Notes & Explorations

The Raspberry Pi AI HAT+ 2 positions the Raspberry Pi 5 as a practical edge-AI host for low-latency inference, sensor fusion, and compact automation. For techni

For a long time, software development followed a predictable, slow-moving arc: idea, weeks of architecture, months of boilerplate, and finally—if the motivation held—a launch.

In today's rapidly evolving technological landscape, the integration of artificial intelligence (AI) into traditional business processes is not just a trend...

In today's rapidly evolving technological landscape, artificial intelligence (AI) has become a cornerstone of innovation in product development. For...

A conversation on what it takes to replace SAAS software. Discuss why it is easy to replicate software systems using AI, but where actual difficulties lie...

A granular comparison of the software tools used to actually load and "chat" with your quantized model files.

A step-by-step guide to installing the claude CLI, authenticating your account, and running your first /init to index your codebase.

How to become a high-trust user by setting up automated "Hooks" (like auto-linting after an edit) and managing tool permissions so the AI never runs a...

The expert level: connecting Claude to your external world (Jira, Google Drive, Slack) via the Model Context Protocol (MCP) and spawning "Sub-Agents" to...

Software engineering is a field that is continuously evolving, spurred by both incremental advancements and groundbreaking innovations. As we move deeper into t...

How to build the "memory" of your project using a CLAUDE.md file to store coding standards, tech stack details, and recurring preferences that the agent reads...

An introduction to Anthropic’s CLI tool that shifts AI from a "chat window" to a specialized agent that lives inside your project files and executes real...

A deep dive into the "Think-Before-You-Code" workflow, where you review Claude’s multi-step implementation plans before giving it permission to touch a single...

In the realm of software development and AI-driven solutions, innovation and the ability to think beyond conventional boundaries are pivotal. Among the multitud

The most advanced level: using tools like n8n or Autogen to let your local AI actually file your taxes, organize your folders, or send draft emails.

An overview of how to transition from simply "talking" to your local model to connecting it to your personal data and local apps.

A guide to Retrieval-Augmented Generation (RAG), which allows your local model to search through your private PDFs, notes, and emails for instant answers.

A deeper dive into "Vision-Language Models" (VLMs) that allow you to ask your local AI questions about your personal photo library or screenshots.

The final "how-to" step: finding a model on Hugging Face, loading it into your software, and sending your first offline prompt.

A look at the "hidden" part of RAG: how tools like ChromaDB or lanceDB store your files as mathematical points so the AI can find them.

A look at the root cause of bias: how incomplete or historical datasets (like 50 years of male-dominated resumes) "teach" the AI to be discriminatory.

A technical look at the "shrinking" process (converting 16-bit files to 4-bit or 8-bit) that allows massive models to run on consumer-grade hardware.

An overview of the "unintended consequences" of AI, covering why we need rules for a technology that moves faster than our laws.

The most granular level: The technical process of "Red Teaming" and mathematical fairness checks used to catch these hidden biases before the AI is ever...

Going back to the high-level map (Article 1) and zooming into the branch that creates content (text, art, video).

The final "polish" where humans grade AI answers to make them safer, more accurate, and less "robotic."

A high-level guide to the "Big Three" requirements—VRAM, System RAM, and Storage—and how to audit your current specs for local LLM.

Zooming in on Generative AI specifically built for human conversation and text generation.

If you feed a machine data from an unfair world, it becomes an unfair machine; exploring how AI inherits human prejudices in hiring, lending, and law.

A deeper dive into "Proxies"—how an AI can discriminate against a group even if you hide their race or gender (e.g., using a "Zip Code" as a secret stand-in...

How an LLM goes from reading the entire internet to being a helpful assistant that follows instructions.

A deeper dive into Video RAM (VRAM), explaining why your graphics card’s memory is the single most important factor for speed and model size for local LLM.

An introduction to the benefits of running models on your own machine, from total data privacy to avoiding monthly subscription fees.

The landscape of software engineering continues to evolve at a rapid pace, with new methodologies, technologies, and concepts emerging to address the complexiti...

In the rapidly evolving landscape of modern technology, leadership within technical domains has undergone a profound transformation. This evolution is not merel...

In an era where technology is at the forefront of business evolution, the gap in skilled technology professionals continues to widen, posing significant challen...

Software engineering is a constantly evolving field where yesterday's innovations become today's fundamentals. Keeping pace with these advancements is critical ...

In the realm of artificial intelligence (AI), neural networks have taken center stage as a fundamental architecture that mirrors the complexity and functionalit...

In an era dominated by rapid technological advancements, machine learning (ML) emerges as a pivotal engine powering a myriad of transformative solutions across ...

Software development is undergoing a seismic shift, driven by advancements in artificial intelligence (AI), software engineering practices, technical leadership...

The most granular level: how a Transformer actually "looks" at a sentence and assigns mathematical weight to words.

The specific type of Neural Network that changed everything, allowing AI to understand context and sequences.

The realm of Artificial Intelligence (AI) is rapidly expanding, shaping the future of industries, revolutionizing how we interact with technology, and altering

The exponential growth in Artificial Intelligence (AI) technologies presents a unique inflection point for finance teams.

In the swift evolution of technology, the integration of Artificial Intelligence (AI) into DevOps has emerged as a transformative force, revolutionizing how dev

In today's rapidly evolving technological landscape, Artificial Intelligence (AI) stands at the forefront, not just as an innovation but as a defining force tha...

The technology landscape is evolving at an unprecedented pace, and programming languages sit at the core of this transformation.