LO
Game developer and designer — how we know
The page itself gives the judgements. This one gives what they rest on: which technologies bear on the work, how the estimate moved since language models reached the public, and the method behind both.
Which technologies matter here#
Four separate signals. They are deliberately not added together — a job exposed to two technologies is not twice as exposed.
How it got here#
The index is not a static number. This is where it would have sat at each capability checkpoint since ChatGPT — reconstructed, and labelled as such.
—— this stretch contains a verified event- - - no event in this stretch — reconstruction only0 = no task exposed, 100 = every task exposed
It starts at 22 because long before this chart, game engines, procedural generation of levels and terrain, and player telemetry already did part of the building and tuning. It climbs through the middle of the chart as code assistants and image and text generators reach prototyping, documentation and bulk text, and studios fold them into their pipelines. It flattens towards 48 because what decides a game — whether a mechanic is fun, and where the team is going — still needs people playing and arguing, and because players' and publishers' reactions to generated content slow its use in finished games.
A flat line is not a forecast of safety. It says which tasks automation has reached so far — the occupations that moved least here are the ones where the constraint is physical or regulatory, and both of those can change.
Method and sources#
- Assessment date
- 2026-10-25
- Basis of the task judgements
- 0 evidence-backed · 7 platform inference · 0 not enough evidence
- Verified events
- 0