u/waitingforathena

Hi I am a 23 yo backend-focused SWE with inconsistent employment history with almost 6 months of fulltime experience since grad.

I am currently looking for a new job (resigned as backend eng from the current org 15 days ago).

I know microservices, queues, cache, websockets, go, javascript. I wanna learn applied AI eng asap as it has many roles in market.

I have three questions to the junior level devs as well as senior devs out there.

1. How should I prep for interviews (I suck at interviews)?

I have never done DSA rigorously (would most probably fail one). Should I hand code projects or should I use CC/agents and work more towards agentic dev plus verification skills? Should I remember the syntax to write in interviews. I mean what exactly to focus on? Will they ask me the workflow of my agentic dev or how I orchestrate agents?

2. How do I benchmark models, different models to understand when to use what models?

I use Sonnet medium or high and I don't know how to really benchmark for my own use case.

3. I want to buy a sub should I go for Claude / codex / cursor / Devin.

I have gemini pro due to an offer and the antigravity is the worst harness mankind ever created.

My use cases are :

1. I create courses with different md files to learn something and I let my agents to teach me like a youtuber / teacher / senior dev.
2. I wanna learn system designs in the same way like above and want to improve at agentic coding workflows + code verification and also wanna learn applied AI engineering and inference engineering.
3. I also want to create some videos for my family business.

Also, if there is any suggestion regarding discounts on Claude code and tips on how to find entry level jobs or how to get a job as a junior dev, it would be helpful (I cant find lot of entry level jobs on career portals).

I am a SWE with 5 YOE and I am mentoring a masters grad, 2025 passout with only internship experience.

He is very interested in system design and understanding internals but struggles with actually writing code. He is also weak at LeetCode and says he often knows the solution in his head but cant translate it into working code.

He recently joined a startup with no senior engineers and the CEO/CTO are pushing the team to ship the product quickly, so he is spinning up agents and using Claude heavily to build things faster.

I have been telling him to read more code, not blindly trust AI, and actually implement things himself. I've also suggested implementing DDIA concepts like LSM trees, SSTables, vector DBs etc instead of only reading about them.

The thing I am confused about is how he should balance actually being good at engineering vs becoming good at AI-assisted engineering.

He is interested in becoming an Applied AI engineer with strong backend/infra knowledge, mainly building agents, RAG, tool calling, evals etc. He keeps seeing this discussed on Twitter/X as a growing role, but I am not sure how much of it is real demand vs Twitter hype.

With AI coding becoming better, I dont want him to spend all his time manually writing code and fall behind on learning how to actually use and orchestrate agents. But at the same time, I dont want him to become someone who can generate 10k lines with Claude but cant debug 50 lines without it.

Basically, he needs to stay sharp at coding, debugging and fundamentals while also learning how to effectively orchestrate and manage AI agents.

So for people actually working in the industry:

1. How should he balance coding without AI vs AI-assisted coding? Should he deliberately code without AI to keep his fundamentals sharp, or should he mostly use AI and focus on understanding, reviewing and debugging what it produces?
2. What should he prioritize for the next 3-5 months? DSA/LeetCode, coding fundamentals, DDIA/system design, backend projects, distributed systems or Applied AI/agents? He may need to switch jobs soon, so he needs to become employable quickly.
3. For senior engineers/managers who hire juniors, what technical bar would you expect from someone with only internship experience? What would make you comfortable putting that person on your team?

If you had a junior who wanted to become an Applied AI engineer with strong backend/infra skills, while still being genuinely good at coding and engineering, what would you tell them to learn first?

TL;DR: His startup is pushing him to use AI agents to ship the product quickly. How should a junior balance staying genuinely good at coding/engineering while also becoming good at AI-assisted development and orchestrating agents? What would you prioritize over the next 3-5 months for someone targeting backend SWE or Applied AI roles?

PS: not a native English speaker. I took help of AI to produce final version of my thoughts