LinkedIn Grad’s Guide 2026: Starting your career in the AI era — from linkedin.com by Gianna Prudente
To help you head off in the right direction, we’ve identified where those starting their careers are finding opportunity, based on data from millions of LinkedIn member profiles.

While all of this is happening, colleges are still catching up. Many students are graduating without having spent much time learning how AI actually fits into day-to-day work — even as employers seek out those exact skills.

“Colleges are moving into an era of, we’ll let the faculty decide, which leads to a very uneven experience for students because some faculty are really into AI and other faculty are not,” says Jeff Selingo, a higher education strategist. “Employers are the same; they don’t really know how to act around early careers.”

Taken together, new grads are entering a uniquely challenging environment: fewer traditional entry points, slower turnover and a workplace that’s evolving faster than the systems preparing people for it.

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I knew my writing students were using AI. Their confessions led to a powerful teaching moment — from theguardian.com by Micah Nathan
The problem wasn’t just the perfectly polished, yet mediocre prose. It’s what’s lost when we surrender the struggle to translate thought into words

For a few moments, all was quiet except the classroom’s ticking radiators. Then, a teary-eyed confession: one of the ostensible authors said she only used AI because she was scared of looking stupid, of being criticized for bad writing. She said she loved writing stories and hated having used AI. But she couldn’t stop herself, recounting a sequence similar to an addict’s descent: at first she fed her story into AI for a grammar check, it suggested line edits and she accepted, then it asked if she wanted structural edits, then it offered to rewrite the entire piece.

The other would-be author admitted he had never written a short story before and he had an idea but didn’t know where to start. I asked him why he didn’t reach out to me for help. He shrugged.

One of the other students raised her hand, saying she didn’t understand why it was bad for AI to write stories as long as the stories are based on their ideas. More students spoke: one wanted to know how using AI was any different from using a human editor. Another wanted me to answer why, at a university that launched one of the world’s first AI research programs in 1959, were we even having this debate? Isn’t AI meant to make everyone’s life easier? Less stressful? Isn’t the point of AI to free humans from the tedium of rote tasks?

The conversation that followed their confessions was one of the most productive teaching moments of my eight years at MIT. Writing, I told them, isn’t supposed to be easy, and of course it can be tedious but that doesn’t make it rote. Writing isn’t just the production of sentences – it’s the training of endurance by way of sustained attention. It’s a way of learning what one thinks by attempting to say it. 


This $10K AI School Promises to Future-Proof Your Career — from builtin.com by Matthew Urwin
Khan Academy, TED and ETS are starting a new program to equip students and professionals with the skills to thrive in an increasingly AI-driven economy. Here’s what you need to know.

Summary: The Khan TED Institute is a higher-education program that will teach students and workers how to use AI through interactive learning. The program’s AI-centric curriculum is an unproven approach, though, casting doubt on whether it will actually improve learning outcomes and career prospects.


 

Want Students to Build a Healthier Relationship With Technology? Start With The Arts — from techlearning.com by Adrianna Marshall
Arts classrooms demonstrate what technology integration at its best can look like

But at a moment defined by rapid AI adoption and ongoing debates about screen time, the argument for protecting and investing in arts education needs to take on a new tone. The arts continue to be one of the most effective places in school for students to build healthier, more intentional relationships with technology.

In short, in the age of AI, we need the arts more than ever.

Digital composition software, notation tools, and recording platforms allow students to experiment, revise, and refine their ideas in ways that would have been far more time-consuming a decade ago. Students can layer tracks, hear immediate playback, annotate their own scores, and collaborate across devices. The same is true in other contexts besides music; in visual arts, for instance, a variety of digital drawing and painting platforms enable students to practice with new mediums, styles, and techniques without having to worry about supplies or messes. But in either case, the core intellectual work of looking and listening critically, understanding structure, and making aesthetic choices remains entirely human and part of the learning.


