EVERYONE is feeding their AI more data. Skills, docs, Slack history, all of it. đź“Ś One thing that matters most gets missed every time: the implicit working style and patterns you're not even aware of yourself. It's the same as how you sometimes can't tell
So, what's the problem?  ❌ The AI has no hands. It can't actually do anything.  ❌ The AI doesn't have the real-time data the task needs.  ❌ You're not giving the AI enough context (and ChatGPT's built-in memory can make it worse, pulling
Do you wanna get a Million Dollar Roadmap for the next 12 months? Let me tell you all - It was a incredible section from Queen of AI, Alicia Lyttle. Everything in 10 min! Use any AI who you works with the most, it could be ChatGPT, Claude, Genimi whatever.
Subtitle: A post-mortem on moving a multi-agent Claude Code + OpenCode setup — and what 14 cron jobs revealed about what's actually load-bearing. I've been running a small "Agent OS" — a thin orchestration layer that runs multiple coding agents on cron, each in its own workspace,
Subtitle: Paywalls, bloat, and broken updates — what 233 angry user bases are trying to tell us. I wasn't planning to do market research this week. I was looking for an app idea — something with real demand that I could actually build. So I pointed my AI agent at
Everyone talks about AI agents. Nobody talks about the bill. I run a team of 5 AI agents on a single Linux machine. They handle my daily briefings, draft tweets, scout for startup ideas, manage coding tasks, and monitor my infrastructure. They've been running for 54 days. I
What happened when I gave a PM role to an AI agent with Linear, Docker sandboxes, and merge permissions. I used to manage my AI coding agents myself. Define the task, dispatch the agent, review the PR, test it, merge it. Repeat. It worked. But I was still the bottleneck.
Today I listened to a podcast episode that touched on a topic I’ve been thinking about for months. As soon as it ended, I went straight to building a demo. To be honest, I don’t really like smartphones. Not in the sense that I don’t use one
I run a small team of AI agents. Each has a role: * 🔨 Forge — the builder. Ships code, deploys, manages the repo. * ⚡ Spark — the marketer. Writes copy, plans launches, does outreach. They have separate workspaces, separate repos, separate responsibilities. Clean separation of concerns. Standard stuff. Then Spark started submitting pull requests
I had my idea pipeline backwards for weeks. I thought marketing was the last step — build first, promote later. Then my marketing agent killed an idea in 10 minutes that my technical analysis said was a go. Here's what I got wrong, and the framework that fixed it.
I built 4 AI agents whose only job is to destroy my ideas. Not refine them. Not validate them. Destroy them. Here's why. When I have a new business idea, my instinct — like everyone's — is to look for reasons it will work. Confirmation bias kicks in
My last post talked about moving from "chatting with AI" to "appointing AI." But what happens after you appoint one? You give it a name. You give it memory. And you let it run. 🧊 Meet Chill Chill is my AI agent companion, built on OpenClaw — an
OpenAI’s frontier projects are moving beyond the text box. The shift toward "Agentic AI" (or Operators) isn't just a new feature—it’s a fundamental restructuring of how companies operate. Here are the 3 most interesting facts about this shift: ✅ From Tool to Teammate: Unlike
🤖 Anyone can build their own agent to manage daily stuff — including personal finance (without linking your bank). I recently built an agent that helps me track expenses + income + categories without relying on a “connect your bank” flow. And honestly? It solved a real pain point for me: ✅ No more manually
I’ve been experimenting with a different way to use AI in products: not just as a chat bubble, but as the thing that drives how the UI responds. 💬📊 As a testbed, I built an AI-first expense tracker with a simple layout: • Left: chat where you talk in plain language
I built an AI team that works completely autonomously—and it's wild to watch. 🤖 Not just automation. True autonomy. These agents literally sit at computers using git/bash/editors, making decisions like humans do. And here's the thing: this isn't just for developers. Think
Agentic AI is fundamentally reshaping how we approach automation and orchestration. 🔹 Where Agentic AI shines: Agents excel at tackling complex, ambiguous, or creative tasks—interpreting flexible goals, iterating plans, adapting to context, and synthesizing results. These AI-driven flows “soften the edges”—handling nuances, subjectivity, and unstructured data that previously required