When we played Arcs, we found it was much more about making short term tactical decisions, and there wasn’t as much room for that kind of deep long term planning, so the experience felt less competitive and less tense for us.

So we are looking for something that gives a similar player experience of constantly balancing short and long term strategy like that, but without going all the way to something with very very complex rules like Twilight Imperium.

Does that make sense?

Dune was basically the opposite you have an element of RNG from deckbuilding, you have multi-step planning and if someone else takes your move you have to recalibrate your plan, you can pull off crazy combos and hidden plans with intrigues.

I highly recommend Dune Imperium Uprising for engineers.

Would love if anyone can recommend any game of similar depth. We tried Arcs, root, and some others but couldn’t find anything similarly competitive and deep while not being one of those way too complicated games like twilight imperium or something.

And ON CONFLICT which can help dedupe among other things in a simple and performant way.

There’s definitely a market for good looking UI that actually works and stands out from the vibe coded junk. Artisanal corn fed UI I guess.

Anyone know if that’s true? I only heard it second hand.

So instead of interactively making one agent do a large task you make small agents do the coding while you focus on the design.

I already use this workflow myself, just multiple terminals with Claude on different directories. There’s like 100 of these “Claude with worktrees in parallel” UIs now, would have expected some of the common jetbrains value adds like some deep debugger integration or some fancy test runner view etc. The only one I see called out is Local History and I don’t see any fancy diff or find in files deep integration to diff or search between the agent work trees and I don’t see the jetbrains commit, shelf, etc. git integration that we like.

I do like the cursor-like highlight and add to context thing and the kanban board sort of view of the agent statuses, but this is nothing new. I would have expected at the least that jetbrains would provide some fancier UI that lets you select which directories or scopes should be auto approved for edit or other fancy fine grained auto-approve permissions for the agent.

In summary it looks like just another parallel Claude UI rather than a Jetbrains take on it. It also seems like it’s a separate IDE rather than built on the IntelliJ platform so they probably won’t turn it into a plugin in the future either.

Thought it might be interesting to hear what changed.

Comments URL: https://news.ycombinator.com/item?id=46130404

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So I’m still sticking with Route53 cause it’s the least annoying registrar and DNS api, for CDN I’m going with bunny and for dirt cheap object storage I’m going with b2.

Then the fun part is the actual self hosting: I’m going with Garage for my normal self hosted S3 api (b2 is for backups etc.), Scylla for DDB, Spin for super fast Wasm FaaS…

Then this weekend I got deep into trying to build my cloudwatch alternative I think I’m going with dumping logs with vector into b2 and then using quickwit for searching the logs.

Just a fun homelab challenge really.

I haven’t yet worked out the best cheap VPS/dedicated provider though, project for next weekend.

Go try doing an aggregation of 650gb of json data using normal CLI tools vs duckdb or clickhouse. These tools are pipelining and parallelizing in a way that isn’t easy to do with just GNU Parallel (trust me, I’ve tried).

I found that clickhouse was the fastest, but duckdb was the simplest to work with it usually just works. DuckDB was close enough to the max performance from clickhouse.

I tried flink & pyspark but they were way slower (like 3-5x) than clickhouse and the code was kind of annoying. Dask and Ray were also way too slow, but dask’s parallelism was easy to code but it was just too slow. I also tried Datafusion and polars but clickhouse ended up being faster.

These days I would recommend starting with DuckDB or Clickhouse for most workloads just cause it’s the easiest to work with AND has good performance. Personally I switched to using DuckDB instead of polars for most things where pandas is too slow.

Was trying to find a good one for 30B quants but there’s so many now and the pricing is all over the place.

I hope they implemented this in some smarter way than just a system prompt.

Yes! This exactly, with o3 you could ask your question imprecisely or word it badly/ambiguously and it would figure out what you meant, with GPT5 I have had several cases just in the last few hours where it misunderstands the question and requires refinement.

> It was related to software architecture, so supposedly something it should be good at. But for some reason it interpreted me as asking from an end-user perspective instead of a developer of the service, even though it was plenty clear to any human - and other models - that I meant the latter.

For me I was using o3 in daily life like yesterday we were playing a board game so I wanted to ask GPT5 Thinking to clarify a rule, I used the ambiguous prompt with a picture of a card’s draw 1 card power and asked “Is this from the deck or both?” (From the deck or from the board). It responded by saying the card I took a picture of was from the game wingspan’s deck instead of clarifying the actual power on the card (o3 would never).

I’m not looking forward to how much time this will waste on my weekend coding projects this weekend.

So far I haven’t been impressed with GPT5 thinking but I can’t concretely say why yet. I am thinking of comparing the same prompt side by side between o3 and GPT5 thinking.

Also just from my first few hours with GPT5 Thinking I feel that it’s not as good at short prompts as o3 e.g instead of using a big xml or json prompt I would just type the shortest possible phrase for the task e.g “best gpu for home LLM inference vs cloud api.”