Very hit or miss.

Stack: go, python Team size: 8 Experience, mixed.

I'm using a code review agent which sometimes catches a critical big humans miss, so that is very useful.

Using it to get to know a code base is also very useful. A question like 'which functions touch this table' or 'describe the flow of this API endpoint' are usually answered correctly. This is a huge time saver when I need to work on a code base i'm less familiar with.

For coding, agents are fine for simple straightforward tasks, but I find the tools are very myopic: they prefer very local changes (adding new helper functions all over the place, even when such helpers already exist)

For harder problems I find agents get stuck in loops, and coming up with the right prompts and guardrails can be slower than just writing the code.

I also hates how slow and unpredictable the agents can be. At times it feels like gambling. Will the agents actually fix my tests, or fuck up the code base? Who knows, let's check in 5 minutes.

IMO the worst thing is that juniors can now come up with large change sets, that seem good at a glance but then turn out to be fundamentally flawed, and it takes tons of time to review

They made their home a concentration camp, no need for railroad cars this time...

I'm thinking of using it to replace an analytics pipeline at my job, which now uses expensive batch jobs. If the tech is solid, we would have instant and incremental updates, instead of recomputing everything every X hours. This would simplify things a lot.

I think Materialize offers a similar product, but last I checked it was only available as a SaaS solution.

I hope to do a proof of concept soon, to compare both solutions

materialize now offers a self managed version of the product https://materialize.com/docs/self-managed/v25.1/

Does anyone have experience with RisingWave in production? It seems like an interesting product but I can't find any experience reports.

I've been running this in prod self hosted for around 6 months (podman with docker compose, minio for s3, streaming with pulsar). We have built position calculations for risk monitoring and booking enrichment pipelines. Risingwave is a much better alternative to Kafka Streams: primarily around consistency, sql first, easy state query and deployment.

The RisingWave team are pretty responsive on slack and the ask ai feature also helps to solve questions. They have coverage from Singapore, China and California.

Issues we have seen have mostly been related to reliability of our on prem Minio cluster which is used to store the data. Other bugs do appear from release to release but once raised get attention quickly.

I was going to go with Redpanda+Flink, would you suggest otherwise? (and why)

Looking at the contributor list, I doubt they speak English or frequent HN so you’ll only get the engineers’ perspective. Looks new and the cloud offering a way to sell it.

A. Some of the team members are in the bay area including the founder who writes well. B. Used it for streaming sql on citus cluster and planning to use it more.

A) I assumed the team members were English speaking and are amazing at what they do (look at it!), more that they might have more customers on the eastern side of the world and that’s totally my bias from past B) but glad to see I’m wrong and that there’s people using it for things. It looks awesome.

Alex Chi was in the project. He is now writing TinyLLM.

Oh I wasn’t talking about the engineers behind the project, they’re good. More if there were companies using this already…

Don’t take it the wrong way, just that the east and west tend to only share things when it’s profound - like deepseek.

But I could be wrong, sometimes things go under the radar until it’s ready.

User name almost checks out

Classic Dutch: “We need this talent… but financially, it is impossible to support them,”

you get runtime errors with a long JVM stacktrace

If the core team had ever addressed the decade of surveys showing that error messages/stacktraces were people's top complaints, you wouldn't need Claude.

Immutability removes so much accidental complexity, it makes whole classes of mistakes dissapear. I'd also take immutability over types.

Clojure sort of guides you to simplicity, building everything out of functions and simple datastructures has big advantages when testing and reasoning about code.

I do find that in larger code bases, Clojure lack of types causes friction (spec is just a bandaid, not a fix).

There are languages with immutability and types (like Haskell), but these don't have the get-shit-done factor I seek.

Seems like a bunch of go programmers really wanted to use go, no matter how impractical.

Interesting! I did an internship where I tried to use transducers for fast information extraction. In theory, you can use FST's for fast approximate parsing. I didn't really work out, but I had lots of fun implementing a libary to compose FST's and explore cool algorithms to compose them. Not much business value was delivered, but I learned a lot.