If I have to read one more project sign-off that says, “Looks good to me,” I think I’m going to lose my mind. In my 11 years as an instructional designer and QA lead, I’ve learned that “looks good” is usually code for “I skimmed it and I’m tired.”
When we’re dealing with high-stakes compliance training or critical safety protocols, we have the luxury (and necessity) of multi-round, exhaustive reviews. But what about the rest? The quick policy updates, the team-specific process walkthroughs, the “soft skill” refreshers? In an era where we’re using AI to spin up drafts in minutes, we need a new approach to quality assurance. We need minimum viable qa.
This isn’t about cutting corners; it’s about applying the right level of rigor to the right level of risk. Here is how I validate low risk training without losing my sanity or compromising on learning outcomes.
Defining the Boundary: What Actually Constitutes "Low Risk"?
Before you start your quick review, you have to be honest about the stakes. I categorize every piece of content before I open the storyboard. If a trainee gets this wrong, does it result in a lawsuit? A system outage? A PR disaster? If the answer is no, it’s low risk. If it’s just about reinforcing a new Slack etiquette or a minor update to an internal tool, we don't need a committee of five stakeholders debating the use of the Oxford comma.
My risk assessment table looks like this:
Training Type Risk Level Validation Strategy Compliance/Legal/Safety High Full SME review + Legal sign-off + Beta testing New Product Launch Medium Targeted SME review + Stakeholder sign-off Low Risk Training Low Self-QA + Spot check checklistThe AI-Assisted "Gotcha" Mindset
I’ve been piloting AI in my workflow for 18 months, and if there is documenting ai use in training one thing I’ve learned, it’s that AI is a confident liar. It will hallucinate a statistic with such professional tone that you might believe it—even when you know the data is proprietary. When I use AI to assist in drafting, my validation process shifts from “is this accurate?” to “where did this come from?”
My “gotchas” doc—a running list of every mistake I’ve caught in drafts—is now 80% AI-generated errors. Things like, “Employees must submit expenses by the 15th,” when the actual policy says the 10th. AI loves to generalize corporate policies. My job during validation is to hunt for those subtle, ambiguous, or just plain incorrect statements that creep into the text.
The Spot Check Checklist for Efficiency
When I’m doing a quick review, I don't read every word three times. I look for the “friction points” that break the learner experience. Here is the spot check checklist I use for low-risk content:
- The "So What" Test: Does the introduction explain why the learner should care in under two sentences? If not, rewrite. Ambiguity Filter: Pick one sentence at random. Can it be interpreted in two different ways? If yes, edit it. I will rewrite a sentence five times to remove any trace of vagueness. Assessment Logic: Can I break the quiz? I take the assessment as if I’m a learner who is bored, distracted, or actively trying to find the “gimme” answer. If I can guess the correct answer without reading the content, the assessment is invalid. Source Tracking: If a fact is stated, is there a link to the internal documentation or policy page? If the answer is “trust me,” it needs a source. Visual Load: Are the screenshots current? Nothing screams “I didn't care about this training” more than an outdated UI in a tutorial.
SME Review: Be Targeted, Don't Be a Nuisance
The fastest way to get “looks good to me” from a SME is to send them a 50-page document and ask them to “check it for accuracy.” That is a recipe for disaster because they won’t read it. They’ll just scan for their name.
Instead, use the minimum viable qa approach to SME reviews:
Highlight the "Danger Zones": Tell the SME, “I am confident in the structure, but I need you to specifically verify the numbers on slide 4 and the process flow on slide 7.” Use Comment-Only Mode: Give them the draft, but use a tool (like Google Docs or Articulate Review) that allows them to highlight specific text. If they can’t point to the error, it’s not an error. Limit the Review Window: Give them 48 hours. If they don’t provide feedback, the “default to launch” rule applies for low risk training (unless it’s a mission-critical error).The Human Element in AI-Assisted QA
Ultimately, your value as an L&D practitioner isn't just in making sure the facts are right—it's in making sure the tone is human. AI tends to sound like an overly formal corporate robot. It loves phrases like "It is imperative that employees utilize the following protocols."
My final pass in the quick review is always for "humanity." I read the content out loud. If I stumble over a sentence, it’s too complex. If it sounds like a LinkedIn thought-leadership post from 2012, it’s too jargon-heavy. I delete, simplify, and ensure the language is conversational.
Why "Minimum Viable QA" is a Strategic Choice
By moving to a risk-based model, you aren't just saving time—you’re increasing your capacity to handle more volume. If you spend 20 hours QA-ing a 5-minute training on how to book a conference room, you aren't being thorough; you’re being inefficient. You’re draining the resources you need for the high-impact projects that actually move the needle for your business.
The goal is to get to a place where your team trusts your validation process so much that when you say, “This is ready for launch,” they don’t feel the need to second-guess you. Stop the endless cycles of vague feedback. Start using your spot check checklist. Be the person who hunts for the ambiguity and kills it before it reaches the learner.
Final Thoughts for the Modern ID
We are the guardians of the learner's time. If we allow sloppy, overconfident, or vague training to reach the LMS, we are wasting that time. Use AI as a force multiplier for your writing, but keep the human brain fully engaged for the validation. And please, for the love of all things L&D, if you ever feel the urge to write “looks good to me,” stop. Take a breath. And find at least one thing—even a single, tiny, ambiguous sentence—that could be made better.
Your learners will thank you for it, even if they don’t know you did it.