From DSC:
I agree. At one of my previous positions, I spent 10 years supervising a digital studio — helping professors and students use a variety of applications to create things. The applications were from Adobe, Apple, and a variety of smaller vendors. The deliverables could be graphics, edited soundtracks, music, videos, flyers, posters, collages, edited photographs, presentations, websites, and more. I longed for people to discover the power of multimedia to communicate their messages, tell stories, stir emotion, powerfully engage themselves (and others), and unleash their creativity.

There were several obstacles to our digital studio being more impactful at that institution. It was under the IT department, not the academic side of the house. It was in the basement of the library, where few students and faculty traveled. During those years, it was highly uncommon for faculty members to require multimedia-based assignments — so many students had to WANT to develop these skills on their own time. The majority of students didn’t see the value in developing the types of digital skills that we were trying to build…or they didn’t have the time.


Also relevant/see:


 

This $10K AI School Promises to Future-Proof Your Career — from builtin.com by Matthew Urwin
Khan Academy, TED and ETS are starting a new program to equip students and professionals with the skills to thrive in an increasingly AI-driven economy. Here’s what you need to know.

Summary: The Khan TED Institute is a higher-education program that will teach students and workers how to use AI through interactive learning. The program’s AI-centric curriculum is an unproven approach, though, casting doubt on whether it will actually improve learning outcomes and career prospects.

Higher education might be on the verge of a radical overhaul to bring it up to speed in the age of artificial intelligence. At the TED2026 conference, Khan Academy, TED and ETS announced that they’re partnering to establish the Khan TED Institute — a new program that reorients the college curriculum around AI. By joining forces, the education technology trio aims to develop an alternative to traditional universities that better tracks student progress, teaches more relevant skills and provides a more personalized learning experience.

Accessibility is another major tenet of the Khan TED Institute. Its virtual nature allows anyone with an internet connection to participate in the program and makes it easier for students to move at their preferred pace. And because its curriculum prioritizes competency over course credits, advanced learners can complete the program in a shorter period. Time isn’t the only thing students can save on, either: The Institute promises a bachelor’s degree for less than $10,000, offering a much more affordable alternative to the typical four-year degree. 


 

From DSC:
Faculty senates don’t do well with this pace of change. But to their credit, few organizations can begin to deal with this pace of change.

 

When anyone can build a course, the real job is deciding which ones shouldn’t exist — from drphilippahardman.substack.com by Dr. Philippa Hardman
Why deciding is the only L&D skill AI can’t replace.

The biggest AI risk that L&D faces isn’t that it gets left behind: it’s that we build more — and flood the organisation with meh-quality content nobody needed in the first place.

In this post, I’ll make the case that:

  • The L&D job has just split in two — and most of us are still working on the wrong half.
  • There’s a new operating model coming for the role, and it’s already running inside a lot of the companies you’ve heard of.
  • The smartest critique of everything I’m about to argue comes from Ethan Mollick — and I think he’s half right.

The question we’ve been asking for the last two years — “how do I get faster at building?” — was the wrong one.

The real question is: can I look at fifteen AI-generated learning assets and decide which three are worth scaling — and put my name to that decision?

 

Make learning accessible to all in higher education — from The Times Higher Education

When accessibility is placed at the heart of teaching and learning, rather than treated as a bolt-on, every student benefits. This week’s spotlight guide offers advice on designing universally accessible learning, in-person and online. Find out how to ease the burden of disability disclosure with universal design for learning, better support neurodivergent students and students with hearing or vision issues, design more accessible assessments and ensure digital tools work for all.

