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Key Lessons in Building Production-Grade AI Agents
These key takeaways are distilled from an in-depth Productbulb Podcast interview with expert AI engineer Rajaswa Patil, who has been a key contributor to major projects like GitHub Copilot and Postman’s AI assistant, Postbot. This document serves as a practical guide for aspiring AI developers, offering insights into the real-world challenges and solutions involved in…
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The Product Bulb Podcast Ep. 07:
Lessons from Building AI Copilots – Secrets to Scaling AI Agents | with Rajaswa Patil Here’s a power packed episode – listen from a foundational AI engineer on scaling AI Agents. The world is captivated by the seemingly magical capabilities of large language models. But behind the curtain of every seamless AI assistant lies a…
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The Product Bulb Podcast Ep. 06: Production Generative AI – Practical Use Cases and Challenges | with Apurva Misra
Join us on this Product Bulb Podcast for a deep dive into the practical applications and challenges of production generative AI with expert AI consultant and machine learning engineer, Apurva Misra. Learn about real-world use cases like customer Q&A systems that reduced human support queries by 21% and innovative applications like allergen detection. Aura shares…
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Product Bulb Spotlight: No.2 | DUB
DUB https://www.dubapp.com/ (Founders: Steven Wang) Copy-trading platform Dub is a platform that allows users to automatically mirror or “copy” the investment portfolios of other users, including prominent figures like politicians and hedge fund managers. The key features of dub include:1. Copy Trading: Users can copy the portfolios of other investors, and their accounts will automatically execute…
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Understanding Production RAG Systems (Retrieval Augmented Generation)
1. What is RAG ? Retrieval Augmented Generation (RAG), is a method where you have a foundation model, and you have a library of personal documents – this can be unstructured data in any format. Now your goal is for answering some questions from your persona library of docs, with the help of LLM. Enter…
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KPIs for GTM | For AI Products
Key Performance Indicators (KPIs) for a Go-To-Market (GTM) strategy are essential for measuring the effectiveness of your approach and understanding whether the product is gaining traction in the market. These metrics will help evaluate how well the GTM strategy is working and identify areas for optimization. Here’s what you need to know about GTM KPIs…
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GTM examples from First Principles Framework
A Go-To-Market (GTM) strategy from a first principles framework involves breaking down the steps required to take a product to market into its most fundamental components. Applying this to AI products, or any technology, includes understanding the market, identifying the customer, defining the value proposition, and determining the optimal distribution and pricing models. To better…
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GTM Motions for AI Products
Go-To-Market (GTM) strategies for Generative AI (Gen AI) products need to account for the complexity, education, and the transformative potential of the technology. Modern Gen AI-based products, like AI models for content generation, image generation, or advanced NLP applications, often face challenges like trust, understanding, scalability, and integration. Below are some of the best GTM…
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Product Bulb Podcast : Ep. 01
Pricing Strategies for AI Products AI Generated Insights using Google’s NotebookLM This is wild..You can now input a podcast episode (like a Youtube Video link) to Google’s NotebookLM and get a summary podcast of 2 AI generated personas discussing your podcast !! Granted that it’s somewhat “too wordy” and one or both the personas try…
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