experimentation

Agents, robots, and us: Skill partnerships in the age of AI — from mckinsey.com by Lareina Yee, Anu Madgavkar, Sven Smit, Alexis Krivkovich, Michael Chui, María Jesús Ramírez, and Diego Castresana
AI is expanding the productivity frontier. Realizing its benefits requires new skills and rethinking how people work together with intelligent machines.

At a glance

Work in the future will be a partnership between people, agents, and robots—all powered by AI. …
Most human skills will endure, though they will be applied differently. …
Our new Skill Change Index shows which skills will be most and least exposed to automation in the next five years….
Demand for AI fluency—the ability to use and manage AI tools—has grown sevenfold in two years…
By 2030, about $2.9 trillion of economic value could be unlocked in the United States…

Also related/see:

The state of AI in 2025: Agents, innovation, and transformation — from mckinsey.com
Almost all survey respondents say their organizations are using AI, and many have begun to use AI agents. But most are still in the early stages of scaling AI and capturing enterprise-level value.

State of AI: December 2025 newsletter — from nathanbenaich.substack.com by Nathan Benaich
What you’ve got to know in AI from the last 4 weeks.

Welcome to the latest issue of the State of AI, an editorialized newsletter that covers the key developments in AI policy, research, industry, and start-ups over the last month.

“Introducing AI assistants with memory” + other items re: AI in our learning ecosystems

On 12/01/2025, in accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, library / librarians, memory, multimedia, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, by Daniel Christian

4 Simple & Easy Ways to Use AI to Differentiate Instruction — from mindfulaiedu.substack.com (Mindful AI for Education) by Dani Kachorsky, PhD
Designing for All Learners with AI and Universal Design Learning

So this year, I’ve been exploring new ways that AI can help support students with disabilities—students on IEPs, learning plans, or 504s—and, honestly, it’s changing the way I think about differentiation in general.

As a quick note, a lot of what I’m finding applies just as well to English language learners or really to any students. One of the big ideas behind Universal Design for Learning (UDL) is that accommodations and strategies designed for students with disabilities are often just good teaching practices. When we plan instruction that’s accessible to the widest possible range of learners, everyone benefits. For example, UDL encourages explaining things in multiple modes—written, visual, auditory, kinesthetic—because people access information differently. I hear students say they’re “visual learners,” but I think everyone is a visual learner, and an auditory learner, and a kinesthetic learner. The more ways we present information, the more likely it is to stick.

So, with that in mind, here are four ways I’ve been using AI to differentiate instruction for students with disabilities (and, really, everyone else too):

The Periodic Table of AI Tools In Education To Try Today — from ictevangelist.com by Mark Anderson

What I’ve tried to do is bring together genuinely useful AI tools that I know are already making a difference.

For colleagues wanting to explore further, I’m sharing the list exactly as it appears in the table, including website links, grouped by category below. Please do check it out, as along with links to all of the resources, I’ve also written a brief summary explaining what each of the different tools do and how they can help.

Seven Hard-Won Lessons from Building AI Learning Tools — from linkedin.com by Louise Worgan

Last week, I wrapped up Dr Philippa Hardman’s intensive bootcamp on AI in learning design. Four conversations, countless iterations, and more than a few humbling moments later – here’s what I am left thinking about.

Finally Catching Up to the New Models — from michellekassorla.substack.com by Michelle Kassorla
There are some amazing things happening out there!

An aside: Google is working on a new vision for textbooks that can be easily differentiated based on the beautiful success for NotebookLM. You can get on the waiting list for that tool by going to LearnYourWay.withgoogle.com.
…
Nano Banana Pro
Sticking with the Google tools for now, Nano Banana Pro (which you can use for free on Google’s AI Studio), is doing something that everyone has been waiting a long time for: it adds correct text to images.

Introducing AI assistants with memory — from perplexity.ai

The simple act of remembering is the crux of how we navigate the world: it shapes our experiences, informs our decisions, and helps us anticipate what comes next. For AI agents like Comet Assistant, that continuity leads to a more powerful, personalized experience.

Today we are announcing new personalization features to remember your preferences, interests, and conversations. Perplexity now synthesizes them automatically like memory, for valuable context on relevant tasks. Answers are smarter, faster, and more personalized, no matter how you work.

From DSC :
This should be important as we look at learning-related applications for AI.

For the last three days, my Substack has been in the top “Rising in Education” list. I realize this is based on a hugely flawed metric, but it still feels good. ?

