The AI Honeymoon is Over: Why Plain Language is Your New Best Friend in L&D

2026-06-24T01:50:56Z

Eric-hill87: Created page with "<html><p> I’ve been in this industry for eleven years—long enough to remember when “AI” meant a clunky, rule-based branching scenario that took three weeks to script. Now, I can generate a 10-module curriculum before my morning coffee. But here is the hard truth I’ve learned after eighteen months of piloting these tools: <strong> AI generates content at the speed of thought, but it validates at the speed of zero.</strong></p><p> <img src="https://images.pexels..."

<html><p> I’ve been in this industry for eleven years—long enough to remember when “AI” meant a clunky, rule-based branching scenario that took three weeks to script. Now, I can generate a 10-module curriculum before my morning coffee. But here is the hard truth I’ve learned after eighteen months of piloting these tools: <strong> AI generates content at the speed of thought, but it validates at the speed of zero.</strong></p><p> <img src="https://images.pexels.com/photos/7279120/pexels-photo-7279120.jpeg?auto=compress&cs=tinysrgb&h=650&w=940" style="max-width:500px;height:auto;" ></img></p> <p> If you aren't applying rigorous plain language checks and a risk-based QA framework to your AI-assisted work, you aren’t an instructional designer; you’re a glorified copy-paste operator. As someone who keeps a running "gotchas" doc—a graveyard of the most embarrassing hallucinations and corporate jargon bloopers I’ve found in AI drafts—I’m here to tell you how to stop trusting the machine and start doing the real work of enablement.</p><p> <iframe src="https://www.youtube.com/embed/RvxtcGC75Oc" width="560" height="315" style="border: none;" allowfullscreen="" ></iframe></p> <h2> What Validation Actually Means in an AI-Assisted Workflow</h2> <p> Validation in L&D isn't just about spotting typos. It’s about verifying that the content is accurate, instructionally sound, and—most importantly—understandable to the person at the end of the screen. AI models are trained on the internet, and the internet is 40% corporate buzzwords and 60% nonsense. When you ask an AI to write training, it defaults to the "Corporate Voice," which is usually <a href="https://www.reddit.com/r/LearningDevelopment/comments/1u9m41z/has_anyone_changed_how_they_validate_aigenerated/">human in the loop l&d</a> verbose, passive, and deeply confusing.</p><p> <img src="https://images.pexels.com/photos/31092685/pexels-photo-31092685.jpeg?auto=compress&cs=tinysrgb&h=650&w=940" style="max-width:500px;height:auto;" ></img></p> <p> Validation is the process of stripping that veneer away. It means taking an AI-generated draft and putting it through a <strong> plain language training</strong> filter. If you can’t explain the concept to a new hire in one sentence without using an acronym, your training isn't ready. Period.</p> <h2> Risk-Based QA: Why Not Everything Deserves Your Deep Dive</h2> <p> One of the biggest mistakes I see junior IDs make is treating a "How to Reset Your Password" quick-guide with the same scrutiny as a "Compliance Procedures for SEC Reporting" course. That’s a recipe for burnout. You need a risk-based approach to your QA.</p> <p> I categorize my content into three tiers, each requiring a different level of validation:</p> Risk Level Content Type Validation Strategy AI Dependency <strong> Low</strong> Quick-tips, FAQs, meeting refreshers Peer review, readability scores High (AI draft + 5-min polish) <strong> Medium</strong> Process workflows, standard operating procedures SME spot-check, logic verification Moderate (AI draft + structure review) <strong> High</strong> Compliance, safety, product launches SME deep-dive, legal review, stress-test Low (AI for brainstorming/outlining only) <p> For high-stakes content, I never trust an AI to write the final copy. I use it to draft the structure, then I rebuild the content using my own human expertise to ensure accuracy. If the AI hallucinates a process step, it’s not a “typo”—it’s a liability.</p> <h2> Fact-Checking and the "Gotchas" Doc</h2> <p> I mentioned my "gotchas" doc earlier. It is the most valuable tool in my workflow. Every time an AI makes a false claim about a software feature or misinterprets a policy, I write it down. This creates a mental map of where the model tends to hallucinate. For example, I know that if I ask an LLM about our internal LMS permissions, it will almost always guess based on general industry standards rather than our specific, weirdly configured security roles.</p> <h3> The Source-Tracking Habit</h3> <ul> <li> <strong> Verify the premise:</strong> Before reading the AI content, look at the source documents. If the AI contradicts them, flag it immediately.</li> <li> <strong> The "Reverse Trace":</strong> Take a bold claim from your AI draft and ask, "Where does this come from?" If the AI gives you a generic answer or a dead link, it’s hallucinating.</li> <li> <strong> Hard Facts Only:</strong> AI is great at tone and flow; it is terrible at nuanced data. Never let it generate statistics without manual validation against your source of truth.</li> </ul> <h2> SME Review: Stop Wasting Their Time</h2> <p> We’ve all been there: You send a 40-page Word doc to a Subject Matter Expert (SME), and they reply with, "Looks good to me." That feedback is useless. It’s lazy, and it’s dangerous.</p> <p> When using AI-assisted content, your SME review needs to be <strong> targeted and efficient.</strong> Don't ask them to "review this module." Instead, use your editing checklist to create a surgical request:</p> <ol> <li> <strong> The "Red Flag" list:</strong> List the three areas where you felt unsure of the AI’s logic. Ask the SME, "Is this process step correctly prioritized?"</li> <li> <strong> Plain language validation:</strong> Ask the SME, "If a new hire read this, would they understand what to do immediately, or would they have to ask a follow-up question?"</li> <li> <strong> Assessment stress-testing:</strong> I personally try to break every assessment the AI generates. I look for questions where the distractors are too obvious or where the "correct" answer could be argued by a clever learner. I then ask the SME to confirm my "broken" logic.</li> </ol> <h2> The Editing Checklist for Learner-Friendly Writing</h2> <p> Before any content goes live, it must pass these <strong> readability checks</strong>. If it doesn't pass, I rewrite it—usually five times—until it is clean, punchy, and human.</p> <ul> <li> <strong> The "So What?" Test:</strong> Does every paragraph tell the learner why this information matters to their job? If not, delete it.</li> <li> <strong> Passive Voice Purge:</strong> Search for "was/were/by" constructions. Rewrite them into active voice. "The button should be clicked by the user" becomes "Click the button."</li> <li> <strong> Word Complexity Check:</strong> Use tools like Hemingway or readable.io to check the reading grade level. For most corporate training, aim for a 6th to 8th-grade level. No one reads at a university level when they're trying to learn a software task.</li> <li> <strong> Visual Breaks:</strong> Are there massive walls of text? Break them up with bullets, tables, or call-outs. AI loves to write essays; learners love to scan.</li> </ul> <h2> The Takeaway: Don't Be a Bot-Facilitator</h2> <p> AI is a tool, not a colleague. It doesn’t understand your company culture, it doesn’t care about your learners, and it certainly doesn't know when it's lying to you. My role as an instructional designer hasn't disappeared; it has shifted. I am now less of a "content creator" and more of an "editor-in-chief and quality assurance lead."</p> <p> The next time you see a "looks good" from a stakeholder, don't take it as a win. Dig deeper. Ask questions that force engagement. Test your assessments until you find the flaws that will frustrate your learners. Write in plain language, keep your "gotchas" doc updated, and remember: <strong> AI generates the words, but you are responsible for the learning.</strong> Don't outsource your integrity.</p></html>

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The AI Honeymoon is Over: Why Plain Language is Your New Best Friend in L&D