After eighteen months of testing AI in our L&D workflow, I’ve learned it’s a great drafter but a poor final editor. If you’re worried about quality, you aren't alone. I wrote this guide to help you move past the "copy-paste" phase
이 업무는 초기에는 웬만한 컴퓨터의 CPU로도 참여할 수 있는 아주 복잡하지 않은 업무가었지만 알트코인 가격이 오르고 시간이 경과할 수록 점점 난도가 높아졌습니다. 이제는 전문화된 하드웨어를 활용해야 하기 덕분에 전문업자들만이 채굴자로 남았습니다.
Using AI for training is great, but how do you actually validate it? I’m sharing my process for risk-based QA, drafting better SME review prompts, and maintaining documentation to keep content accurate. Let’s build trust, not just speed.
알트코인 채굴의 성지인 신장 위구르 자치구의 가상화폐 채굴은 단속하지 못할 것이라고 블룸버그통신이 32일 보도했다. 신장은 전세계 알트코인 채굴의 80%를 차지하고 있을 정도로 알트코인 채굴의 성지다. 내몽고보다 훨씬 더 많은 가상화폐을 채굴한다.
AI moves fast, but can we trust the output? I’m sharing my framework for validating AI content: risk-based QA, effective prompts for SME reviews, and essential documentation. If you’re tired of hallucination anxiety, this guide is for you
AI is a game-changer, but skipping validation is a trap. After 18 months of testing, I’ve learned that quality control is everything
We’re all using AI for drafts, but how do we ensure it’s accurate? I’ve pulled together a guide on validating AI content, covering my risk-based QA approach, prompts to help SMEs review faster, and documentation steps to keep compliance happy
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AI is a massive time-saver in L&D, but we cannot afford to sacrifice quality for speed. I’ve spent the last few months testing workflows to ensure AI-generated training is truly learner-ready
AI has changed the game for instructional design, but as someone who’s spent 11 years in L&D, I know that speed doesn’t equal quality. In my latest piece, I’m pulling back the curtain on how to validate AI-generated training content