anuragvishwa

Hey Guys, could you please help me choose between 2 ideas i am planning to build:

1.Prompt Engineering Evaluations for LLMs through playground .

2. Fine Tuning a foundational model.

Thanks.

These are the features i am working on - 1. Collaborative playground with history 2. Prompt management and deployment controls 3. Backtest changes and confidently update models 4. Capture feedback and run quantitative experiments

Would like your feedback and suggestions

Launching soon, the playground : 1. Collaborative playground with history 2. Prompt management and deployment controls 3. Backtest changes and confidently update models 4. Capture feedback and run quantitative experiments

Feedbacks and comments are most welcome

I am planning to build a startup around some pain points around K8s, it may be related to platform engineering as well. - I tried building Opensource Platform as a service (Visualith) that would help you deploy k8s cluster and application on your AWS account but have 0 takers. I think i am missing the point here. Need some feedback around the pain points so that i could build an actual solution.

I recently launched my open-source product, visualith.com . It is a PAAS for AWS. - It helps you quickly deploy cluster(EKS) and applications using GitOps principle (ArgoCD). - It contains graphana and prometheus pre configured. - It also contains Kubecost preconfigured. I am unable to get a single user to try the product. What am i doing wrong or is the timing wrong. Desperately need some suggestions.