Claude Code Puts Tech Workers on Notice — from builtin.com by Matthew Urwin
Anthropic is flexing its new and improved Claude Code, which used vibe coding to build the company’s latest tool, Cowork. The feat has inspired both excitement and angst within the tech world as the future of work continues to grow more uncertain.

Summary:
Anthropic is becoming the leader in enterprise artificial intelligence, thanks to upgrades made to Claude Code. The coding tool practically built Anthropic’s Cowork product — sparking both excitement around the possibilities of vibe coding and fears around the job outlook of tech workers.

 

The Campus AI Crisis — by Jeffrey Selingo; via Ryan Craig
Young graduates can’t find jobs. Colleges know they have to do something. But what?

Only now are colleges realizing that the implications of AI are much greater and are already outrunning their institutional ability to respond. As schools struggle to update their curricula and classroom policies, they also confront a deeper problem: the suddenly enormous gap between what they say a degree is for and what the labor market now demands. In that mismatch, students are left to absorb the risk. Alina McMahon and millions of other Gen-Zers like her are caught in a muddled in-between moment: colleges only just beginning to think about how to adapt and redefine their mission in the post-AI world, and a job market that’s changing much, much faster.

“Colleges and universities face an existential issue before them,” said Ryan Craig, author of Apprentice Nation and managing director of a firm that invests in new educational models. “They need to figure out how to integrate relevant, in-field, and hopefully paid work experience for every student, and hopefully multiple experiences before they graduate.”

 

Amid AI and Labor Market Changes, Companies Look to Grow Their Own Skilled Workers — from workshift.org by Colleen Connolly

The explosion of artificial intelligence, combined with slowing growth in the labor force, has many companies reconsidering how they hire and develop workers. Where they once relied on colleges and universities for training, a growing number of companies are now looking in-house.

Investment in developing employees and would-be hires is becoming a key differentiator for companies, according to a new report from the Learning Society, a collaborative effort led out of the Stanford Center on Longevity. And that’s true even as AI adoption grows.

The Big Idea: The report authors interviewed 15 human resources executives from major firms, which ranged in size from Hubbell, an electric and utility product manufacturer with about 17K employees, to Walmart with more than 2M employees. The authors asked about four topics: the impact of AI and technology on work, skill building and talent development, supporting workers over longer working lives, and new partnerships between businesses and higher education.

 

Jim VandeHei’s note to his kids: Blunt AI talk — from axios.com by CEO Jim VandeHei
Axios CEO Jim VandeHei wrote this note to his wife, Autumn, and their three kids. She suggested sharing it more broadly since so many families are wrestling with how to think and talk about AI. So here it is …

Dear Family:
I want to put to words what I’m hearing, seeing, thinking and writing about AI.

  • Simply put, I’m now certain it will upend your work and life in ways more profound than the internet or possibly electricity. This will hit in months, not years.
  • The changes will be fast, wide, radical, disorienting and scary. No one will avoid its reach.

I’m not trying to frighten you. And I know your opinions range from wonderment to worry. That’s natural and OK. Our species isn’t wired for change of this speed or scale.

  • My conversations with the CEOs and builders of these LLMs, as well as my own deep experimentation with AI, have shaken and stirred me in ways I never imagined.

All of you must figure out how to master AI for any specific job or internship you hold or take. You’d be jeopardizing your future careers by not figuring out how to use AI to amplify and improve your work. You’d be wise to replace social media scrolling with LLM testing.

Be the very best at using AI for your gig.

more here.


Also see:


Also relevant/see:

 

FutureFit AI — helping build reskilling, demand-driven, employment, sector-based, and future-fit pathways, powered by AI
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The above item was from Paul Fain’s recent posting, which includes the following excerpt:

The platform is powered by FutureFit AI, which is contributing the skills-matching infrastructure and navigation layer. Jobseekers get personalized recommendations for best-fit job roles as well as education and training options—including internships—that can help them break into specific careers. The project also includes a focus on providing support students need to complete their training, including scholarships and help with childcare and transportation.

