VenkataSakethDakuri

AI Agent evaluation - Galileo
AI technical cofounder - Woz (YC W25)
LLM model and LLM system evaluation - Arize AI
Statefull AI Agents - Letta
LLM Fine tuning - unsloth  https://unsloth.ai/blog/r1-reasoning
Prompt Engineering : https://www.kaggle.com/whitepaper-prompt-engineering?utm_source=alphasignal
Firebase Studio, a web-based IDE to build and deploy full-stack AI applications
AI Agents Unleashed , playbook for ai agents in production

NVIDIA provides a cutting-edge, modular workflow for synthetic data generation (SDG), leveraging platforms and models like Omniverse Replicator, Isaac Sim, NeMo, and advanced LLMs (such as Nemotron-4 and Llama 3.1).

VenkataSakethDakuri

Main Components of LLM training:
architecture, training algo/loss, data, evaluation, systems



AI systems:
Majority completion strategy: for doing a hard reasoning task, the model can go in diff reasoning paths and final answer can be the majority output from these paths.
dspy is a declarative programming library designed for building and optimizing AI-powered applications, especially those leveraging large language models (LLMs). It provides a structured and modular approach to defining tasks, training models, and integrating AI capabilities.

VenkataSakethDakuri

Lovable:
Encourage External Tool Usage

Nudge GPT to use external tools for specific tasks.
Particularly useful for frontend tasks (e.g., progress bars, UI components).
Explicitly Include "Connect to Database"

Mention "Connect to database" in either the user prompt or system message to ensure proper handling of database-related tasks.
Fix Row-Level Security (RLS) Issues