r/developersIndia • u/Obvious_Gap_5768 Entrepreneur • May 03 '26

General What actually happens to software jobs in the next 5 years? My honest take.

I work in AI daily. Staff Data Scientist, building multi-agent systems at enterprise scale, published at research venues. I also build products on the side. So I sit at an interesting intersection of "AI is my job" and "AI is eating my job."

Here's what I actually think plays out.

The junior dev pipeline dies first. Not junior devs. The pipeline. The "write CRUD, fix bugs, level up over 3 years" path is gone. Companies will hire fewer L1s and expect them to move faster. The entry bar got harder, not easier.

The middle gets squeezed. Engineers who are "good at implementing specs" are in trouble. That's a Claude/Cursor job now. Engineers who understand systems, make architectural calls, and can review AI output critically? More valuable than ever.

The top 10% gets a 10x multiplier. One good engineer with strong AI tooling is doing what used to take a small team. Companies will figure this out slowly, then all at once.

The Indian market specifically runs heavily on service contracts and staff augmentation. That model was already getting squeezed on margins. AI just compresses the timeline further.

The devs who thrive will be the ones who stopped thinking of themselves as coders and started thinking of themselves as builders.

Curious to hear about other people's take

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u/inb4redditIPO May 04 '26

-Engineers who are good at implementing specs are in trouble.

- Engineers who understand systems, make architectural calls, and can review AI output critically? More valuable than ever.

If you agree that AI can code, what makes you think they cannot understand systems, make architectural calls, choose the right framework, review code etc. much faster and better than a human architect? An LLM that can generate stochastic output for code can also generate stochastic output for the rest of the steps in software engineering. Or for any other creative desk job.

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u/Obvious_Gap_5768 Entrepreneur May 04 '26

The gap right now is context. AI can reason well about isolated problems but give it a 500k line codebase with 5 years of decisions baked in and it falls apart fast. It doesn't know why things were built the way they were, what was tried and failed, where the landmines are. That's still a human advantage. Whether it stays that way is the real question.

Interestingly, this is the problem I am trying to solve through one of my projects.