 

The Learning and Employment Records (LER) Report for 2026: Building the infrastructure between learning and work — from smartresume.com; with thanks to Paul Fain for this resource

Executive Summary (excerpt)

This report documents a clear transition now underway: LERs are moving from small experiments to systems people and organizations expect to rely on. Adoption remains early and uneven, but the forces reshaping the ecosystem are no longer speculative. Federal policy signals, state planning cycles, standards maturation, and employer behavior are aligning in ways that suggest 2026 will mark a shift from exploration to execution.

Across interviews with federal leaders, state CIOs, standards bodies, and ecosystem builders, a consistent theme emerged: the traditional model—where institutions control learning and employment records—no longer fits how people move through education and work. In its place, a new model is being actively designed—one in which individuals hold portable, verifiable records that systems can trust without centralizing control.

Most states are not yet operating this way. But planning timelines, RFP language, and federal signals indicate that many will begin building toward this model in early 2026.

As the ecosystem matures, another insight becomes unavoidable: records alone are not enough. Value emerges only when trusted records can be interpreted through shared skill languages, reused across contexts, and embedded into the systems and marketplaces where decisions are made.

Learning and Employment Records are not a product category. They are a data layer—one that reshapes how learning, work, and opportunity connect over time.

This report is written for anyone seeking to understand how LERs are beginning to move from concept to practice. Whether readers are new to the space or actively exploring implementation, the report focuses on observable signals, emerging patterns, and the practical conditions required to move from experimentation toward durable infrastructure.

 

“The building blocks for a global, interoperable skills ecosystem are already in place. As education and workforce alignment accelerates, the path toward trusted, machine-readable credentials is clear. The next phase depends on credentials that carry value across institutions, industries, states, and borders; credentials that move with learners wherever their education and careers take them. The question now isn’t whether to act, but how quickly we move.”

– Curtiss Barnes, Chief Executive Officer, 1EdTech

 


The above item was from Paul Fain’s recent posting, which includes the following excerpt:

SmartResume just published a guide for making sense of this rapidly expanding landscape. The LER Ecosystem Report was produced in partnership with AACRAO, Credential Engine, 1EdTech, HR Open Standards, and the U.S. Chamber of Commerce Foundation. It was based on interviews and feedback gathered over three years from 100+ leaders across education, workforce, government, standards bodies, and tech providers.

The tools are available now to create the sort of interoperable ecosystem that can make talent marketplaces a reality, the report argues. Meanwhile, federal policy moves and bipartisan attention to LERs are accelerating action at the state level.

“For state leaders, this creates a practical inflection point,” says the report. “LERs are shifting from an innovation discussion to an infrastructure planning conversation.”

 
 
 

Global list of over 100 L&D conferences in 2026 — from donaldhtaylor.co.uk by Don Taylor

I’m a firm believer in conferences. This isn’t just because I have chaired the Learning Technologies Conference in London since 2000. It’s because they are invaluable in sustaining our community. So many in Learning and Development work alone or in small teams, that building and maintaining personal contacts is crucial.For a number of years, I have kept a personal list of the Learning and Development conferences running internationally. This year, I thought it would be helpful to  share it.

 

 
 

What’s Happening to Jobs for New Grads — from linkedin.com by Jeff Selingo

No matter where you go to college, the job market math for new graduates is grim right now, as I write in a new article out yesterday in New York magazine.

There were 15% fewer entry-level and internship job postings in 2025 than the year before, according to Handshake, a job-search platform popular with college students; meanwhile, applications per posting rose 26%.

How much AI is to blame for the fragile entry-level job market is unclear. Several research studies show AI is hitting young college-educated workers disproportionately, but broader economic forces are part of the story, too.

As Christine Y. Cruzvergara, Handshake’s chief education strategy officer, told me, AI isn’t “taking” jobs so much as employers are “choosing” to replace parts of jobs with automation rather than redesign roles around workers. “They’re replacing people instead of enabling their workforce,” she said.

Today’s graduates are stuck in an in-between moment. Many started college before AI mattered and graduated into a labor market reshaped almost overnight, where entry-level roles are disappearing faster than students can adapt.

 
 

AI Is Quietly Rewiring the ADDIE Model (In a Good Way) — from drphilippahardman.substack.com by Dr. Philippa Hardman
The traditional ADDIE workflow isn’t dead, but it is evolving

The real story isn’t what AI can produce — it’s how it changes the decisions we make at every stage of instructional design.

