AI Writing Tips Blog
Browse by topic →Practical guides and tools for writing with AI.
Posts
How AI Changes the Math on Per-Article Freelance Rates
If AI cuts production time by half, the per-hour rate on a fixed-price project doubles. What that means for pricing, what to do about it, and why not every client relationship survives the change.
Using AI Writing Tools Without a Subscription to All of Them
Most writers do not need every tool. How to pick one and get good at it rather than maintaining five subscriptions at different capability levels.
Batching vs. Linear Production: Which Workflow Fits Your Output
Writing ten articles one at a time is different from writing ten at once. How AI changes the math on both approaches and when each one makes sense for a solo content operation.
The Brief Is the System: Why Good Input Determines Everything
Most AI output problems start upstream of the prompt. What a brief needs to contain before you hand anything to a model, and why the writers getting good results are spending more time on setup.
ChatGPT vs. Gemini for Content Marketing: What Changes at Scale
For writers running high-volume operations, differences in output consistency and cost matter. A practical assessment from the content production side.
Claude vs. ChatGPT for Content Writing: A Practical Comparison
Not a features comparison. A working comparison based on actual content tasks: which handles long-form better, which holds tone more consistently, which produces output that needs less editing.
The Content Audit Workflow: Using AI to Refresh Old Posts
Updating existing content has better ROI than producing new content in most cases. How to build a workflow that uses AI to identify gaps, update, and republish without treating every refresh as a new article.
Building a Content Calendar You Can Actually Maintain Alone
For solo operators who own the whole content operation. How to plan a publishing schedule that accounts for AI-assisted production times, batching, and the weeks where nothing goes as planned.
Context Is the Prompt: How to Give AI What It Actually Needs
Generic inputs produce generic outputs. What context means in practice: the audience, the argument, the angle, the constraints, the register. How to supply it efficiently.
The Handoff Problem: Editing AI Drafts Without Starting Over
AI drafts that require a full rewrite are a failure mode, not a feature. How to structure the generation step so editing is revision, not reconstruction.