– Michael G Wagner

Read on Substack

I’m a Professor. A.I. Has Changed My Classroom, but Not for the Worse. — from nytimes.com by Carlo Rotella [this should be a gifted article]
My students’ easy access to chatbots forced me to make humanities instruction even more human.

Law Firm 2.0: A Trillion-Dollar Market Begins To Move — from abovethelaw.com by Ken Crutchfield
The test cases for Law Firm 2.0 are arriving faster than many expected.

A move to separate legal advice from other legal services that don’t require advice is a big shift that would ripple through established firms and also test regulatory boundaries.
…
The LegalTech Fund (TLTF) sees a $1 trillion opportunity to reinvent legal services through the convergence of technology, regulatory changes, and innovation. TLTF calls this movement Law Firm 2.0, and the fund believes a reinvention will pave the way for entirely new, tech-enabled models of legal service delivery.

From Paper to Platform: How LegalTech Is Revolutionizing the Practice of Law — from markets.financialcontent.com by AB Newswire

For decades, practicing law has been a business about paper — contracts, case files, court documents, and floor-to-ceiling piles of precedent. But as technology transforms all aspects of modern-day business, law firms and in-house legal teams are transforming along with it. The development of LegalTech has revolutionized what was previously a paper-driven, manpower-intensive profession into a data-driven digital web of collaboration and automation.

Conclusion: Building the Future of Law
The practice of law has always been about accuracy, precedent, and human beings. Technology doesn’t alter that — it magnifies it. The shift to the platform from paper is about liberating lawyers from back-office tasks so they can concentrate on strategy, advocacy, and creativity.

By coupling intelligent automation with moral obligation, today’s firms are positioning the legal profession for a more intelligent, responsive industry. LegalTech isn’t about automation, it’s about empowering attorneys to practice at the speed of today’s business.

What Legal Can Learn from Other Industries’ AI Transformations — from jdsupra.com

Artificial intelligence has already redefined how industries like finance, healthcare, and supply chain operate — transforming once-manual processes into predictive, data-driven engines of efficiency.

Yet the legal industry, while increasingly open to innovation, still lags behind its peers in adopting automation at scale. As corporate legal departments face mounting pressure to do more with less, they have an opportunity to learn from how other sectors successfully integrated AI into their operations.

The message is clear: AI transformation doesn’t just change workflows — it changes what’s possible.

7 Legal Tech Trends To Watch In 2026 — from lexology.com

Small Language Models Are Changing Legal Tech: What That Means for Lawyers and Law Firms — from community.nasscom.in

The legal profession is at a turning point. Artificial intelligence tools are moving from novelty to everyday utility, and small language models, or SLMs, are a major reason why. For law firms and in-house legal teams that are balancing client confidentiality, tight budgets, and the need to move faster, SLMs offer a practical, high impact way to bring legal AI into routine practice. This article explains what SLMs are, why they matter to lawyers, where they fit in legal workflows, and how to adopt them responsibly.

Legal AI startup draws new $50 million Blackstone investment, opens law firm — from reuters.com by Sara Merken

NEW YORK, Nov 20 (Reuters) – Asset manager Blackstone (BX.N), opens new tab has invested $50 million in Norm Ai, a legal and compliance technology startup that also said on Thursday that it is launching an independent law firm that will offer “AI-native legal services.”

Lawyers at the new New York-based firm, Norm Law LLP, will use Norm Ai’s artificial intelligence technology to do legal work for Blackstone and other financial services clients, said Norm Ai founder and CEO John Nay.

Law School Toolbox Podcast Episode 531: What Law Students Should Know About New Legal Tech (w/Gabe Teninbaum) — from jdsupra.com

Today, Alison and Gabe Teninbaum — law professor and creator of SpacedRepetition.com — discuss how technology is rapidly transforming the legal profession, emphasizing the importance for law students and lawyers to develop technological competence and adapt to new tools and roles in the legal profession.

New York is the San Francisco of legal tech — from businessinsider.com by Melia Russell

Legal tech ?? NYC.
To win the market, startups say they need to be where the law firms and corporate legal chiefs are.
Legora and Harvey are expanding their footprints in New York, as Clio hunts for office space.

Legal Tech Startups Expand in New York to Access Law Firms — from indexbox.io

Several legal technology startups are expanding their physical presence in New York City, according to a report from Legal tech NYC. The companies state that to win market share, they need to be located where major law firms and corporate legal departments are based.

Linklaters unveils 20-strong ‘AI lawyer’ team — from legalcheek.com by Legal Cheek

Magic Circle giant Linklaters has launched a team of 20 ‘AI Lawyers’ (yes, that is their actual job title) as it ramps up its commitment to artificial intelligence across its global offices.

