Working In AI

A plain-spoken guide to building a career in and around AI: the roles that actually exist and what they look like on an ordinary Tuesday, where a degree matters and where it does not, how to build a portfolio with no job history, what to do when the courses run out and you still freeze at an empty file, how hiring really works in India, Nigeria, Brazil, Europe and the US, what the money looks like in local terms, how freelancing and contracting actually pay, and which parts of this work are most exposed to automation. No hype, no doom, and no pretending that any of it is the same everywhere.

1. 1The jobs, described as they feel on a Tuesday7 minMost AI work is moving messy data and checking outputs, not training models.
2. 2Who actually needs a degree6 minA degree opens doors in some markets; evidence that you can build is what keeps you inside.
3. 3A portfolio when you have never been paid for this7 minA portfolio proves judgement under mess, not that you can finish someone else's tutorial.
4. 4When the courses end and you still freeze7 minYou learn to build by finishing small things alone, not by watching bigger things being finished.
5. 5How people actually get in8 minMost people enter this field sideways, from an adjacent job or through someone who vouches.
6. 6Pay, rates, and who actually decides them8 minPay is set by employer type, country and your alternatives, far more than by your job title.
7. 7Which parts of this work are most exposed7 minWell-specified work with fast verification goes first; being accountable for the answer goes last.