Hex Explained
The hex is a constraint framework for building AI workflows. Six skills, six commands, one config. It maps directly to how Anthropic's Model Context Protocol architecture actually works — not as a metaphor, but as a design spec. The hex exists because the problem was never "which AI
Gpt Deep
OpenAI has announced more developer products than any other AI company. The API. Fine-tuning. The GPT Store. Plugins — then not plugins. Assistants API v1 — then v2. Function calling. The Responses API. A growing stack of SDKs. Every Dev Day brings new features, new frameworks, new promises about what developers can
Gpt Deep
Most people who use ChatGPT don't know the API exists. Most developers who use the API rarely open ChatGPT. And the people who use both regularly understand something that OpenAI's marketing obscures — these are fundamentally different products that share models but offer different capabilities, different pricing,
Gpt Deep
OpenAI has shipped not one but two distinct image generation systems inside ChatGPT, and the interface doesn't make the distinction clear. DALL-E 3 — the older, more controlled system — and GPT-4o native image generation — the newer, more flexible, less predictable one — coexist in the same product. When you ask
Gpt Deep
The demo was the moment everyone decided the future had arrived. OpenAI showed a model that could hear you speak, understand your tone, laugh at your jokes, and respond in a natural human voice — all in real time. No transcription step. No text-to-speech pipeline. The model processed audio natively and
Gpt Deep
ChatGPT's memory feature is OpenAI's attempt to solve the most common complaint about AI assistants — that they forget everything the moment you start a new conversation. The pitch is simple: ChatGPT learns about you over time. It remembers your name, your job, your preferences, your projects,
Gpt Deep
Canvas is OpenAI's side-panel editing interface — a space where you and GPT-4o work on a document or code file together, making targeted edits rather than regenerating entire responses. Anthropic has Artifacts. Google has the Gemini canvas. OpenAI has this. They all solve variations of the same problem — the
Gpt Deep
Function calling is the mechanism that turns GPT from a text generator into something that can do things. You describe functions — name, description, parameters as JSON Schema — and the model decides when to call them and with what arguments. It doesn't execute anything itself. It says "I&
Gpt Deep
OpenAI's Assistants API launched as the framework for building stateful, tool-using AI applications. Persistent threads, built-in file search, code interpreter, function calling — all managed server-side so you could "build agents without the plumbing." The pitch was compelling. The reality involves a lot of plumbing. Some of
Gpt Deep
Every article in this series covers what works. This one collects what doesn't. Not as a hit piece — GPT is a genuinely capable tool that millions of people use productively every day — but as an honest inventory of the limitations that OpenAI's marketing glosses over and
Gpt Deep
A Custom GPT is a system prompt, a set of uploaded files, and optionally some API connections — wrapped in a shareable link with a name and an icon. OpenAI launched them in late 2023 alongside the GPT Store, promising a marketplace where anyone could build and monetize AI-powered tools. The
Done With You
The first objection people raise against the done-with-you model is the ceiling. "It doesn't scale." They say this like it is a fatal flaw — as if a business that caps at $240K to $384K per year for a single operator with no employees, no overhead, and