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What Makes You The Number 1 Product Manager?

Amazon often does this thing where they start with the customer instead of just coming up with a product and then trying to figure out how to sell it. They call it " working backwards. " This strategy totally works for any product decisions, but it's especially important when they're making something new. The Press Release Exercise When it comes to launching new stuff, product managers usually start by writing a press release for customers. This press release is all about their pain points, how current solutions fall short, and how the new product is going to crush it. If the benefits don't get customers excited, the product manager needs to keep tweaking the press release until it sounds super awesome. It's way easier and cheaper to make changes to a press release than it is to change the product itself. Here’s a template I use to describe a new service or product: Main heade r: The product name anyone directly understands, like “Ultra-compact power charger”

Beyond Ctrl+F - Use LLM's For PDF Analysis

PDFs are everywhere, seemingly indestructible, and present in our daily lives at all thinkable and unthinkable positions. We've all got mountains of them, and even companies shouting about "digital transformation" haven't managed to escape their clutches. Now, I'm a product guy, not a document management guru. But I started thinking: if PDFs are omnipresent in our existence, why not throw some cutting-edge AI at the problem? Maybe Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) could be the answer. Don't get me wrong, PDF search indexes like Solr exist, but they're basically glorified Ctrl+F. They point you to the right file, but don't actually help you understand what's in it. And sure, Microsoft Fabric's got some fancy PDF Q&A stuff, but it's a complex beast with a hefty price tag. That's why I decided to experiment with LLMs and RAG. My idea? An intelligent knowledge base built on top of our existing P

Run Llama3 (or any LLM / SLM) on Your MacBook in 2024

I'm gonna be real with you: the Cloud and SaaS / PaaS is great... until it isn't. When you're elbow-deep in doing something with the likes of ChatGPT or Gemini or whatever, the last thing you need is your AI assistant starts choking (It seems that upper network connection was reset) because 5G or the local WiFi crapped out or some server halfway across the world is having a meltdown(s). That's why I'm all about running large language models (LLMs) like Llama3 locally. Yep, right on your trusty MacBook. Sure, the cloud's got its perks, but here's why local is the way to go, especially for me: Privacy:  When you're brainstorming the next big thing, you don't want your ideas floating around on some random server. Keeping your data local means it's  yours , and that's a level of control I can get behind. Offline = Uninterrupted Flow:  Whether you're on a plane, at a coffee shop with spotty wifi, or just hate being at the mercy of your interne

Key Principles for Building the Best Products and Companies

If you're a product person, you know it's not just about the features. It's about building something people actually want and love. But it's easy to get caught up in the weeds: endless feature lists, chasing shiny tech, and forgetting who you're really building for. A Story From My Corporate Days We were about to launch a brand-new sustainability product. We'd done the research, got customer feedback, even lined up beta users – everything by the book. Then, in the kickoff meeting, a manager pipes up, "We need at least 30 people to fast-track this." I looked at him like he'd sprouted a second head. "Why?" I asked. His response? "Because with that many people, we'll be important." Honestly, it was like my brain short-circuited. What the hell? I told him, "I could snag 100 people from the train station in an hour, but that doesn't mean we'd get anything done."  Side note: the project died. Not because of a lac

OSX improved (Update)

Updated May 17, 2024 to fit M* architecture My favorite development environment on my MacBook includes an improved Zsh shell and an extended .vimrc configuration file with syntax highlighting, error checking, TextMate snippets, and the Solarized color scheme.  Here's a guide for setting up similar features:  The features include directional key navigation for directories and files, developer-friendly colors, command highlighting, improved history search, auto-complete for options and SSH connections (if keys are known), and many more useful enhancements.   Get Xcode:  AppStore => Xcode => Install Xcode From now we use a terminal window. Install Brew /usr/bin/ruby -e "$(curl -fsSL" Install git and wget:   brew install git   brew install wget Install oh-my-zsh:   wget --no-check-certificate -O - | sh The script want

AI in Product Development?

I like product ideation brainstorming—done right and focused,  it opens my mind to think much more analytically about an idea, its development, and its trajectory. But on the other hand, I often had brainstorming sessions, and they were just a waste of time. And to be honest, can you count how often a session went sideways, got stuck in the same old thought patterns, and the loudest voices in the room dominate the conversation?  I did a test yesterday with GPT-4o, and it blew the lid off my creative potential. I had tried the same exercise with the earlier models, and it was a colossal waste of time and energy. Adding AI To The Product Team, worth? Short, after the test, yes, it's definitely worth. Why? We as startup founders, product managers or developer, our job isn't just about executing on a roadmap, we have to build the roadmap and come up with the  right  product idea at the right time - in the first place. That means staying ahead of the curve, spotting opportunities w

What The Heck is XOps in Product Development?

