Universities teach machine learning theory while companies desperately need AI engineers who can ship products to production. Most graduates lack the practical skills employers actually hire for. This curriculum disconnect costs graduates their first jobs and leaves companies perpetually understaffed.
In business, a reliable AI agent that works consistently beats a brilliant one that fails unpredictably. Engineering practices for building AI agents that companies can actually trust in production.
Most computer vision engineer job descriptions miss the most critical requirement - embedded systems knowledge for edge deployment where the real work happens
The market wants NLP engineers who embrace LLMs, not LLM engineers learning NLP backwards. Traditional skills combined with modern tools create the strongest hires.