AI Is Useful For Writers - But Terrible At Writing Your Blog For You
If I read "In the era of" one more time, I'm closing the tab. Let's be honest: AI helps with text, but handing it the pen for your blog drains value fast. Readers don't need another tidy remix of the same training data. They need perspective, proof, and lived experience.
Where AI actually helps
Use it for summaries, meta descriptions, and alt text. These are functional, repeatable, and time-consuming - perfect for automation.
In fact, search engines often replace your meta text anyway, so generating options with AI is a smart time trade. Quality here has improved enough that it's the best tool for the job.
Why AI-written blogs fail readers
The job of a blog is to add value: updates, unique examples, better references, custom visuals, fresh angles. LLMs scrape the same internet and regurgitate a neat summary of it. Different models, same source material.
Paste AI paragraphs into your post and you're shipping consensus mush. The first person to do it might look original. The hundredth does not. At that point, readers are better off asking the bot directly - no ads, no fluff.
Why writers still hit "Generate"
- It's cheap: Ad-supported blogs are losing traffic to chatbots. Budgets shrink, output suffers, and AI becomes the stopgap to keep the lights on.
- Confidence: Many writers over-edit for "perfect" grammar and end up prompting more than writing. Imperfect human language is still clear - and often more engaging.
- Speed: Shipping an AI draft in minutes beats a blank page. But readers can now spot (and skip) filler. Raw AI output without editing feels disrespectful of their time.
A line in the sand for writers
AI can assist. It shouldn't replace you. Keep it on the factory floor, not the stage.
- Use AI for outlines, meta text, alt text, TL;DRs, and finding gaps or counterpoints.
- Write the core narrative yourself: the thesis, arguments, and transitions.
- Add something the model can't: personal data, field notes, opinions, screen captures, and custom visuals.
- Link to original sources and better references than the top three search results.
- Run a value audit: "If I stripped my name and brand, would this still be worth saving?" If not, rewrite.
Detection won't save us
Search platforms now reward helpful content regardless of how it's produced, which makes sense because reliable detection doesn't exist at scale. See Google's guidance on AI-generated content for context.
Google: Guidance about AI-generated content
OpenAI: AI text classifier had low accuracy
Unlike images, text has no dependable watermark. Simple edits break most detectors. That means the burden falls on us to protect the signal of human writing.
A simple, defensible workflow
- Define your thesis: One sentence. No hedging.
- Pressure test it: Ask AI for the strongest counterarguments and unanswered questions.
- Draft fast in your voice: Short paragraphs. Tight sentences. Kill filler.
- Layer proof: Data points, screenshots, quotes from primary sources, and your own examples.
- Automate the boring parts: Use AI for summary, meta description, alt text, and a checklist.
- Ship, then edit: Publish, gather feedback, improve. Treat posts like products.
Responsible ways to use AI (without handing it the pen)
- Outline exploration, headline options, FAQ generation, and research checklists.
- Meta descriptions, TL;DRs, alt text, and light grammar passes.
- Prompt libraries for consistent summaries and formatting - helpful for teams.
If you want to sharpen those assistive workflows (summaries, prompts, tool stacks) without turning your blog into paste, these resources help:
Final thought
Readers are flooded with generic content and have built-in filters now. Raw AI output feels like spam dressed up as help.
Use the machine for leverage, not as a ghostwriter. Keep your point of view front and center, and your work will stand out long after the templates blur together.
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