Browse Comments — Clean (de-noised)

Those who kept preaching about an "AI bubble" should be ashamed. In doing so, they risked misleading people, students, and future professionals who were making important decisions and planning for a world increasingly shaped by AI. Looking back, it's frustrating. It makes you wish you could go back in time and punch the sh*t out of their mouths.

For entry level positions AI isxa big threat because their tasks are typically the ones you use AI for when you're already an expert or a manager. But how to become an expert if you don't start learning the job at an entry level after graduation... ?

When I was a kid after getting my masters in Engineering, I had to write about 200 applications for a job. About 150 to get a required internship. We had typewriters back than with no printers. It was a big problem even more so for foreigners. In our current day & age you would expect their progressive professors to be smart enough to guide them in the right direct. But even without that there is so much information available & far more open opportunities that they just need to search & plan better. They could also go to a foreign country to gain experience provided they can get out of their lazy comfort zone & learn a foreign language.

Gerald Piletta That’s the real challenge. AI is compressing the traditional apprenticeship model where juniors learned through repetitive tasks. But I think the new path to expertise will come from building faster, experimenting more, and working alongside AI instead of without it. The graduates who use AI to accelerate learning, not replace thinking, will progress much faster than previous generations.

Feel terrible for all these young people who have worked hard to get their degrees and in certain countries borrowed money to do so only to learn the reward (a job providing a living wage) is no longer in sight. I can appreciate it when they say they have been misled.

A really important perspective on how AI is changing the value of work rather than simply replacing it. The people who will stand out are likely the ones who learn how to combine technical skills, adaptability, creativity, and domain expertise instead of relying only on traditional credentials. The point about building publicly and showing real-world problem solving is especially relevant in today’s market.

Alvin Foo bingo. Accerlate learning.

This is explored in my new book on Artificial Intelligence - AIlienMinds summary Optimists foretell a golden age of Al-managed abundance. Doomers cry: vast cyber-minds will crush old style humanity! ... or make us irrelevant. Meanwhile, geniuses fostering the artificial intelligence boom clutch clichés rooted in our dismal past... or else in cheap sci-fi. Is there still time for perspective? - on 4 billion years of evolution? - or 60 centuries of feudal stagnation? - or how we handled prior tech revolutions? - or mistakes that keep getting repeated... - or ways this time may be different? From Al-driven unemployment to deceitful images, to hallucinating LLMs and tools for tyrants... to potential wondrous gifts by machines of loving grace... come evade the standard ruts.

Some needed context on both sides of the equation. We've recently added four software engineers to the Avnir team.Students/candidates: Two joined us through an internship. You significantly derisk that position for an employer if they can experience your intellectual curiosity, horsepower, learning velocity, and work ethic. Put your ego aside, hustle, learn new skills that Claude Code can't do (yet), and get your foot in the door to work in a fast-paced, high-pressure to produce outcomes (code is not an outcome!) team environment.Employers: I don't know a business that doesn't need fresh thinking. When you invest in the right kind of human talent, they'll amplify your AI investments. Recent grads think very differently from traditional software engineers. Other functions bring their customer- and product-centric knowledge to engineering, all in an effort to thrive amid the evolution toward AI-first thinking.

Torbjörn Maaherra thoughts on this one. Not sure I entirely agree

No worries, bruh. You’re on TV, you got your moment of fame, and you’re surrounded by people who just talk. So welcome to the club of talk doers. Well, they have "jobs", so you need to figure out (social engineer) how to get one of those * jobs and enjoy the sweet, good life blah blahism of fluffism.

Build your own, we are only 5 years out from all these companies restructuring and everyone will be entry level, because the knowledge that those seniors hold on to will be fed into a SOP wiki for the juniors to query. Why pay 120k when you can pay 50k and augment?

All these smart people can be trained on AI tools within a week. I am not sure why companies are not giving a chance to early career professionals. They are smart they can figure it out, only reason they have not been able to go all in would be cost to start using models for even a single problem. There are some free options which people should try to get familiarity.

The companies who fail to train home grown entry level employees will meet their end when the talent pool dries up.

Joey 🇵🇬 Two things can be true at the same time. There is a genuine bubble but that does not mean the impact will not be felt in the job market

Companies mentioned in connection with reduced, limited, or reassessed AI spending in 2025–2026: 1. Uber: reportedly reviewed AI spending after using up its annual AI budget much faster than expected in 2026. 2. Microsoft: limited or scaled back access to some internal AI tools as token and usage costs rose. 3. Amazon: tightened controls around AI usage and token consumption, and signaled that AI should not be used for its own sake. 4. Meta: was mentioned among companies paying closer attention to AI-related spending and internal usage. 5. Salesforce: was also cited among companies moving toward tighter controls or rationing of AI usage due to rising costs. 6. Klarna: partially reversed its aggressive AI-driven customer support strategy and brought more human workers back. The issue was mainly service quality, not cost alone. 7. Duolingo: softened its strict “AI-first” position after public criticism. This was more of a strategic adjustment than a direct budget cut. Reuters reported, citing Gartner, that more than 40% of agentic AI projects may be cancelled by the end of 2027. The trend was already visible in 2025–2026, with rising costs, unclear business value, and immature technology among the main reasons.

Evgen Mirzenko, that's true. But, can we expect this from a 22 year old person, who just graduated from university or college? This sounds more of skills that you learn when you get older.

Max Cherhyshov, Indeed, agenetic AI systems are voracious consumers of tokens.

150 applications without response, is normal for many jobs, with or without AI. Graduates with experience may expect 100+ applications before they land the right one. What more the fresh graduates. So if you ask me, it is not entirely about AI. More about persistence and grit rhat is lacking.

A real problem indeed! Friends of mine in software development who have lost their jobs are leveraging InsiderChimp to get an early warning of the companies considering posting a position (but have not) where they have an insider connection who can get them early access to the final decision makers. I built InsiderChimp to find myself a job using intent data. It worked and I got a full time offer. Intent data tells you when a company is searching for a skill or a contractor or an employee before posting a position It gives you an edge that is desperately needed in this market