(Total 44)

  • SDLC - QA

    The QA role is quietly transforming from testing interfaces to evaluating agent behavior and reasoning. Instead of pass/fail scripts, testers now focus on behavior coverage, feedback loops, and system observability. Quality is no longer just about functionality — it’s about understanding why an AI system acted the way it did.
  • SDLC - Agile to Agentic

    Agile gave us structure, but startups are now exploring agentic workflows where AI contributes directly to planning, estimation, and execution. Core practices like backlog grooming, story pointing, and burndown tracking are being reimagined — with agents assisting, suggesting, and sometimes completing tasks. This shift isn’t just about speed, but about redefining how teams work and who’s doing the work.
  • Motion Meaning Metrics

    As AI transforms how we work and think, it’s critical to understand who does what—between humans and machines. This framework maps roles across physics, philosophy, and business using RACI and the 4 A’s of AI (Assist, Automate, Augment, Autonomy). It’s a guide to help you define the boundaries between motion, meaning, and machine. I got to do some deep and theoretical work on my flight back from Europe over the weekend (nothing better for than no WiFi, limited in-flight infotainment).
  • ChatPilot

    We’re building a semantic search system to surface past support tickets that match the meaning—not just the keywords—of new incoming requests. Our current approach involves cleaning and chunking historical data, embedding it using models like OpenAI or Hugging Face, and storing it in a vector database for real-time retrieval. We’re also exploring RAG-style workflows and would love to hear from others who’ve tackled semantic retrieval at scale.
  • Swipe and Filter

    The pace of AI innovation is now so fast that even experts struggle to keep up, with dozens of major releases happening weekly. To manage this overwhelming firehose of updates, I use a simple swipe-based mental model — left for irrelevant, right for interesting, and down for important — helping me stay focused and reduce FOMO. In the AI era, the real advantage isn’t knowing everything, but knowing what to ignore.
  • Distribution Led Growth

    As building product becomes cheaper and easier, the real differentiator has shifted from product-led growth to distribution-led growth. Valuations are increasingly tied to how well a company scales — not just what it ships — with GTM strategy becoming the new moat. The smartest teams are now designing distribution into the product from day one, treating it as a core system, not a separate phase.
  • Vibe Refactoring

    Sometimes vibe coding isn’t about shipping new features—it’s about cleaning up old ones with precision. I used Cursor’s agent to refactor mislabeled code in my app, turning what would’ve been a tedious manual task into a smooth, efficient flow. Agentic development brings the same creative energy to refactoring as it does to building.
  • Rufus Rant

    Even trillion-dollar companies can stumble with AI when context is missing. When I asked Amazon’s AI assistant, Rufus, to compare selfie sticks in my cart, it gave generic responses and then admitted it didn’t actually have access to my cart. The lesson? Don’t fake AI intelligence—transparency builds trust, especially at key decision moments.
  • Decision Augmentation

    What started as an impromptu pitch at Tech Alpharetta turned into a pivotal moment in my startup journey. Sharing the vision behind Finciples — a decision-support platform that brings legendary investment principles into the Intelligence Age — sparked challenging but invaluable feedback from seasoned mentors. What resonated most wasn’t just the tool, but the idea that AI should augment human judgment, not replace it — a message that left the room curious, engaged, and ready for more.
  • Lock Screen Widgets

    What begins as a simple desire to replace the iPhone’s lock screen camera with Perplexity reveals a deeper shift: AI tools are becoming ambient, something we want immediate, intuitive access to — not tucked away behind apps and tabs. The friction isn’t just technical, it’s conceptual — we’re starting to expect AI to be where we are, when we need it, as naturally as a flashlight or camera. And that’s not an Apple rant — it’s a signal that our relationship with technology is evolving from app-first to intent-first.
  • Podium to Prompts

    Storytelling isn’t just for humans anymore—it’s how we influence machines, too. In a conversation with Neha Negandhi, we explored how the same principles that captivate audiences on stage can make prompts more powerful and aligned when interacting with AI. Those who master storytelling—whether to people or algorithms—will hold the ultimate leverage in this new era of communication.
  • Pair Programming is better than Vibe Coding