The new cohort is a mix of external tech specialists and Linklaters lawyers who have decided to boost their legal expertise with advanced AI know-how. They will be placed into practice groups around the world to help build prompts, workflows and other tech driven processes that the firm hopes will sharpen client delivery.

I went to a closed-door retreat for top lawyers. The message was clear: Don’t fear AI — use it. — from businessinsider.com by Melia Russell

AI is making its mark on law firms and corporate legal teams.
Clients expect measurable savings, and firms are spending real money to deliver them.
At TLTF Summit, Big Law leaders and legal-tech builders explored the future of the industry.

From Cost Center to Command Center: The Future of Litigation is Being Built In-House — from law.stanford.edu by Adam Rouse, Tamra Moore, Renee Meisel, Kassi Burns, & Olga Mack

Litigation isn’t going away, but who leads, drafts, and drives it is rapidly changing. Empirical research shows corporate legal departments have steadily expanded litigation management functions over the past decade. (Annual Litigation Trends Survey, Norton Rose Fulbright (2025)).

For decades, litigation lived squarely in the law firm domain. (Wald, Eli, Getting in and Out of the House: Career Trajectories of In-House Lawyers, Fordham Law Review, Vol. 88, No. 1765, 2020 (June 22, 2020)). Corporate legal departments played a responsive role: approving strategies, reviewing documents, and paying hourly rates. But through dozens of recent conversations with in-house legal leaders, legal operations professionals, and litigation specialists, a new reality is emerging. One in which in-house counsel increasingly owns the first draft, systematizes their litigation approach, and reshapes how outside counsel fits into the picture.

AI, analytics, exemplar libraries, playbooks, and modular document builders are not simply tools. They are catalysts for a structural shift. Litigation is becoming modular, data-informed, and orchestrated by in-house teams who increasingly want more than cost control. They want consistency, clarity, and leverage. This piece outlines five major trends from our qualitative research, predictions on their impact to the practice of law, and research questions that are worth considering to further understand these trends. A model is then introduced for understanding how litigation workflows and outside counsel relationships will evolve in the coming years.

Could Your Next Side Hustle Be Training AI? — from builtin.com by Jeff Rumage
As automation continues to reshape the labor market, some white-collar professionals are cashing in by teaching AI models to do their jobs.

Summary: Artificial intelligence may be replacing jobs, but it’s also creating some new ones. Professionals in fields like medicine, law and engineering can earn big money training AI models, teaching them human skills and expertise that may one day make those same jobs obsolete.

DEEP DIVE: The AI user interface of the future = Voice — from theneurondaily.com by Grant Harvey
PLUS: Gemini 3.0 and Microsoft’s new voice features

Here’s the thing: voice is finally good enough to replace typing now. And I mean actually good enough, not “Siri, play Despacito” good enough.

To Paraphrase Andrej Karpathy’s famous quote, “the hottest new programming language is English”, in this case, the hottest new user interface is talking.

The Great Convergence: Why Voice Is Having Its Moment
Three massive shifts just collided to make voice interfaces inevitable.

1. First, speech recognition stopped being terrible. …
2. Second, our devices got ears everywhere. …
3. Third, and most importantly: LLMs made voice assistants smart enough to be worth talking to. …

Introducing group chats in ChatGPT — from openai.com
Collaborate with others, and ChatGPT, in the same conversation.

Update on November 20, 2025: Early feedback from the pilot has been positive, so we’re expanding group chats to all logged-in users on ChatGPT Free, Go, Plus and Pro plans globally over the coming days. We will continue refining the experience as more people start using it.

Today, we’re beginning to pilot a new experience in a few regions that makes it easy for people to collaborate with each other—and with ChatGPT—in the same conversation. With group chats, you can bring friends, family, or coworkers into a shared space to plan, make decisions, or work through ideas together.

Whether you’re organizing a group dinner or drafting an outline with coworkers, ChatGPT can help. Group chats are separate from your private conversations, and your personal ChatGPT memory is never shared with anyone in the chat.

“Textbooks are no longer one-size-fits-all” [Fitzpatrick] + other items re: AI in our learning ecosystems

On 11/18/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, change, changing business models, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learner profiles, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, lifelong learning, Open AI, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, training / L&D, trends, United States, universities, vendors, by Daniel Christian

Three Years from GPT-3 to Gemini 3 — from oneusefulthing.org by Ethan Mollick
From chatbots to agents

Three years ago, we were impressed that a machine could write a poem about otters. Less than 1,000 days later, I am debating statistical methodology with an agent that built its own research environment. The era of the chatbot is turning into the era of the digital coworker. To be very clear, Gemini 3 isn’t perfect, and it still needs a manager who can guide and check it. But it suggests that “human in the loop” is evolving from “human who fixes AI mistakes” to “human who directs AI work.” And that may be the biggest change since the release of ChatGPT.

