You're tired of AI. Not because you hate the technology — but because every time you try to use it, it creates more friction than it removes.
Another tool to evaluate. Another prompt that doesn't quite work. Another output you have to fix before it's usable. At some point, it starts to feel easier to just do the work yourself.
That feeling is real. But it's not an AI problem. It's a workflow problem.
Here's what's actually happening
Most L&D teams didn't integrate AI into their workflow. They dropped it on top of it.
Someone found a tool that looked useful. They started using it for one-off tasks. Other people on the team tried different tools. Now there are five tools, no shared prompts, inconsistent outputs, and no one is quite sure what's worth keeping.
That's not adoption. That's accumulation. And accumulation is exhausting.
The difference between teams that feel relief and teams that feel fatigue
Teams that get real value from AI aren't using more tools — they're using AI at specific, defined points in their workflow where it removes a real bottleneck. They've made a decision: this is where AI helps us, and this is how we use it.
That decision usually covers three things:
1. Which workflow stages get AI support Not everything. Usually 2–3 phases where the time cost is highest or the output is most repeatable — things like drafting learning objectives, building first-pass storyboards, or repurposing existing content.
2. What prompts the team actually uses Shared, tested prompts that produce consistent output. Not everyone experimenting individually. Not prompt roulette. A short library that works.
3. What quality standard the AI output needs to meet before it moves forward This is the one most teams skip. Without it, every AI output becomes a judgment call, which adds cognitive load instead of removing it.
When those three things are in place, AI stops feeling like a project and starts feeling like a tool — something you reach for without thinking about it.
The question worth asking your team this week
Are we exhausted because AI doesn't work — or because we never decided how to use it?
If it's the second one, the answer isn't more tools. It's a cleaner system.
🧠 Prompt of the Week
Use this when you need to audit where AI actually fits in your team's current process:
I'm an L&D professional working inside an organization.
Our team uses [ADDIE / SAM / agile — choose one] as our design framework.
Our most time-intensive phases are [list 2–3 phases or tasks].
Help me identify 3–5 specific places where AI could reduce time or effort
without sacrificing instructional quality. For each, suggest the type of
AI task (drafting, summarizing, generating options, etc.) and a simple
prompt approach to get started.
Run this with your actual workflow in mind. It takes 10 minutes and usually surfaces at least one thing worth trying immediately.
If you want a structured way to work through this — not just the prompt, but a full five-week plan for getting your AI workflow off the ground — that's exactly what the AiDDIE Reset is. It's free, it takes about 20 minutes a week, and it's designed for L&D professionals who want a real system, not more experimentation.
[Sign up at aiddie.co →]
— Gus
Most AI fatigue I see is fixable. It just takes a decision, not a new tool.