First: XOps is not a new Marvell movie, waiting for Wolverine's revival. Period. XOps FTW  I'm a CPO. I'm not an HR expert, and I sure as hell don't want to spend my days mediating squabbles between product, design, sales and data teams. But here's the thing I've learned the hard way: if you want to build products that actually solve user problems and hit your business goals, you better figure out how to make these folks play nice in the sandbox. XOps might sound like something out of a comic book, but it's a mindset shift, a way of structuring your teams and their workflows to truly put the customer at the core of everything. Think of it as the secret sauce that turns a bunch of smart individuals into a cohesive product-building machine. I'm too lazy to write what XOps means, DevOpsSchool did it already:  XOps stands for “Cross-functional Operations,” which refers to the practice of bringing together teams and individuals from different functional area

How to Nail Your Product Definition

Let's be honest, most product definitions suck. They're either packed with jargon that makes your eyes glaze over, filled with features nobody gives a crap about, or so vague they could be about anything. And most importantly, they totally miss the unfair advantage. Wait, what the hell is an unfair advantage?  Simply, it's the killer feature or a strategic edge that's so good, the others can't even copy it. It can be so simple as a dark mode, or an App Store feature to let competitors hook in. It's like building with Lego: you want that one foundational piece that's the base for everything else. Start with a simple square? Cool. But with the right unfair advantage, you can build it into a freaking skyscraper that everyone wants a piece of. Let me break down how I start to build new products. Step 1: Forget the "What," Focus on the "Why" (and How It Makes Users' Lives Easier)  Simplified: Customer Problem > Fancy Features  If you c

It's 2024, Hacking Your Way to Truly Useful Products

Last weekend I got again fed up by SaaS companies and their permanent "digital engagement" noise, so I canceled. You guess what really fed me up then? The extortion when I cancel my subscription, leading to mandatory, useless interrogation practice - surveys: "We want to understand why you want to cancel" with dozens of questions! Folks, when you DON'T understand why and when customers cancel and why your awesome product has more churn than all wholesale companies combined , then your complete product metrics (if any) are wrong and your product team needs to reevaluate how they build products. Yes, the tech startup bubble obsesses over user and customer engagement. Your investors tell you that, the "marketing" gurus, "influencers," and I don't know who else. They tell you to push notifications, implement annoying gamification,and endless "sticky" features, desperately trying to keep eyeballs locked on our products and services.

Rethinking Product Management: Flexibility and Customer Obsession for Success

I've been building products for a long time now, moving from Solution Engineer and Solution Architect over Product Manager to my current role as CPO. Along the way, I've seen the landscape shift dramatically. One thing's for sure: if you want to create products that customers truly love (and that drive real business results), you need to stay obsessed with their experience. That means rethinking some of the old "tried and true" ways of doing things. Don't: Just Adding Features Experience is critical for building customer loyalty: A great interface sells software. No great customer experience, no sales. Product management isn't about mindlessly churning out features. It starts with a deep understanding of your customers, the market and your competition. What drives the customer behavior? What are their biggest pain points?  To answer those questions, you need a toolkit that includes research, analytics, and direct feedback channels. This empathy for your cu

AI's False Reality: Understanding Hallucination

Artificial Intelligence (AI) has leapfrogged to the poster child of technological innovation, on track to transform industries in a scale similar to the Industrial Revolution of the 1800s. But in this case, as cutting-edge technology, AI presents its own unique challenge, exploiting our human behavior of "love to trust", we as humans face a challenge: AI hallucinations. This phenomenon, where AI models generate outputs that are factually incorrect, misleading, or entirely fabricated, raises complex questions about the reliability and trust of AI models and larger systems. The tendency for AI to hallucinate comes from several interrelated factors. Overfitting – a condition where models become overly specialized to their training data – can lead to confident but wildly inaccurate responses when presented with novel scenarios (Guo et al., 2017). Moreover, biases embedded within datasets shape the models' understanding of the world; if these datasets are flawed or unreprese