Yatharth Sharma
YatharthS
AI & ML interests
TTS, speech generation, Agents, MCP
Recent Activity
reacted to TravisMuhlestein's post with 🔥 3 days ago
One of the most underrated parts of AI-assisted engineering may have nothing to do with the model.
It's the infrastructure around the engineer.
Shriyash Balshetwar and Shubham Jangle, engineers at GoDaddy, were spending roughly 16 mechanical pull requests per week managing localization branches. None of the work was particularly difficult—it was repetitive, easy to forget, and occasionally capable of blocking releases.
They built a GitHub App to remove the entire workflow.
What I find interesting is what happened underneath the simple idea of "automate the PRs."
The production system needed idempotent webhook handling, installation-scoped authentication, retry logic around GitHub's asynchronous mergeability state, per-repository configuration, and safe pattern matching.
The app itself is under 900 lines of JavaScript.
The interesting lesson is that the hard part of automation isn't always the automation.
It's building the reliability around it.
As AI agents take on more software engineering tasks, I expect this distinction to become even more important. The systems surrounding an agent—events, permissions, state, retries, validation, and feedback—may matter as much as the model making the decision.
🔗 https://www.godaddy.com/resources/news/how-a-github-app-saved-us-hours-of-manual-effort
Curious what other engineering workflows people have found worth automating end-to-end. reacted to theirpost with 🚀 11 days ago
Open sourcing Coala Embeddings! It can compress 20 million documents which can take 80gb ram down to just 1gb RAM.
Why is this important? Embeddings are used everywhere(RAG, semantic search, etc.) by many.
Coala Embeddings massively cheapen cost to host them while being simply and easy to use.
GitHub: https://github.com/ysharma3501/CoalaEmbeddings
Notebook Demo: https://colab.research.google.com/drive/1TXip-vZg72e_2AB185MINufVVav8Oo9T?usp=sharing reacted to theirpost with 🔥 11 days ago
Open sourcing Coala Embeddings! It can compress 20 million documents which can take 80gb ram down to just 1gb RAM.
Why is this important? Embeddings are used everywhere(RAG, semantic search, etc.) by many.
Coala Embeddings massively cheapen cost to host them while being simply and easy to use.
GitHub: https://github.com/ysharma3501/CoalaEmbeddings
Notebook Demo: https://colab.research.google.com/drive/1TXip-vZg72e_2AB185MINufVVav8Oo9T?usp=sharingOrganizations
