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

Agile coach

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
Boards, metrics and the cadence design.
Estimate

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

16%40%+6.4
The real retro and the elephant in the room.
Estimate

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

18%14%+2.5
Train, unblock and the manager who will not let go.
Estimate

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

16%32%+5.1
Scale, dependencies and fake agile.
Estimate

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

16%28%+4.5
Conflict, power and not selling extra frameworks.
Estimate

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

18%18%+3.2
That they stop faking it, and not inflating velocity.
Estimate

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

16%14%+2.2
Total100%24%

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

Skills and activities

  • retros
  • agile cadence
  • unblock teams
  • flow metrics
  • fake agile
  • agile training
  • dependencies
  • velocity

Sources for this job· O*NET 13-1111.00· ESCO/ISCO 2421

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