Automation index
How much of a Props master’s job can AI already do?
A props list comes earlier. The object being there, working and not breaking on stage do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Props master
19%
AI can already do 19% of this job.
#479 / 633
View rankingProps master
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
List, references and the budget.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Make, adapt and the one that will not fit the hand.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Rehearsal, the change and the one that vanishes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Show, tables and the preset.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The actor, the whim and not improvising the weapon.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
That it is there, and not breaking on stage.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 19% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- props lists
- presets
- adapt objects
- props rehearsals
- show tables
- stage weapons
- references
- props budget
Sources for this job· O*NET 27-1027.00· ESCO/ISCO 3435
IS WORK OVER?
Prompt engineer
34%
#21 / 633
View rankingPrompt engineer
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512