[ why built, not watched ]

AI raises the floor more than the ceiling. It still needs real human expertise.

Four things the research now says about expertise in the age of AI, and how SourceBoot is built in answer to each.

[ reviewed 2026-09-16 ]12 sources7 peer-reviewed

[ claim 01 · the floor ]

AI makes the routine part cheap.

In big field studies of support and coding work, the least experienced gained the most and the experienced gained little. Routine competence is no longer scarce.

+26%

More tasks completed with Copilot across three company trials, with larger gains for less experienced developers.

peer-reviewedCui et al. · Management Science2026 · n = 4,867

≈ experts

On the writing task, marketing specialists with AI all but matched the AI-aided in-house writers. The group furthest from the skill did not move: you need enough to refine the output.

reportHarvard Business Review2026-03 · n = 78

[ claim 02 · the ceiling ]

Past the routine, AI needs a judge. Judgment is expertise.

Outside what the model can do, using it makes people worse, and the line is not obvious. Those who did better judged the output rather than taking it.

−10% high performers: likely +15%

The same GPT-4 advisor: low performers lost, high performers likely gained. The gap came from which advice each chose to act on.

peer-reviewedOtis et al. · Management Science2026 · field experiment, Kenya

319 surveyed

Knowledge workers surveyed: the more they trusted the AI, the less critical thinking they reported. Confidence in their own skill ran the other way.

peer-reviewedLee et al. · Microsoft Research & CMU, CHI2025

[ claim 03 · the rung ]

The rung you used to learn on is being pulled up.

Expertise used to be built in the entry-level years. In AI-exposed jobs and at firms adopting AI, the youngest workers are falling behind and the experienced are not.

≈ −9%

Junior employment at firms adopting generative AI, relative to non-adopters, after six quarters. Senior employment at the same firms kept growing.

working paperHosseini Maasoum & Lichtinger · Harvard2026 · 65M workers, résumé data

−65%

Entry-level hiring at the twelve companies SignalFire calls the Tech Majors, since 2019. Their advice to new grads: demonstrate proof of work before anyone gives you permission.

reportSignalFire · State of Tech Talent2026-06

[ claim 04 · the practice ]

Lean on AI while you learn and you learn less. Unless it gives hints, not answers.

Randomised trials in code and in mathematics agree: with a model handing over answers, people do worse on the test. In maths, hints instead of answers largely removed the harm.

−17 pts 50% vs 67%

On a comprehension quiz, for developers who learned a new library with an AI assistant to hand. No significant speed-up either.

randomised trialAnthropic2026-01 · n = 52

−17% hints arm: ≈ 0

On the exam, after practising with a model that gave answers. The hints-only arm, built on teachers' solutions, largely removed the harm.

peer-reviewedBastani et al. · PNAS2025 · n ≈ 1,000

[ built in answer ]

AI spins it. Expertise pins it.

[ pin 01 · the floor ]depth, in order

A path carries its own prerequisites, so you go deeper rather than wider.

[ pin 02 · the ceiling ]graded by running it

Every lab is graded by building and running your code on your own machine. sboot submit runs the same checks as sboot test; we compute the verdict.

[ pin 03 · the rung ]proof, not potential

You finish with a git repo you own from the first commit, and a system that runs. We never ask anyone to trust our grade.

[ pin 04 · the practice ]hints, never answers

The hint ladder is written by a person, one rung per ask, with no answer key.

[ your path is open ]

Build something that actually runs before you decide anything.

See the paths →

This page is about the world, not a promise about your career. What SourceBoot promises is the competence: systems you built, that run.