#llm

Building a Centaur Chess App with AgentCore Runtime and Strands Agents

In 1998, Garry Kasparov proposed a new format: human players paired with computer assistance. He called it "Advanced Chess," though the community settled on a better name: centaur chess. The idea was

5h ago16 min read

RNRonie Neubauerronieneubauer.com

Sistemas Multi-Agentes com AI: Do Conceito à Produção

Todo mundo tá falando de "agentes de AI". Metade não sabe o que é. A outra metade tá construindo coisas que não precisavam ser multi-agent. Vou explicar do zero, passar pelos padrões de orquestração,

15h ago17 min read

CSClaudio Santosclaudiosantos.hashnode.dev

Image Prompts for LLMs, LangChain & CrewAI (Corporate Tech Style)

There’s a point in everyone’s journey with artificial intelligence when excitement turns into a more mature kind of curiosity. At first, it’s easy to be impressed: you ask a language model something,

37m ago9 min read

IKIvan Klawdblog.thecgaigroup.com

We Tried to Replace Claude with a Local Model. Here's What Happened.

We Tried to Replace Claude with a Local Model. Here's What Happened. By Ivan | CGAI Operations | February 2026 Every month we run a benchmark. Not for fun — for money. We run agents 24/7. They make hundreds of API calls a day. At that volume, every ...

47m ago7 min read

KGklement Gunnduklementgunndu1.hashnode.dev

Pydantic for AI Output Validation: Stop Parsing Raw LLM Strings

Pydantic for AI Output Validation: Stop Parsing Raw LLM Strings LLM outputs are strings. Treat them like strings and your agent breaks. We run 9 AI agent teams in production. Every team calls LLMs. Every LLM returns text. The question is what happens...

3h ago8 min read

SVSai Varnik Kammarisaivarnik.hashnode.dev

ELASTIC BLOGATHON 2026 Building a Simple RAG Pipeline with Elasticsearch as a Vector Database: A Practical Guide with Architecture, Code & Lessons Learned

By Software Engineer (GenAI / Search) | Elastic Blogathon 2026 | Theme: Vectorized Thinking Abstract Retrieval-Augmented Generation (RAG) is reshaping how developers build AI-powered search and q

1d ago10 min read

LDLightning Developertech-odyssey.hashnode.dev

Beyond OpenAI: Taking Back Your AI Privacy in 2026

In 2026, the digital landscape has shifted significantly. While ChatGPT remains a household name, a quiet revolution has taken place in the world of open-source AI. We are no longer tethered to a sing

1d ago5 min read

YSYusuf Solomonysolomon.hashnode.dev

Building a Philosophical Debate Agent with LangGraph

Introduction One of the best use cases of large language models is research, especially when the model has access to the internet and can query information from different sources. This particular proc

1d ago16 min read

KKashifblog.ifkash.dev

Teaching Llama 3 to be Polite

The Objective The goal of this project was to take a powerful open-source Large Language Model (LLM) and instill a strict behavioral constraint: the model must politely decline to answer any request t

2d ago8 min read

NANikhil Adithyanfreecodecamp.org

How to Build an LLM Market Copilot MVP with LangChain, APIs, and Streamlit

In fintech or wealthtech products, people constantly need quick market context. They need to know why a particular stock moved, what changed recently, or what they should watch next. This usually beco

1d ago36 min read

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#llm

Building a Centaur Chess App with AgentCore Runtime and Strands Agents

Sistemas Multi-Agentes com AI: Do Conceito à Produção

Image Prompts for LLMs, LangChain & CrewAI (Corporate Tech Style)

We Tried to Replace Claude with a Local Model. Here's What Happened.

Pydantic for AI Output Validation: Stop Parsing Raw LLM Strings

ELASTIC BLOGATHON 2026 Building a Simple RAG Pipeline with Elasticsearch as a Vector Database: A Practical Guide with Architecture, Code & Lessons Learned

Beyond OpenAI: Taking Back Your AI Privacy in 2026

Building a Philosophical Debate Agent with LangGraph

Teaching Llama 3 to be Polite

How to Build an LLM Market Copilot MVP with LangChain, APIs, and Streamlit

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#llm

Building a Centaur Chess App with AgentCore Runtime and Strands Agents

Sistemas Multi-Agentes com AI: Do Conceito à Produção

Image Prompts for LLMs, LangChain & CrewAI (Corporate Tech Style)

We Tried to Replace Claude with a Local Model. Here's What Happened.

Pydantic for AI Output Validation: Stop Parsing Raw LLM Strings

ELASTIC BLOGATHON 2026 Building a Simple RAG Pipeline with Elasticsearch as a Vector Database: A Practical Guide with Architecture, Code & Lessons Learned

Beyond OpenAI: Taking Back Your AI Privacy in 2026

Building a Philosophical Debate Agent with LangGraph

Teaching Llama 3 to be Polite

How to Build an LLM Market Copilot MVP with LangChain, APIs, and Streamlit