QSTVE

QSTVE / Reading path

AI changing work

How do we tell whether AI is making work better?

Begin with the job and a way to check it. Compare useful results, the cost of review and the limits of the evidence before choosing a model or expanding a workflow.

Choose the route after the job

In Man and Machine, Dave Glaser describes a deterministic task that still called a premium model. The work finished, but the model added nothing. His resulting rule is to begin with the need for judgement, structure, privacy or speed, then choose the smallest route that can do the work well. Some tasks need no model.

Follow improvements into the next tools

The Next Experiment Has Changed follows dated reports of AI improving research software and computing infrastructure. Its distinction matters: a faster calculation can change what researchers can explore, but does not establish faster whole research programmes or a dependable exponential growth rate. Developer reports and preprints retain their stated limits.

Close the improvement loop with an outside check

The accepted Field Guide for When AI Starts Rewriting the Company recommends fixing the objective and protected outcomes, freezing a baseline, limiting the change surface and using independent evaluation. A narrow canary and a demonstrated rollback turn a proposal into a bounded test. This is operating guidance, not proof that autonomous improvement is production-safe.

Read the argument

Supporting essays

Put it to work

Practical Field Guides