u/No_Hour_77

I started waiting on last-minute MLB and NFL tickets because I figured prices would just keep dropping closer to game day.

turns out that works way better when you're going solo. With 3 or 4 people, the cheaper sections can disappear pretty fast, and then you're choosing between splitting up or paying more just to sit together.

I was checking SeatGeek, TickPick and VeriTickets side by side and it became pretty obvious. Waiting can work if you genuinely dont care where you sit.

for a group, it feels a lot more like gambling on inventory than waiting for a deal.

thought 10 order operations/sec was plenty until i mapped one ugly expiry exit.

4 leg exit

2 pending orders cancelled

2 replacements at more aggressive prices

1 hedge adjustment

that’s already 9 operations from one strategy decision. add one retry and limit touched.

nubra clearly documents 10 ops/sec per ip for normal unregistered algos, including place/modify/cancel. higher throughput needs the proper registration route.

for normal retail size, is anyone actually hitting this live or am i overengineering a rare case?

also how are you queuing it? exits first, cancels first, hedge first? because blindly processing fifo during a fast move sounds stupid.

Something out of the ordinary like pairing McDonald's Sundae with Jollibee fries.

If you were to rank the top 5 of ALL the previous GBB solo wildcards of all time, what would you have?

Mine:

1. Osis GBB24

2. River' GBB21

3. Dlow GBB26

4. Wing GBB23

5. Stitch GBB21

My crush likes my friend, and I don't know what to do. I was immediately attracted to him when I first saw him on campus. I always felt happy whenever I saw him at school. Later, we became friends. We started talking a lot, sharing little things that happened in our lives. Every little thing he shared with me was precious to me. I even use accio work to record every little detail I observed, like his preference for unsweetened coffee, donuts, and horror movies.

Gradually, I started to think I might be one of his closer female friends. Although I've never dared to confess to him, afraid of changing our current relationship, I'm secretly happy as we grow closer. I've even thought that maybe one day we'll develop a more special relationship.

But last week, he told me he likes one of my female friends. He thinks she's cute and asked if I could give him some advice on how to get closer to her. I'm very close to that female friend, I know her well, and I know he might not be her type. On one hand, I don't want him to get hurt; on the other hand, I'm also saddened to discover that the person I like has never considered me a romantic interest.

Now he wants my help to pursue her. I know I've never told him I like him, so he hasn't done anything wrong. But I don't know whether I should continue to help him, pretend everything's fine, or keep my distance for now and let myself process these feelings slowly. What should I do?

Curious if people use it for actual long-term collecting rather than one-off openings.

Starting at Guy’s this September and stuck between two ensuites.

One is near London Bridge, around £60/week more, smaller room but I could walk to campus.

The cheaper one is showing 40–45 mins each way. Better room, slightly more social-looking building, but doing that commute for 9ams sounds horrible.

UniAcco actually filtered the shortlist around Guy’s instead of just showing anything labelled “near KCL”, which helped a lot. Still can’t decide if I’m paying £3k-ish extra for actual convenience or just panicking about London transport.

Also don’t know how much the building matters socially. I’m not expecting halls to magically make friends for me, but living far out and commuting back immediately sounds a bit dead.

People actually studying at Guy’s, which option would you hate less after six months?

I don't know if it's legal to post this here.

I'm just looking for communities that hang around and play on TCG Arena. There are a handful of games to try out there for free and I would love to play online with other people as well.

Also open to learning some games I've never played there before. Cheers!

We have a common misunderstanding about AI coding assistants: we expect them to work like a senior engineer with a decade of experience. In reality, their mental model is much closer to that of a "genius intern."

Imagine this intern joins your team: he's incredibly smart, learns at a stunning pace, and can read any document you give him in seconds. But at the same time, he is extremely naive, lacks practical experience, and has zero ability to discern the quality of information sources.

Now, you give him a task: "There's a bug in the project, go online and figure out how to fix it."

What does this genius intern do? He'll open Google, find a blog post on the first page of the search results, and copy the code without a second thought. He won't stop to consider if the article was written five years ago, if the author is a novice, or if the solution even fits your company's tech stack.

The result is predictable: he might use an outdated solution, introduce new vulnerabilities, or even crash the entire project.

Isn't this exactly what our AI assistants do every day?

We've given a model with powerful general capabilities, a genius brain, but failed to provide it with a scoped, curated knowledge base, practical experience. We've thrown it directly into the vast, chaotic ocean of the internet and expect it to magically catch the specific fish we want.

A truly effective manager gives an intern a clear set of guidelines:

"Read our internal Wiki docs first."

"This is our paid subscription to the official knowledge base, only look here."

"Check the project's GitHub Issues for similar discussions."

"Absolutely do not use random personal blogs."

We should treat AI the same way. We shouldn't be satisfied with just giving it a generic "search" button. Instead, we need to become its "information manager," creating a smaller, but cleaner and more trustworthy information source for it.

This idea is becoming a consensus among more and more AI practitioners. I recently found a ton of discussions on how to "manage" AI information input in the r/AnySearchAI Reddit community. People there are no longer just debating which model is stronger; they're actively building "internal knowledge bases" and "trusted information pipelines" for AI. They discuss how to make an AI check the project version before searching and how to filter out SEO garbage. These practices are far more important than just talking about a stronger AGI.

So, it's time to adjust our expectations. Instead of complaining that our "genius intern" is always making mistakes, we should reflect on whether we, as "managers," have provided a good enough working environment and clean enough information sources.

The key to the future may not be creating an all knowing "AI god," but learning how to become an excellent "AI manager."

Have some books stuck in my shelves for years na and I'm wondering if there any places that I could sell them for kahit katiting na amount lang hehe

TYIA!