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SMSusie Mccoywriteforusai.hashnode.dev2h ago · 5 min read

Build Your First AI Chatbot Using an LLM API

Large Language Models (LLMs) have made it possible to build a working, intelligent chatbot in an afternoon — no machine learning background required. This guide walks through the architecture, the too

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PRPriya Ramanarchybase.hashnode.dev7h ago · 7 min read

Text Prompts Can't Hold a Floor Plan Together. Here's What We Do Instead.

By Priya Raman, AI/ML Engineer at ArchyBase, working on spatial reasoning for floor plan generation If you've spent any time prompting an image model to produce a floor plan with a specific footprint

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NKNguyên Khangtechnologydecoded.hashnode.dev1d ago · 15 min read

The AI Revolution Isn't About Bigger Models—It's About Agents and MCP

No longer limited to conventional "Q&A" chat windows, artificial intelligence is making a powerful shift into the era of AI Agents — collaborators capable of autonomous reasoning, action, and end-to-e

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RVRahul Vijayvergiyarahulvijayvergiya.hashnode.dev1d ago · 6 min read

AI Fundamentals for Developers: Tokens, Vectors and Embeddings

If you're reading about AI, LLMs, or RAG, you'll hear terms like tokens, vectors, and embeddings all the time. They may sound complicated, but the basic idea is quite simple. Computers don't understan

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MLManuel Langai-control-plane.hashnode.dev18h ago · 5 min read

Beyond the Baseline: How Strategic Leaders Upgrade AI from an Author to an Adversary

A freelancer recently published a post comparing AI models, landing on a curious conclusion: he preferred one platform simply because its ecosystem allowed him to chat hands-free in his car about "ran

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HSHarshal Shahdelvingwithharshal.hashnode.dev1d ago · 7 min read

AI Threat Modeling: A Complete Guide to Securing AI Applications

As AI applications become increasingly integrated into business operations, securing them is no longer optional. Traditional security approaches alone are not enough. Organizations must understand the

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ISIkraj Singhikrajsingh.hashnode.dev2d ago · 13 min read

Data Engineering in the Age of GenAI

This article is written in my personal capacity. The views expressed are my own and do not represent Amazon or my employer. Examples are based on public information and synthetic scenarios; no confide

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VKVinay Kumarn4ryn.hashnode.dev1d ago · 9 min read

Where RAG Fails: Understanding the Limitations of Retrieval Augmented Generation

Artificial Intelligence has become incredibly good at answering questions, writing code, summarizing documents, and assisting with everyday tasks. But if you've ever asked an AI about something that h

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HPHarsh Prajapatiharsh-prajapati.hashnode.dev1d ago · 11 min read

Where RAG Fails: Understanding the Limitations

If you've spent any time in the Generative AI space over the last couple of years, you've heard the term RAG — Retrieval-Augmented Generation — thrown around as the fix for almost every LLM problem. N

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YSYuvraj Singhtechwithyuvi.hashnode.dev2d ago · 9 min read

Building My First Multi-Agent App Builder with LangGraph

I have been working extensively with AI since 2023. Over the last few years, I have built applications using provider APIs, written prompts that could qualify as short essays, worked on context engine

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#generative-ai

Explore Hashnode

Trending tags this week

Build Your First AI Chatbot Using an LLM API

Text Prompts Can't Hold a Floor Plan Together. Here's What We Do Instead.

The AI Revolution Isn't About Bigger Models—It's About Agents and MCP

AI Fundamentals for Developers: Tokens, Vectors and Embeddings

Beyond the Baseline: How Strategic Leaders Upgrade AI from an Author to an Adversary

AI Threat Modeling: A Complete Guide to Securing AI Applications

Data Engineering in the Age of GenAI

Where RAG Fails: Understanding the Limitations of Retrieval Augmented Generation

Where RAG Fails: Understanding the Limitations

Building My First Multi-Agent App Builder with LangGraph