Intake:Digital

Your thoughts on AI First, review what would be released publicly Your name and account details won’t be attached, but anyone can read what you make public: your employer, people you know, governments, and strangers. Your country (United States) will also be shared. Hello! I’m an AI interviewer from Anthropic. As AI is becoming more capable and more consequential, we want to hear how it’s showing up in… Expand start Great — let's dive in. To start, what's the last thing you used AI for? AI was last used to write and debug a custom Python script for parsing documentation. Thanks — that gives me a concrete picture. Now, thinking more broadly: can you tell me about your most memorable moment with AI? the most memorable moment was when it first became more organized for letting AI help organize my daily workload, summarize information, and plan projects. That sounds like a shift in how you worked day to day. Can you walk me through what that actually looked like — what were you do...

Let’s explore this **together**, like curious co-creators building something meaningful step by step. You asked me to **guide you step by step to create the Python script** — perfect! This will turn everything we’ve uncovered (the extracted poem + the 15 SEO keywords) into a clean, reusable offline package. Before we begin, pause and ask yourself: - What do you want this script to **do** when you run it? (Store the poem, output the keywords as a comma-separated string, auto-create a README.md file, and give you instructions for zipping everything?) - Why is learning to build it yourself more powerful than just receiving a finished file? If that sparks your curiosity, let’s walk through it **one mindful step at a time**. I’ll ask you a question after each step so you can truly own the process. --- ### Step 1: Choose your workspace & create the file Open your favorite code editor (VS Code, PyCharm, even Notepad++). Create a new folder on your desktop called `poem-s...

Building Your First Local LLM App AZLOKISME JANUARY 13, 2026 INTRO Not long ago, using powerful AI meant sending your data to distant server farms. It was like renting a supercomputer; useful, but not personal. Now, with efficient models like Llama 3 and tools like Ollama, things have changed. You can run AI on your own machine. In this article, I’ll walk you through building your first local LLM app, even if you’re new to LLMs. Build a Local LLM App: Getting Started We’ll build a working chat-based AI app in Python that runs only on your computer. Your data stays private, there are no API fees, and it’s just you and your code. To follow along, you need a few dependencies: Install Python: Ensure you have Python installed (version 3.8 or higher is recommended). Install Ollama: Go to ollama.com and download the installer for your OS. Once installed, open your terminal and run:  ollama pull llama3.2 This command downloads the core model we’ll use. Next, open your terminal and install ...