How we read the signal

Analysis frame

Evidence level

Mixed evidence

Analytical lens

Separate a decade-long occupational projection from present hiring and the entry-level training mechanism.

Affected groups
  • Aspiring and early-career developers seeking paid experience
  • Employers relying on experienced engineers and future talent pipelines
What remains unknown
  • BLS projections cannot guarantee annual hiring or isolate AI's effect
  • Stanford's relative shortfall spans highly exposed occupations, not only software development
Second-order effects to watch
  • Automating junior assignments can reduce the pipeline of experienced engineers
  • Demand for integration and verification can create new roles if employers train entrants

A forecast is not a hiring guarantee

BLS projects a 10% increase across software developers, quality-assurance analysts and testers from 2025 to 2035. It is a scenario based on labor-market assumptions, not a count of offers waiting for current students.

Watch the entry path

Stanford's payroll analysis finds a widening relative shortfall for young workers in highly AI-exposed jobs. It does not isolate AI as the sole cause. Track junior offers, paid apprenticeships, mentoring time and promotion into independent engineering work.

Primary trail

Go to the source

Read the evidence behind this analysis. External links open in a new tab.

CNBC — AI and software-developer jobs U.S. Bureau of Labor Statistics — occupational outlook, 2025–2035 Stanford Digital Economy Lab — young workers in AI-exposed occupations