Top Tweets for #100daysofAIEngineering
100 DaysOfAIEngineering — Day 07/100
Today built the Autonomous AI Agents using LLM-Based Tool Decision Making
#100daysofcode
#100daysofaiengineering
#aiagents
#agenticai
100 Days of AiEngineering — Day3/100
Today learned about:
Basic to advanced prompt engineering.
#100daysofaiengineering #100daysoflearning
#aiengineering
#promptengineering
🤖 The 3 Don’ts and Do’s of Building AI Applications
#100DaysOfAIEngineering
Not every lesson in AI engineering comes from tutorials. Some hit you after your model breaks, leaks, or gets exploited.
Here are 3 foundational Don’t–Do rules that could save your project:
🧵
🚀Day 52 of #100DaysOfAIEngineering
For the past 21 days, the 100DaysOfAIEngineering challenge has been on an indefinite pause…
But we're back stronger than ever! 💪
Building Efficient Agentic Workflows: No-Code and With Code 🧵🧵
#100daysOfAIEngineering #aiagents #coding
DeMCP is pioneering the future of AI x Web3.
WalletMCP is my small contribution to that vision 😁
Explore, test, and fork WalletMCP👇 https://t.co/5DZDUBZj6e
Let’s build the future together.
#MCP #AI #solana #demcp #aiengineering #100daysOfAIEngineering
🚀 Day 51 of #100DaysOfAIEngineering
Ever heard of the term Mixture of Experts (MoE)?
It’s more than just a buzzword in the artificial intelligence space, it's one of the most widely adopted architectures behind state-of-the-art (SOTA) large language models.
🚀 Day 48 of #100DaysOfAIEngineering
Google just launched a new protocol for agents and for the past 3 days it has been a buzzword in the AI engineering world.
Some are calling it the “MCP killer” but is it?
🚀Day 47 of #100DaysofAIEngineering
On the 46th day of this journey we talked about a popular AI engineering concept known as tool calling.
And today we would be giving an LLM the ability to analyze and test codes using tool calling (we are implementing tools calling 😁)
🚀 Day 43 of #100DaysOfAIEngineering
Today, we’re diving into the core of AI Engineering, where all the real action is happening. One of the hottest topics everyone’s buzzing about since late last year is... AI Agents.
🚀Day 42 of #100daysofAIEngineering
For the past 41 days, we've been laying the groundwork, covering essential machine learning concepts and terminologies. But now, we’re stepping into the real AI engineering, the cutting-edge trends and innovations that define the field today.
🚀 Day 40 of #100DaysOfAIEngineering
For the past few weeks, we’ve been exploring Large Language Models (LLMs) and various augmentation techniques. But today, we’re diving into something different, something even more exciting than LLMs!
🚀 Day 39 of #100DaysofAIEngineering
For the past three days, I’ve been working on the final part of the KBLaM implementation, embedding the knowledge base into the model’s attention layers.
🚀 Day 38 of #100DaysOfAIEngineering
Two days ago, we completed the first part of our PDF KBLaM pipeline, extracting structured knowledge base triples from PDFs using Gemini 2.0 Pro Exp. If you missed it, you can check it out here 👉 (https://t.co/T5togkUpCq).
🚀 Day 36 of #100DaysOfAIEngineering
For the past few days, we've been diving into RAG (Retrieval-Augmented Generation) and its variants, a surefire way to help a Large Language Model (LLM) generalize beyond its training data.
🚀 Day 35 of #100DaysOfAIEngineering
Yesterday, we explored Cache-Augmented Generation (CAG), a blazing-fast alternative to RAG. And as promised, here’s the implementation! (Phew 🤧)
#ai #coding #SoftwareEngineering
🚀 Day 32 of #100DaysOfAIEngineering
Yesterday, we explored the Augmentation component of a RAG system, how it enhances retrieval, refines queries, and improves response accuracy. Today, let’s dive into the Generation component, where the magic of response crafting happens.
🚀 Day 30 of #100DaysOfAIEngineering
Yesterday, we explored how AI retrieves data by converting user queries into vectors and finding the most relevant matches using similarity search.
🚀 Day 28 of #100daysOfAIEngineering
Yesterday, we were supposed to explore how the Retrieval component of the RAG (Retrieval-Augmented Generation) system works, but… we took a detour into the Model Context Protocol that's shaking up the AI industry.
#AI #aiengineering
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