u/IDontKnowAGoodUsrNam

So I wanted to get a 22lr MP5 and one of my local FFL(actually all of the FFLs I had relation with) had one in store and willing to transfer one to me.. And all FFL told me as long as it is 30 inches more in length, they should be fine..

On the AWB.... mp5 is banned explicitly by name but "technically", the 22lr version is not the same gun as the mp5 - different action type. And since it is 22lr and more than 30inches, it's not considered as an assault weapon thus the "distribution, transfer, import" is not banned?

And for me as a buyer, as long as the FFL is willing to transfer it, I'm not fall under any legal obligations that could violate the AWB since it only bans manufacturing/import/distribution/transfer?

Another thing that confuses me is on the transfer paperwork for the background.. It says Semiautomatic "ASSAULT" Rifle... Which I'd assume it's just a classification...

What do people think... How TF do I even interpret the stupid law..

I've been seeing a lot of doom-posting here lately. "Hiring is frozen." "Senior roles are impossible." "It's all nepotism and referrals now."

I just finished a search that started in January and ended with a senior offer at Microsoft — AI Security focused, market TC. And my honest read: the market is fine. But if your prep looks the same as it did two years ago, you're going to feel like the market is broken.

Here's what actually changed.

I figured I'd refresh LeetCode first, run through some duistributed systems, polish my STAR stories, and be good to go in 6–8 weeks.

I was caught off guard almost immediately.

Within the first few screens, I was getting questions I genuinely hadn't prepped for:

"Tell me about a time you had to evaluate tradeoffs in an AI-powered system. Or how would you approach it"

These weren't ML engineer roles. These were general senior SWE positions — backend, platform, one was even infra-adjacent. The behavioral layer has quietly gone AI-aware and nobody really talks about it.

I kept the LeetCode cadence going — you still need it, full stop — but I had to add a whole new layer:

System design with AI components: RAG pipelines, evaluation loops, model serving tradeoffs
AI security concepts: prompt injection, data leakage, model abuse vectors
And critically: behavioral stories that speak to AI judgment, not just engineering execution

That last one tripped me up the most. I had plenty of strong STAR stories about scaling systems, handling incidents, cross-team influence. But "tell me about a time you made a tradeoff in an AI system" — I didn't have a clean answer ready. Most people don't, unless they've specifically worked on AI projects and thought about how to frame them.

The mental reframe that helped: AI questions at the senior level are really leadership and judgment questions in disguise. They want to know how you think about risk, uncertainty, and tradeoffs — just in a new domain.

What the interviews actually looked like

Three things stood out compared to previous cycles:

Behavioral rounds are now AI-aware. At least half my behavioral loops included one question that touched on AI — how you've worked with it, how you've thought about its risks, how you'd advise a team using it. This wasn't every company, but it was most of them.
System design expects AI fluency. Not deep ML knowledge — but you need to be able to reason about where AI fits, what breaks, and what the cost/risk profile looks like. "That's more of an ML team concern" is not a good answer anymore.
They're evaluating judgment, not credentials. The best interviewers weren't checking if you'd shipped a model. They were checking if you could reason about AI the same way you reason about databases or message queues — as a tool with tradeoffs.

Honest takeaway for anyone prepping now

The bar shifted more than it went up. That's actually an opportunity — most candidates are still grinding pure LeetCode and memorizing system design templates. If you layer in AI fluency, especially on the behavioral side, you stand out.

You don't need to become an ML engineer. You need to:

Have real stories (or well-reasoned hypothetical takes) about AI tradeoffs and judgment calls - Honestly man.. just prepare a few stories with enough detail. You want to send them the signal that you are in the game.
Be able to design systems with AI components without freezing up
Think out loud about risk, failure modes, and when not to use AI

Resources that actually helped

A few things worth sharing for anyone in active prep:

LeetCode — still non-negotiable for coding rounds, nothing has replaced it
Neetcode.io — better structured than raw LeetCode grinding, the roadmap is genuinely useful if you don't know where to start
System Design Primer (GitHub) — free, comprehensive, good foundation; just mentally add an AI layer to every design you practice
River Rock Prep — newer platform, still early, but I'd specifically call this out for AI behavioral questions. They have a solid question bank mapped to actual company values with an LLM-based mock interview format. A few of the questions I practiced on there came up almost verbatim in my loops. It's cheap around 15$ and I felt worth it for that specific gap. Not for everyone, but if the AI behavioral side is where you're weak, it fills a real hole.

I hope this helps and keep grinding! And I hope y'all get a job in 2026.

Want to get a mk23..