GitHub repo: https://t.co/wObdNY4VUQ(don't forget to star it ⭐ ) ...

I just built my own multi-agent deep researcher!It uses a 100% local LLM and MCP.Here's an overview of how it works:- User submits a query- Web agent searches with Bright Data MCP tool- Research agents generate insights using platform-specific tools- Response agent crafts a coherent answer with citationsTech stack:- Bright Data MCP for real-time web access- CrewAI for multi-agent orchestration- Ollama to locally serve GPT-OSSWhy Bright Data MCP?To build this workflow, we needed to gather information from se ...

RT Avi Chawla (@_avichawla)4 strategies LLMs use to generate text: https://t.co/ouSe6oC3LT ...

4 strategies LLMs use to generate text: https://t.co/ouSe6oC3LT ...

RT Avi Chawla (@_avichawla)- Replit's Agent wiped out a production DB- Zillow lost $304M due to its home-buying AI- iTutor paid $365k when AI rejected old applicantsAI disasters like these can literally make you lose your job!Let's learn how to build Agents that don't fail in production (with code): https://t.co/MQZVsk1EPF ...

That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. ...

Building Agents is about engineering “behavior” at scale. So you cannot vibe-prompt an Agent and expect it to work.Parlant gives the structure to build Agents that behave exactly as instructed.GitHub repo: https://t.co/kjVj5Rp7Xm(don't forget to star it ⭐) ...

AI Risk & Failure - AI failures can lead to job loss [1] - Building robust Agents is crucial to avoid production failures [1] Financial Losses due to AI - Zillow experienced a $304 million loss due to its home-buying AI [1] - iTutor paid $365 thousand when AI rejected older applicants [1] Examples of AI Failures - Replit's Agent wiped out a production database [1]

RT Avi Chawla (@_avichawla)Pytest for LLM Apps is finally here!DeepEval turns LLM evals into a two-line test suite to help you identify the best models, prompts, and architecture for AI workflows (including MCPs).Works with all frameworks like LlamaIndex, CrewAI, etc.100% open-source with 11k stars! https://t.co/Xayu1aFGFV ...

LLM Evaluation Tools - DeepEval transforms LLM evaluations into a two-line test suite [1] - DeepEval helps identify the best models, prompts, and architecture for AI workflows, including MCPs (Multi-Choice Preference) [1] - DeepEval is 100% open-source with 11 thousand stars [1] Framework Compatibility - DeepEval works with all frameworks like LlamaIndex, CrewAI, etc [1] Community Engagement - The author encourages readers to reshare the information [1] - The author shares tutorials and insights on DS (Data Science), ML (Machine Learning), LLMs (Large Language Models), and RAGs (Retrieval-Augmented Generation) daily [1]