Prepared for: Enterprise AI Teams and AI/Security Leadership Based on: Publicly available information and Cursor's provided documentation from:https://www.cursor.com/security, https://trust.cursor.com/faq and https://trust.cursor.com/ Table of Contents Executive Summary Introduction to Cursor Core Security Architecture and Practices AI Request Processing and Data Handling Codebase Indexing: Functionality and Security Privacy Mode: Guarantees and Implementation Enterprise-Specific Features and Considerations Potential … Continue reading Detailed Security and Enterprise Readiness Report: Cursor AI IDE
Tag: AI product
Answer Your “Why” Before Building an AI Product
“People don’t buy what you do; they buy why you do it.”— Simon Sinek It's very common nowadays, to see teams chase every new coding assistant, chatbot, and AI agent—only to end up spinning in circles. So let's drill down here. When you let shiny tools dictate your roadmap, you muddle your product vision, lose … Continue reading Answer Your “Why” Before Building an AI Product
Quick Outline for Designing Data Pipelines for Machine Learning Projects
As a Machine Learning Engineer, designing a data pipeline involves ensuring data flow is efficient, scalable, reliable, and optimized for the requirements of ML models. Here’s a structured outline to keep in mind: 1. Data Ingestion Sources and Types: Identify data sources (e.g., databases, APIs, logs, IoT devices) and data types (structured, semi-structured, unstructured). Batch … Continue reading Quick Outline for Designing Data Pipelines for Machine Learning Projects
TIL Journal : Oct 03, 2024
AI GTM, Never ending quest of PMF, Most important slide in your pitch deck ... Topic 1: Source: Lenny's Podcast | Lessons from a 2-time unicorn builder, 50-time startup advisor and 20-time board member | Uri Levine Notes from my NotebookLM assistant: Here are some important takeaways from the podcast in a Q&A format: What … Continue reading TIL Journal : Oct 03, 2024
What’s LLM Observability ? Latest tools to look out for
2024 is looking to be the year where a lot of applied Large Language Models (LLMs) from enterprise companies, other than the creators of the foundation LLMs, are going to come out of the Proof of Concept (POC) phase to actually being used by their customers. It's gonna be a year of trial and error, … Continue reading What’s LLM Observability ? Latest tools to look out for
Sample Go-To-Market Strategy for an LLM feature- Translate natural language to query language in a database company
Large Language Models (LLMs) have significantly turned the tide towards AI applications being taken seriously by almost every company in every single domain. Now if you a Product Manager, you may come across the ask - Craft a Go-To-Market (GTM) strategy for an LLM feature. So here's a sample GTM strategy for a new LLM … Continue reading Sample Go-To-Market Strategy for an LLM feature- Translate natural language to query language in a database company
AI Product Management in Cybersecurity: McKinsey’s Three Horizons of Growth ? Flip it for startups, keep it for mega corps
What’s McKinsey’s Three Horizons of Growth ? The McKinsey’s Three Horizons of Growth is a management framework first introduced in the book “The Alchemy of Growth” published in 2000, which has since been referenced by top product strategists to help businesses execute existing business models while simultaneously innovating and pushing the boundaries and creating new … Continue reading AI Product Management in Cybersecurity: McKinsey’s Three Horizons of Growth ? Flip it for startups, keep it for mega corps
Infinite Couch 