for the people who have to decide about it
Clear, hype-free guides to using AI in your work and business. What actually works, tested and explained in plain English.
Most engineering teams fail with AI coding agents because they treat setup as an individual problem. The teams winning in 2026 share one playbook — here it is.
An agent operating system only earns its keep once it touches your site and remembers what worked. Here are the two highest-ROI recipes — autonomous SEO publishing and a shared agent memory — with the exact APIs and steps.
AI automation fails 80% of the time. Here are 7 battle-tested lessons from real implementations that separate AI projects that save money from the ones that become expensive toys.
NotebookLM SEO research uses a 3-prompt workflow to find sources, extract content gaps, and build a ranking blueprint in minutes. Here's the full method with verified prompts and limits.
An agent operating system replaces five disconnected AI tabs with one persistent workspace that shares memory, swaps models, runs scheduled tasks, and works autonomously. Here is how to set one up.
ChatGPT Work turns ChatGPT from chatbot into agent. It can write code, browse the web, call 1,400+ plugins, run scheduled tasks, and work autonomously for hours. Here is what is real, what it costs, and how to set it up.
The Tech Archive covers artificial intelligence for people who have to make decisions about it. Every piece starts from something checkable: a model release and what changed in it, a tool and what it costs to run, a research result and what it does and does not show. We write about model releases, AI agents, developer tooling, research, funding, and policy, and we link to the primary source so you can disagree with our reading of it.
What you will not find is a launch rewritten from a press release, a benchmark quoted without its conditions, or a prediction dressed up as a finding. When something is genuinely unclear we say so and explain what evidence would settle it. That is slower than the news cycle and it is the point.
Practical automation for teams without an engineering department: what to adopt, what it actually costs once you run it every day, and which tasks are still cheaper to do by hand. Read the small business guides.
How generative tools change research, drafting, and measurement, and where they quietly produce work that reads fine and says nothing. Read the marketing guides.
Agent frameworks, model APIs, and local inference, tested on real work rather than demos, with the failure modes written down beside the setup instructions. Read the developer guides.
New articles publish several times a week. You can follow along by RSS, browse everything in the full article archive, or start from a topic.