 

 
 

Here is Chris Martin’s posting on LinkedIn.com:


Here is Dominik Mate Kovacs’ posting on LinkedIn.com:


The AI ‘hivemind’: Why so many student essays sound alike — from hechingerreport.org by Jill Barshay
A study of more than 70 large language models found similar answers to brainstorming and creative writing prompts

The answers were frequently indistinguishable across different models by different companies that have different architectures and use different training data. The metaphors, imagery, word choices, sentence structures — even punctuation — often converged. Jiang’s team called this phenomenon “inter-model homogeneity” and quantified the overlaps and similarities. To drive the point home, Jiang titled her paper, the “Artificial Hivemind.” The study won a best paper award at the annual conference on Neural Information Processing Systems in December 2025, one of the premier gatherings for AI research.


AI Has No Moral Compass. Do You? — from michelleweise.substack.com by Michelle Weise & Dana Walsh
Why the Age of AI Demands We Take Character Formation Seriously

Here’s something to chew on:

Anthropic, the company behind Claude — a chatbot used by 30 million users per month — has exactly one person (whom we know of) working on AI ethics. One. A young Scottish philosopher is doing the vital work of training a large language model to discern right from wrong.

I don’t say this to shame Anthropic. In fact, Anthropic appears to be the only company (that we know of) being explicit about the moral foundations and reasoning of its chatbot. Hundreds of millions of users worldwide are leveraging tools from other LLMs that do not appear to have an explicit moral compass being cultivated from within.

I raise this because this is yet another example of where we are: extraordinary technical power advancing without an equally strong moral infrastructure to support it.

Why do we keep producing people who are skilled but not wise?

 
 

Teach Smarter with AI — from wondertools.substack.com by Jeremy Caplan and Lance Eaton
10 tested strategies from two educators who actually use them

I recently talked with Lance Eaton, Senior Associate Director of AI and Teaching & Learning at Northeastern University and writer of AI + Education = Simplified. We traded ideas about what’s actually working. We came up with 10 specific, practical ways anyone who teaches, coaches, or leads can put AI to work.

Watch the full conversation above, or read highlights below.


Beyond Audio Summaries: How to Use NotebookLM to *Actually* Design Better Learning — from drphilippahardman.substack.com by Dr. Philippa Hardman
Five methods to maximise the value of NotebookLM’s features

In practice, what makes NotebookLM different for learning designers is four things:

  • Answers grounded in your sources (with citations):
  • Source toggling:
  • Multi-format studio & multi-source summaries:
  • Persistent workspace:


5 Evidence-Based Methods NotebookLM Operationalises…


Shadow AI Isn’t a Threat: It’s a Signal — from campustechnology.com by Damien Eversmann
Unofficial AI use on campus reveals more about institutional gaps than misbehavior.

Key Takeaways

  • Shadow AI is widespread in higher education: Faculty, researchers, students, and staff are using AI tools outside official IT channels, including consumer platforms and public cloud services that may involve sensitive data.
  • Unauthorized AI use creates data, compliance, and cost risks: Consumer AI tools may store or reuse user data, while uncoordinated adoption drives redundant licenses, unpredictable cloud costs, and weaker security oversight.
  • Institutions are shifting from restriction to enablement: Some campuses are making approved paths easier by offering ready-to-use research environments, campus-managed AI tools, clear guidance on data and vendors, and streamlined approval processes.

How L&D Can Lead in the Age of AI Even If Your Company’s Not Ready — from learningguild.com

How to lead even when your company doesn’t allow AI
Even if your corporation isn’t ready for AI, you can still research tools personally to stay ahead of the curve, so when organizational restrictions lift, you are ready to use AI for learning right away. Here are some tools you can test at home if they’re restricted in your workplace:

  • Content generation – Start testing text-based tools to get a taste of how AI can accelerate content creation. Then take it to the next level by exploring tools that generate voices, music, and sound effects.
  • AI coaching tools – Have AI pose as a customer co-worker or customer to get a taste of what it’s like to use it as a conversation coach. Next, use the voice and video capabilities in an app like ChatGPT to explore how AI can coach someone through tasks.
  • In-the-flow learning assistants – Test turning documents into a conversational avatar and interacting with it to see how it feels. Then think about how the technology could potentially transform static content into dynamic learning experiences for employees.
  • Vibe-coded simulations – Experiment with this technology by creating a simple, fun game. Afterwards, brainstorm some ideas on how it could quickly create simulations for your learners in the future.

