The hardest part of building an AI agent platform isn't the technical complexity—it's choosing which tools to use when every option seems both perfect and overwhelming. The Ocean of Options Building an AI agent platform today means navigating an unprecedented landscape of choices. The sheer volume of available frameworks, tools, and platforms can quickly overwhelm … Continue reading AI Agent Frameworks: A Product-First Approach to the Problem of Plenty
Category: AI product management
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
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
The Plentiful Cybersecurity Problem: Too Many Vendors, Too Little Product Sense
Let’s get one thing out of the way - the market opportunity for cybersecurity as a whole - in the next 5 years, is humongous. Gartner predicts it will reach $267 billion in 2026, with an annual growth rate of 11%. If there is one domain where you find it difficult to find experienced professionals, … Continue reading The Plentiful Cybersecurity Problem: Too Many Vendors, Too Little Product Sense
Data Science Leadership Series – Part 3: Building Great Products by Balancing Product and Engineering Mindsets
I wrote about why we need AI Product Management when building complex data products in a previous post in the Data Science Leadership Series, and I feel this has to be followed by a very important topic that almost every single software development team faces, especially in high growth startups where the speed of innovation … Continue reading Data Science Leadership Series – Part 3: Building Great Products by Balancing Product and Engineering Mindsets
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
The Game Changer: Large Language Models Unleashing the Power of AI in Cybersecurity
Applied Machine Learning and AI in cybersecurity is slowly growing into mainstream industry, not just as an add-on anymore. As threat actors have started automating and streamlining a lot of their attack pipelines using off the shelf Large Language Models, the good actors are essentially forced to catch up with them ! It’s not just … Continue reading The Game Changer: Large Language Models Unleashing the Power of AI in Cybersecurity
Data Science Leadership Series – Part 2 : How to choose data projects: Core Product Vs Support Consulting Vs Research | Beware of your bottomline
The biggest challenge for data scientists / managers in decision making capacity and one with the biggest consequential outcome for both the business and the data team, I feel, is the part where you say yes / no / let’s modify - to a new data project idea from leadership, or even starting a new … Continue reading Data Science Leadership Series – Part 2 : How to choose data projects: Core Product Vs Support Consulting Vs Research | Beware of your bottomline
Data Science Leadership Series : Part 1 – The need for AI Product Management
People keep talking about data science being such a rewarding and lucrative career, but I feel it's time to talk about the serious gaps that's been bugging this field, in terms of operationalizing a successful data teams. Few tech companies like the Googles and Microsofts of the world have got this working like a well-oiled … Continue reading Data Science Leadership Series : Part 1 – The need for AI Product Management
Infinite Couch 