    Vibe coding may feel trendy, but for serious programmers, it’s a risky shortcut. Instead, pairing with AI as a coding partner allows you to stay in control—using AI to assist, not replace, your thinking. Treat AI like a teammate in your Scrum team: ask specific questions, review outputs, and always own the final outcome.
  • Founders and Subconscious Branding

    Our product choices aren’t purely logical—they’re shaped by subconscious signals like founder visibility, storytelling, and personal moments that build trust. Tools like ChatGPT, Perplexity, and Grok became my defaults not just for their features, but because their founders live rent-free in my head through podcasts, interviews, and media presence. In the AI era, founder-led storytelling isn’t vanity—it’s the new moat.
  • Vibe Debugging

    In the world of programming, much of the real work isn’t about writing code—it’s about debugging invisible, maddening issues that don’t show up in tutorials. While building an AI chatbot, I hit a CORS error that only appeared on my machine, leading to hours of vibe debugging until ChatGPT pointed me to an unexpected culprit: AirPlay was using port 5000. This experience reminded me that the hardest bugs often live not in the code itself, but in the environment, and the real skill is staying calm and curious in the messy middle.
  • AI Conversations - Conference Rooms to Kitchen Tables

    AI is no longer just a conference room conference call — it’s becoming deeply personal. Last night Pooja Rastogi a Sr. Project Manager came over, not to chat casually, but to explore how she could bring AI into her workplace. Over tea, we went from tool choices to transformation arcs, showing that the most powerful AI adoption while may get started in a corporate setting is often amplified through trusted, everyday conversations
  • Cognitive Leverage and Judgement

    As capital and knowledge become widely accessible, the advantage no longer lies in having them—but in how you use them. Just as capital leverage moved from access to allocation, cognitive leverage is shifting from scarcity to judgment. In a world of abundant tools, the true edge is clarity, synthesis, and decisive action.
  • Pricing Outcomes - AI Projects and Products

    AI Musings - Pricing Dilemma. AI has made it cheaper than ever to build, but expensive to run — exposing a gap between how value is delivered and how it’s priced. While outcome-based pricing is becoming the ideal, most still default to time or feature-based models because true impact is hard to quantify. The real challenge is figuring out how to price cognitive leverage — not just effort. This post explores that tension and invites others to share how they’re navigating pricing in an AI-driven world.
  • AI Agents are not teammates

    AI Musings - AI Agents are not teammates. AI agents are powerful tools — but they’re not teammates. You can build efficiently with them, but real growth, momentum, and accountability still come from working with people. In an AI-first world, the stack may scale your output, but it’s the human connection that sustains your journey.
  • Build in Public - Writing

    This post shares my journey from casually posting on LinkedIn to building a structured content workflow under the Build In Public moniker. It highlights how I use simple tools—like Markdown, GitHub Pages, and spreadsheets—alongside AI to refine ideas, maintain consistency, and publish across platforms. The goal: write in public, stay in control, and let the system power creativity.
  • Three Men and AI

    Building a B2C app isn’t just about vibe coding your way to a product—it takes clarity, structure, and the right leverage. With just three core builders, we’ve used AI as a co-pilot across roles—from product vision to backend architecture—turning vague ideas into executable momentum. It’s not about replacing thinking, but expanding capability through AI-augmented strategy and agent-powered execution.
  • Writing Process

    A personal look at how I’ve built a repeatable system for writing — from idea intake to publishing. While the intent and voice remain human, tools like ChatGPT and Perplexity now automate parts of research and augment synthesis, accelerating both clarity and output.
  • Flywheel Motion

    A well-designed flywheel doesn’t just spin faster — it becomes inevitable. And behind the scenes, AI is amplifying every turn — helping us capture insights faster, spot patterns earlier, and move from idea to action.
  • New meaning of Who not How

    We used to ask: “Who can help me get this done?” Now, in the Intelligent Age, the better question is: Which Agent can do this for me?”. This shift isn’t subtle — it’s a complete rethinking of leverage.
  • AI Tech Ecosystem

    Agentic AI is shifting from modular tools to full ecosystems like Google’s Agentspace, pushing developers to choose platforms, not just models. The big question now is when — and how — to go all-in on an ecosystem.
  • Outcomes and experiences over engineering

    We need to focus on AI’s impact and user experience, not its mechanics, emphasizing seamless integration and empowering outcomes over technical details.
  • Why do I need AI Agents if I have ChatGPT?