The Higher Ed Playbook for AI Affordability — from campustechnology.com by Jason Dunn-Potter

Key Takeaways

  • Affordable AI adoption focuses on evolving existing systems: Universities are embedding AI into current devices, workflows, and legacy systems rather than rebuilding infrastructure or investing in new data centers.
  • Edge AI reduces costs and improves access: Running AI models on local devices or networks lowers cloud processing costs, enhances security, and supports learning use cases such as tutoring, translation, transcription, and adaptive learning.
  • Enterprise integration and governance drive impact: Institutions are applying AI across admissions, advising, facilities, and research workflows, supported by shared resource hubs, data governance, AI literacy, and outcome-driven implementation.
 

Report: No Foolproof Method Exists for Detecting AI-Generated Media — from campustechnology.com by Chris Paoli

Key Takeaways

  • Microsoft Research warns no foolproof method exists for detecting AI-generated media reliably.
  • C2PA provenance, watermarking, and fingerprinting each face security and reversal attack risks.
  • Combined high-confidence authentication and public education are crucial for AI media integrity.

 

 
 

“But what’s happening right now is exponential.” — from linkedin.com by Josh Cavalier

Excerpt:

I need to be honest with you. I’ve been running experiments this week with Claude Code and Opus 4.6, and we have reached the precipice in the collapse of time required to produce high-quality text-based ID outputs.

This includes performance consulting reports, learning needs analyses, action mapping, scripts, storyboards, facilitator guides, rubrics, and technical specs.

I just mapped the entire performance consulting process into a multimodal AI integration architecture (diagram image). Every phase. Entry and contracting. Performance analysis. Cause analysis. Solution design. Implementation. Evaluation. Thirty files. System specifications for each. The next step is to vet out each “skill” with an expert performance consultant.

Then I attempted a learning output: an 8-module course built with a cognitive scaffold that moves beyond content delivery to facilitate deliberate practice, meaning-making, and guided reflection within the learner’s own context.

The result:



AI and human-centered learning — from linkedin.com by Patrick Blessinger

Democratizing opportunities

AI adaptive learning can adapt learning in real-time. These tools have the potential to provide a more personalized learning experience, but only if used properly.

The California State University system uses ChatGPT Edu (OpenAI, 2025). Students use it for AI-assisted tutoring, study aids, and writing support. These resources provide 24/7 availability of subject-matter expertise tailored to students’ learning needs. It is not a replacement for professors. Rather, it extends the reach of mentorship by reducing access barriers.

However, we must proceed with intellectual humility and ethical responsibility. Even though AI can customize messages, it cannot replace the encouragement of a teacher or professor, or the social and emotional aspects of learning. It’s at the intersection of humanistic values and knowledge development that education must find its balance.

 

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.

 

Kling 3.0 just launched. The best video model yet. — from heatherbcooper.substack.com by Heather Cooper
& workflows from Imagine Art 1.5 pro, Pixverse Real-Time Video & Genspark

In today’s edition:

  • Kling 3.0: Everyone a Director
  • Character consistency, native audio, 15-second generations & first results
  • Image & Video Prompts
  • Imagine Art 1.5 Pro, Genspark AI Workspace 2.0 & PixVerse Real-Time Video Workflows

Kling 3.0: Everyone a Director
Kling just dropped version 3.0, and it’s a legitimate leap forward for AI video production (Kling is the GOAT). After spending early access time testing the new capabilities, I can confirm this is the most significant update to video generation tools I’ve seen in months.

Key highlights:

  • Character & Element Consistency:
  • Flexible Video Production:
  • Native Audio with Dialogue & Singing:
  • Enhanced Image Generation:
  • Professional Output:
 
© 2025 | Daniel Christian