IS WORK OVER?

Automation index

How much of a Prompt engineer’s job can AI already do?

A prompt and an eval come earlier. Knowing when the model lies, and what must not be automated, do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Prompt 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.

TaskShareAIPoints
Design prompts, tools and chains.
Estimate

No public source provides a precise figure. This is our estimate.

24%58%+13.9
Evals, datasets and regressions.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Integrate with product and safety limits.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Talk to the business about a good output.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Watch hallucinations, bias and cost.
Estimate

No public source provides a precise figure. This is our estimate.

14%20%+2.8
Decide what the model gets, and what it does not.
Estimate

No public source provides a precise figure. This is our estimate.

12%16%+1.9
Total100%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

Mobile developer

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.

TaskShareAIPoints
Screens, API and offline state.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Store review, crashlytics and ANRs.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Real device, the notch and fragmented Android.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
CI, tests and the week's release.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Product, the redesign and not breaking what people use.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That it does not crash, and not ignoring the one-star.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%28%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • build apps
  • ship to stores
  • crashlytics
  • offline state
  • ANRs
  • mobile tests
  • fragmented Android
  • store review

Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2514

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