After working with thousands of instructional designers on my bootcamp, I’ve learned something counterintuitive: the best teams aren’t the ones with the fanciest AI tools — they’re the ones who know when to use which mode—and when to use none at all.

Once you recognise that, you start to see instructional design differently — not as a linear process, but as a series of decision loops where AI plays distinct roles.

In this post, I show you the 3 modes of AI that actually matter in instructional design — and map them across every phase of ADDIE so you know exactly when to let AI run, and when to slow down and think.


Also see:

Generative AI for Course Design: Writing Effective Prompts for Multiple Choice Question Development — from onlineteaching.umich.edu by Hedieh Najafi

In higher education, developing strong multiple-choice questions can be a time-intensive part of the course design process. Developing such items requires subject-matter expertise and assessment literacy, and for faculty and designers who are creating and producing online courses, it can be difficult to find the capacity to craft quality multiple-choice questions.

At the University of Michigan Center for Academic Innovation, learning experience designers are using generative artificial intelligence to streamline the multiple-choice question development process and help ameliorate this issue. In this article, I summarize one of our projects that explored effective prompting strategies to develop multiple-choice questions with ChatGPT for our open course portfolio. We examined how structured prompting can improve the quality of AI-generated assessments, producing relevant comprehension and recall items and options that include plausible distractors.

Achieving this goal enables us to develop several ungraded practice opportunities, preparing learners for their graded assessments while also freeing up more time for course instructors and designers.

 

Which AI Video Tool Is Most Powerful for L&D Teams? — from by Dr. Philippa Hardman
Evaluating four popular AI video generation platforms through a learning-science lens

Happy new year! One of the biggest L&D stories of 2025 was the rise to fame among L&D teams of AI video generator tools. As we head into 2026, platforms like Colossyan, Synthesia, HeyGen, and NotebookLM’s video creation feature are firmly embedded in most L&D tech stacks. These tools promise rapid production and multi-language output at significantly reduced costs —and they deliver on a lot of that.

But something has been playing on my mind: we rarely evaluate these tools on what matters most for learning design—whether they enable us to build instructional content that actually enables learning.

So, I spent some time over the holiday digging into this question: do the AI video tools we use most in L&D create content that supports substantive learning?

To answer it, I took two decades of learning science research and translated it into a scoring rubric. Then I scored the four most popular AI video generation platforms among L&D professionals against the rubric.
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For an AI-based tool or two — as they regard higher ed — see:

5 new tools worth trying — from wondertools.substack.com by Jeremy Kaplan

YouTube to NotebookLM: Import a Whole Playlist or Channel in One Click
YouTube to NotebookLM is a remarkably useful new Chrome extension that lets you bulk-add any YouTube playlists, channels, or search results into NotebookLM. for AI-powered analysis.

What to try

  • Find or create YouTube playlists on topics of interest. Then use this extension to ingest those playlists into NotebookLM. The videos are automatically indexed, and within minutes you can create reports, slides, and infographics to enhance your learning.
  • Summarize a playlist or channel with an audio or video overview. Or create quizzes, flash cards, data tables, or mind maps to explore a batch of YouTube videos. Or have a chat in NotebookLM with your favorite video channel. Check my recent post for some YouTube channels to try.
 

What AI-Generated Voice Technology Means For Creators And Brands — from bitrebels.com by Ryan Mitchell

Voice has become one of the most influential elements in how digital content is experienced. From podcasts and videos to apps, ads, and interactive platforms, spoken audio shapes how messages are understood and remembered. In recent years, the rise of the ai voice generator has changed how creators and brands approach audio production, lowering barriers while expanding creative possibilities.

Rather than relying exclusively on traditional voice recording, many teams now use AI-generated voices as part of their content and brand strategies. This shift is not simply about efficiency; it reflects broader changes in how digital experiences are produced, scaled, and personalised.

The Future Role Of AI-Generated Voice
As AI voice technology continues to improve, its role in creative and brand workflows will likely expand. Future developments may include more adaptive voices that respond to context, audience behaviour, or emotional cues in real time. Rather than replacing traditional voice work, AI-generated voice is becoming another option in a broader creative toolkit, one that offers speed, flexibility, and accessibility.

 
© 2025 | Daniel Christian