Avoiding “Content Debt”: How to Harness LLMs Without Derailing Your Web3 Project

The Promise and Peril of LLMs

LLMs like ChatGPT and the recently open-sourced DeepSeek AI are incredible tools. When used correctly, they can more than double your productivity in numerous fields—content creation chief among them. However, when used incorrectly, they can be an absolute nightmare.

We’ve all seen the infamous case of that one lawyer who submitted entirely AI-generated citations for cases that never even existed. Oof.

Beware the Hidden Cost: Content Debt

Here at Crypto Copy Pros, we specialize in writing content for Web3 projects. Many of these projects are led by brilliant developers who are too bogged down with actual development to handle the core documentation and communication work. That’s where we come in.

But increasingly often these days, the draft documents we receive are just plain nonsense—complete with hallucinated features and nonexistent technologies. As it would seem, rogue team members from all over the Web3 space have found themselves buckling under the pressure of an overwhelming content schedule, and chosen to employ an LLM to talk about key project announcements, milestones, and launches on their behalves.

While LLMs excel at writing about topics within their training data, they’re obviously terrible at describing your proprietary technology solution if it doesn’t exist in that data… who whould’ve thought? 🙂

If you want precision, credibility, and to ensure your readers are gaining a deep understanding of your product’s unique value, you still need real human expertise. LLMs can power your productivity, but they should always be driven by someone who understands your project’s innermost workings and overall strategy. That’s the only way to keep your documentation grounded in reality.

Otherwise… well. Have you ever heard of “technical debt?” It’s the hidden cost developers incur when they rely on shortcuts and quick fixes—eventually demanding more time and resources to fix or rebuild. The same concept applies to marketing: “content debt.” When your team leans too heavily on AI, messy messaging and misinformation can pile up.

Don’t let your team end up with content debt. Sifting through AI hallucinations to find the truth can be more time-consuming than crafting accurate content from the start—wiping out any initial savings in time or money. Trust us, we’ve been there…

How to Un-F*ck Your Content After It’s Been Fed Through the LLM Meat Grinder

Sometimes you can’t spot the damage until you’re halfway through reading an AI-generated draft that drifts into gibberish. Don’t panic—content can be rescued. Here’s a quick guide to pull your piece out of AI hell and restore authenticity.

  1. Reconnect With Your Core Team
    • Talk to Technical Leads/Project Owners: Real humans with deep knowledge of your project are the best source of truth. Gather them to clarify the article’s overarching goal and key talking points.
    • Re-Align on Objectives: Make sure everyone is crystal clear on what the content is supposed to convey, who it’s for, and why it matters.
  2. Dig Up the Earliest Drafts
    • Go Back to the Roots: If there’s a version before the AI took over, return to it. Original outlines, bullet points, and human-written notes can help re-establish the piece’s intended meaning.
    • Extract Human Insights: Look for any context or key phrases that AI might have distorted. This is your guiding light for accuracy.
  3. Re-Validate Every Claim
    • Fact-Check and Verify: Take a magnifying glass to each “fact” in the AI-generated copy. If something seems off—or too good to be true—it probably is.
    • Link Back to Real Sources: Whenever possible, tie statements to actual documentation, code repositories, or known references. If you can’t find a credible source, the claim likely needs to be cut.
  4. Scrub Away Hallucinations
    • Compare AI Content with Reality: LLMs are notorious for making up features and technologies. Cross-check anything that looks suspicious or overhyped.
    • Use Official Docs as Your Compass: If the AI is referencing technology that your project doesn’t actually have, delete or correct it ASAP.
  5. Engage a Subject-Matter Editor
    • Human Expertise is Key: Enlist someone deeply familiar with your product’s internals—or a professional editor who can quickly spot nuances that AI misses.
    • Double Down on Authenticity: This editor should ensure the tone, structure, and facts all align with your brand’s identity and the project’s reality.
  6. Iterate with Purpose (Not Blindly)
    • Use LLMs Strategically: If you want to leverage AI for final polishing, do so under watchful human supervision. Provide it with bullet points, style guides, or outlines to keep it on track.
    • Review in Rounds: Have your team read through the revised content at least twice. Each pass might reveal new errors or misleading points.
  7. Establish a Future-Proof Workflow
    • Version Control: Keep track of all drafts—human and AI-generated. This helps you pinpoint exactly where things went sideways.
    • Clear Guidelines: If AI is going to be part of the process, set firm rules on how and when it’s used, and who is ultimately responsible for fact-checking.
  8. Don’t Skimp on a Final Read-Through
    • One Last Sanity Check: Before hitting publish, make sure the content is cohesive, consistent, and undeniably yours.
    • Spot-Check Special Sections: Headlines, captions, charts, code samples—these are often prime spots for AI mix-ups.

By combining the speed of an LLM with the discernment of real human expertise, you can salvage your content without sacrificing accuracy or credibility. In other words, you’ll un-f*ck your copy, maintain trust with your audience, and avoid the dreaded “content debt” that comes from letting AI run amok.

When used judiciously, LLMs can be a powerful ally—especially in the fast-paced world of Web3. Yet without real human oversight and knowledge, you risk creating content debt instead of content gold. Invest in credible expertise up front, and you’ll not only save yourself headaches but also maintain a consistent, trustworthy narrative for your project.



Author: Joshua Clow
Chief Copywriter at CCP, Josh is a 10+ year blockchain veteran and experienced technical copywriter with a track record of crafting high-quality content for top Web3 service providers.