yubozhao's comments

Yeah. Exploratory work are much less rigid and they are more throw away. Don’t need to have spec.

Turn that exploratory work to product would be the challenges. It is hard to balance the two

Yeah, we use mixture of agents to get you the best results

Creator here. Happy to answer any questions

Background:

We been helping mid-market companies for the past 1.5 years and finally ready to share the internal platform publicly. Yansu (严肃) is a AI coding platform that use spec + TDD to build complex software projects. It is more like a SOP than coding agent. We focus on understanding requirements and checking outcomes against those requirements while iterating the code based on the tests.

Yansu tries to learn as much tribal knowledge as possible. These are things you don’t write down in google doc or Notion. Yansu absorbs these knowledge by continuously talking to users and distilling learning from them.

It's as if a spec + TDD platform had a baby with character.ai.

Why care about requirements? B/c 80% of any software development is understanding requirements and what exactly we want to build. We also focus on outcomes, the only thing that matters. We deliver satisfying outcomes by simulating scenarios and generating tests based on those scenarios. Our agents take that tedious testing part of the code away from others.

We prioritize accuracy over latency/cost, using a mixture of agents (not limited to CC, codex, and etc) to get the job done. We then run through continuous-testing-generating pipelines until all things pass.

What does Yansu mean? “Serious” in Chinese. Just like my favorite artist, Rene Magritte, painting in his kitchen in a suit. I want to give my coding respect and care.

Our goal is to level people up from IC to tech leads, to work on the high leverage work of planning, validating, and educating.

We made a launch video to celebrate human work that builds on all of the creative minds before us. Shoutout to CinemaSings for making this happen.

Enjoy the video and check us out: https://x.com/isoformai/status/1986101032477434129

thanks! We try to make it no AI involved and build on all of the cool cinemas before us

I am curious about how you think about memory.

Yep. I agree. And that's what I am trying to tell folks. Focus on higher value work.

You have a wrong assumption of what context and teaching means with twiddling with prompts.

The job of human is providing teaching via feedback. Your manager does the same thing to you too. And you can distill those feedback into learnable experience for your llm to be better next time.

We always want to go higher leverage/value tasks. This time is teaching others, not just writing code.

We are not automating ourselves out of the job, we are changing the nature of the job. From writing to teaching.

As we are building a collaboration platform between you and your AI coworkers. We wrote down our experience on this new relationship, and how it reflect in our product, where are the relationship now and how they are evolving over time.

Happy to hear your thoughts

I think the target personas is different. While they might have the same capabilities, but the job-to-be-done is different.

openllmetry is focus on engineers, who wants to use this as more of a piping solution and it sits on top of opentelemtry. While opentelemetry is a popular solution. It is just applying a solution to a new problem.

OpenLayers to me is thinking from the ML/AI problems from ground up and while serving the data scientists and probably prompt engineers.

The tea from a region in Fujian has a great flavor that is referred to as "duck-feces fragrance". When people ask about the soil, the farmers say they use duck feces to deter others from stealing their soil.

Any real world examples? How does it work out for them?

How does Openlayer handle the privacy and security of the data that's uploaded to the platform, especially considering the sensitive nature of some ML datasets?

SD is great now to be "creative". It would be 1000% more useful if we can give it a few constraints and still be "creative".

With stable diffusion out and making it trivial to generate fake images, Blockchain and NFT are going to be more indispensable in proving authenticity

Curious about your reason behind being less of a fan of the SSPL license. Can you elaborate more?

disclosure: I have a repo using the SSPL license

I have polio from the vaccination (mid 80s in China). Shitty vaccine then.

The long term affect is not fun. And not to mention post polio syndrome.

Hey Komatsu, thanks for supporting!

haha, I wish we created spam accounts....Tried to get on the first page by posting to the community slack, but that didn't work :(

hello, maintainer for bentoml here.

Elastic license prevents users to bundle the project as part of their commercial offering. They can use however they want internally.

For BentoML, we will stay with Apache-2, because we see this could be a standard for the industry to use. We are not going to restrict it.

If copilot saves more than 30 mins of your time per month, then it is totally worth it.