – Thinking about how to stop a superintelligence before it starts.

AI solutions architect – Someone who draws boxes and arrows until th