Blog

April 7, 2026

Engineering An AI Agent To Navigate Large-scale Event Data - Part 2

Part 2: From Query Patterns to Intelligent Tools & Agent Design

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July 8, 2025

Model Context Protocol

Anthropic's Model Context Protocol (MCP) is revolutionizing AI integration by providing a standardized way for LLMs to connect with external systems. Learn the core concepts, architecture, and build a practical Hacker News server that extends Claude's capabilities with real-time data access.

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June 26, 2025

The Great Data Divergence: Why Generative AI Demands a New Approach Beyond the Data Lake

The slow, batch-processing nature of the data lake is obsolete for modern Generative AI, which requires instant access to fresh data. In this article, the author proposes a shift away from centralizing data, advocating instead for an API-first approach. This allows AI applications to directly and quickly access live data from its source, enabling truly real-time, responsive features.

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May 27, 2025

Prompt Deployment Goes Wrong: xAI Grok's Obsession with White Genocide

An analysis of the May 2025 incident where xAI's Grok chatbot began inappropriately referencing 'white genocide' in South Africa. This post-mortem delves into the probable cause—a flawed post-processing prompt—framing it as a critical MLOps failure. It underscores the necessity of treating prompts as key artifacts, implementing progressive deployment strategies, and using appropriate metrics for AI safety and reliability.

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May 26, 2025

Hackathon Speedrun: Build & Deploy a RAG App in Minutes with Vertex AI Studio & Vertex AI Search!

This article provides a quick guide for building and deploying a Retrieval Augmented Generation (RAG) application in minutes, perfect for hackathon environments. It details how to leverage Google Cloud's Vertex AI Studio and Vertex AI Search to create a grounded Large Language Model (LLM) application that can answer questions based on a specific knowledge base, such as company documentation. The process involves preparing data in Google Cloud Storage, creating a searchable data store with Vertex AI Search, crafting and grounding a prompt in Vertex AI Studio, and then deploying the AI assistant as a web app using Cloud Run. The guide emphasizes speed and automation, allowing users to focus on data and user experience rather than complex technical setups.

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May 22, 2025

Should You Use Graph-based Vector Database for Multimodal AI?

As AI systems grow more multimodal and context-aware, traditional vector stores fall short. Graph-based vector databases offer a way to model relationships, context, and connections, making them an increasingly practical choice for modern AI applications.

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May 12, 2025

Blueprints for the Agentic Era: Inside the Revolution Transforming Enterprise AI

At a packed Microsoft Reactor event in SF, CrewAI, LlamaIndex, and Lambda laid out how agents are quietly becoming core enterprise infrastructure. From scaling headaches to state management, cost tradeoffs to hallucination risks, this wasn’t a hype fest - it was a hands-on look at what it really takes to get agents into production.

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May 12, 2025

GenV: An Agentic Workflow for Actionable Insights from Google Meet Recordings

This blog introduces GenV (Generative AI for Video Analytics), a practical Python-based agent designed to extract actionable insights from Google Meet recordings using multimodal AI. Built with tools like Google Colab, Google Cloud Storage, and Vertex AI's Gemini models, GenV automates the tedious process of summarizing meetings, identifying action items, and capturing key decisions. The workflow—Locate → Prepare → Analyze → Report—leverages structured Pydantic schemas to ensure consistent and useful outputs such as summaries, project discussions, and technical insights. The result is a powerful demonstration of how focused, agentic AI can streamline knowledge retrieval and improve meeting productivity, especially for professionals in AI and MLOps.

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May 6, 2025

When Prompt Deployment Goes Wrong: MLOps Lessons from ChatGPT’s 'Sycophantic' Rollback

An analysis of the April 2025 GPT-4o sycophancy incident through the lens of MLOps. Learn why prompt changes demand rigorous deployment strategies (Canary, Shadow) and how neglecting MLOps/LLMOps principles impacts AI safety and user trust in Large Language Models (LLMs) and Machine Learning systems.

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April 29, 2025

BKFC: An Agentic Workflow for Gathering Knowledge from Google Chat

This article introduces BKFC (Build Knowledge From Chats), a Python notebook designed as an agentic workflow to tackle the common problem of extracting useful information from cluttered Google Chat histories. The author explains how manually searching through chats is inefficient. BKFC automates this by fetching recent messages via the Google Chat API, processing them, and then using Vertex AI's Gemini model for analysis. Crucially, it prompts Gemini to return structured insights (like summaries, Q&A, action items, project updates) based on a predefined Pydantic schema. The tool demonstrates a practical way to use AI (specifically Gen AI and APIs) to turn conversational data into organized, actionable knowledge, saving time and improving team awareness.

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