    AI agents complement ChatGPT by enabling contextual memory, workflows, collaboration, observability, and autonomy, making them essential for business operations beyond simple assistance.
  • Vibe Design

    When building product ideas, I move from sketches and mind maps to “vibe writing” specs with ChatGPT and then “vibe coding” with Claude and Cursor, but I’ve realized I’m missing a “vibe design” step in between. I’m looking for a tool that feels like a Copilot for UX/UI — something that helps me quickly sketch and refine prototypes without jumping straight into code.
  • Content Creators vs Content Consumers

    We examine the gap between creators and consumers, highlighting AI’s role in empowering developers and non-developers while questioning universal coding adoption.
  • My AI Toolkit Apr 2025

    This post explores AI tools for research and creative work, highlights ChatGPT and Claude+Cursor, and envisions AI agents to streamline work management.
  • The New Age Interview

    Reflects on rigorous interview preparation, including Amazon’s structured process, leadership principles, STAR-format storytelling, and lessons from a Fractional CTO interview.
  • Eisenhower Matrix in the Age of AI Agents

    AI agents redefine delegation in the Eisenhower Matrix, automating tasks like scheduling, note-taking, CRM updates, and document synthesis for enhanced productivity.
  • Storytelling, Learning, Communicating

    Reflections on storytelling, authenticity, and AI’s impact on learning, emotions, and communication, sparked by a talk and ongoing conversations about AI’s evolving role.
  • Flow State

    Explores achieving flow state through environment, tools, and AI-enhanced workflows for writing, drawing, and coding, highlighting AI’s role in sustaining creativity.
  • $20 for paid plans

    Reflects on the $20 pricing standard for AI tools, exploring market competitiveness, perceived value, and psychological pricing while seeking insights on pricing strategies.
  • Agentic Architecture and Design Principles

    Design agentic systems by leveraging OOP, modularization, low-code tools, traditional tech stacks, and staying updated on AI trends for scalable, efficient architectures.
  • The Evolution of Work: Roles, Processes, Decision Making

    This post explores AI’s impact on organizational roles, processes, and decision-making, highlighting shifts in workflows, leadership, and human-AI collaboration.
  • Rise of Agents

    This post explores the future of AI agents in enterprises, addressing governance, marketplaces, training, and their integration alongside human workers.
  • UX of BI vs AI

    We explore transitioning from traditional BI UX to AI-driven Copilot interfaces for data interaction, seeking tools and ideas for implementation.
  • Where Do You Collaborate?

    Explores collaboration among builders, sharing personal methods like leveraging networks, meetups, and tech scenes, while seeking the best platforms for meaningful engagement.
  • AI Mindset

    If Mindset is Everything, here’s what’s been shifting mine. Lately, I’ve been consuming a mix of thought-provoking ideas that are reshaping how I think about AI, intelligence, and work. No particular order—just perspectives that have made me pause and rethink:
  • AI Tech Stack

    Sharing the author’s AI tech stack, covering tools for research, marketing, design, coding, content creation, and LLM provisioning, inviting readers to share theirs.
  • Model Context Protocol

    Exploring Model Context Protocols (MCPs), their server setups, integration options, and potential for improving content aggregation and synchronization in multi-sided marketplaces.
  • Agentic Architecture and Design Principles

    Agentic system design emphasizes modularity, atomic agents, low-code tools, traditional tech stacks for complexity, and preparing for purpose-built LLMs and evolving AI UX.
  • Workflows and Decisions

    AI-driven agents in retail enhance decision-making by automating workflows, analyzing data, and providing dynamic recommendations while involving humans for complex judgments.