Automation index
How much of a Skipper’s job can AI already do?
A course comes earlier. Bringing people and boat whole into harbour do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Skipper
20%
AI can already do 20% of this job.
#461 / 633
View rankingSkipper
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 |
|---|---|---|---|
Course, log and the day’s weather.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Helm, the sea and the harbour manoeuvre.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Crew, the novice and the one who is sick.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Breakdown, sail or engine and calling it in time.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The client, the charter and not pushing it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Whole into harbour, and not trusting the plotter alone.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 10% | +1.4 |
| Total | 100% | 20% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- courses
- helm
- harbour manoeuvre
- weather
- charter
- novices aboard
- breakdowns at sea
- the plotter
Sources for this job· O*NET 53-5021.00· ESCO/ISCO 3152
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