Every student has a real starting point. Most classrooms never find it. That's what we build at Chaos Theory: learning programmes for schools, colleges and educators, including a year-long AI subject for schools. I write here about AI in classrooms and building in India.
@JeremyErard This is the part the job numbers miss. Entry-level work was where people learned judgment cheaply, so if that rung shrinks, colleges and employers have to build that practice on purpose.
@pdf_si The second reason was always the bigger one. A company that stops hiring juniors saves money for a few years and then finds it has no seniors who learned its systems the hard way.
@Dictxtxr Both sides are saving time on the paperwork. The part neither should automate is a student explaining their thinking out loud to someone who is listening.
@uglyrobot Ownership is the right word, but people usually learn it by owning small things first and getting some of them wrong. If entry-level work goes to agents, someone still has to decide where the next owners get their practice.
@cperry248 The line that stands out is that none of the 17 learning roles defines a career path. The people hired to teach everyone else how to work with AI are the ones with the least clarity on where their own job leads.
@PerBylund The A/B test point is the one schools should take seriously: if nearly all online coursework now gets done by AI, the work has to move back into the room where the thinking is visible. That is less a generation problem than an assessment design problem.
Junior work was never only about output. It was where people learned judgment by getting small things wrong.
If AI takes that work, where do the next professionals learn it?
Agree. You see it fast in maths. A student who got the answer from a tool can't tell you where they'll get stuck next time. A good AI tutor asks "what did you try first?" before it says anything else.
@TEXTUP_ Grading the product, not the thinking, is the right way to put it. The harder question is what replaces coursework for the slow skills an exam room cannot test, like research and revision.
@smartinmot2014 Students can tell feedback written for them from feedback produced to fill a box. If AI takes over the tick-box part, the time it frees should go into that conversation, not into more marking.
@JakeWSimons The split that matters is not book versus chatbot, it is whether a child has an adult checking their thinking. An AI tutor with no teacher behind it is cheaper, not better, and that is the part worth arguing about.
@connectajitcpr Competing globally in deep tech is mostly a patience problem. Indian startups are rewarded for fast revenue, and deep tech needs years of building before the first sale, so the talent is here but the timelines rarely are.
@danpdc Going from 1000 lines to 80 is a great exercise because students see the cost of noise for themselves. Using a coding agent and knowing what it is actually reading are two different skills, and most curricula teach neither yet.
@Dipanshu_AI Point 5 is the one schools should start with. The same tool that sharpens a student who checks its answers makes a student who copies them weaker, so questioning AI output has to be taught early, not left to chance.
@Ideas4India Economic pressure, paperwork and missing information are quieter barriers than a missing school building, which is why they rarely show up in enrolment totals. Field accounts like this show where the system actually loses the child.
@ahamam101 And who notices that the AI was wrong in the first place. That judgment is the part of teaching that gets more valuable as AI gets better, not less.
@arnaudmercier The real test of Study Mode is whether it is allowed to say no. A tutor that hands over the answer the second time a student pushes is still a lookup tool, just a politer one.
@Saurabh_TyagiX The missing step in that list is building one real thing before college ends. A degree says you sat through the years; one project you can explain says what you can actually do.
@cneuralnetwork Reading code you could have just used is underrated. Most learners stop at the API call, and the ones who open the file and trace one forward pass are the ones who can debug it later.