Results May Vary — from aiedusimplified.substack.com by Lance Eaton, PhD
On Custom Instructions with GenAI Tools….

I’m sharing today about custom instructions and my use of them across several AI tools (paid versions of ChatGPT, Gemini, and Claude). I want to highlight what I’m doing, how it’s going, and solicit from readers to share in the comments some of their custom instructions that they find helpful.

I’ve been in a few conversations lately that remind me that not everyone knows about them, even some of the seasoned folks around GenAI and how you might set them up to better support your work. And, of course, they are, like all things GenAI, highly imperfect!

I’ll include and discuss each one below, but if you want to keep abreast of my custom instructions, I’ll be placing them here as I adjust and update them so folks can see the changes over time.

“ElevenLabs just launched a voice marketplace” + [GIFTED ARTICLE] “How people really use ChatGPT” + several other items re: AI in general

On 11/13/2025, in 21st century, 24x7x365 access, A/V -- audio/visual, Artificial Intelligence/Agents/LLMs/and Related, bots, computer science, content development, aggregation, repositories, corporate / business world, creativity, digital audio, emerging technologies, Emotion, engagement / engaging students, experimentation, global / globalization, history, human-computer interaction (HCI), innovation, media/film, platforms, play, productivity / tips and tricks, programming, society, story, storytelling, the downsides of how people use tech, tools, trends, United States, vendors, by Daniel Christian

ElevenLabs just launched a voice marketplace — from elevenlabs.io; via theaivalley.com

Via the AI Valley:

Why does it matter?
AI voice cloning has already flooded the internet with unauthorized imitations, blurring legal and ethical lines. By offering a dynamic, rights-secured platform, ElevenLabs aims to legitimize the booming AI voice industry and enable transparent, collaborative commercialization of iconic IP.
.

[GIFTED ARTICLE] How people really use ChatGPT, according to 47,000 conversations shared online — from by Gerrit De Vynck and Jeremy B. Merrill
What do people ask the popular chatbot? We analyzed thousands of chats to identify common topics discussed by users and patterns in ChatGPT’s responses.

.
Data released by OpenAI in September from an internal study of queries sent to ChatGPT showed that most are for personal use, not work.

Emotional conversations were also common in the conversations analyzed by The Post, and users often shared highly personal details about their lives. In some chats, the AI tool could be seen adapting to match a user’s viewpoint, creating a kind of personalized echo chamber in which ChatGPT endorsed falsehoods and conspiracy theories.

Lee Rainie, director of the Imagining the Digital Future Center at Elon University, said his own research has suggested ChatGPT’s design encourages people to form emotional attachments with the chatbot. “The optimization and incentives towards intimacy are very clear,” he said. “ChatGPT is trained to further or deepen the relationship.”

Per The Rundown: OpenAI just shared its view on AI progress, predicting systems will soon become smart enough to make discoveries and calling for global coordination on safety, oversight, and resilience as the technology nears superintelligent territory.

The details:

OpenAI said current AI systems already outperform top humans in complex intellectual tasks and are “80% of the way to an AI researcher.”
The company expects AI will make small scientific discoveries by 2026 and more significant breakthroughs by 2028, as intelligence costs fall 40x per year.
For superintelligent AI, OAI said work with governments and safety agencies will be essential to mitigate risks like bioterrorism or runaway self-improvement.
It also called for safety standards among top labs, a resilience ecosystem like cybersecurity, and ongoing tracking of AI’s real impact to inform public policy.

Why it matters: While the timeline remains unclear, OAI’s message shows that the world should start bracing for superintelligent AI with coordinated safety. The company is betting that collective safeguards will be the only way to manage risk from the next era of intelligence, which may diffuse in ways humanity has never seen before.

Which linked to:

AI progress and recommendations — from openai.com
AI is unlocking new knowledge and capabilities. Our responsibility is to guide that power toward broad, lasting benefit.

From DSC:
I hate to say this, but it seems like there is growing concern amongst those who have pushed very hard to release as much AI as possible — they are NOW worried. They NOW step back and see that there are many reasons to worry about how these technologies can be negatively used.

Where was this level of concern before (while they were racing ahead at 180 mph)? Surely, numerous and knowledgeable people inside those organizations warned them about the destructive/downside of these technologies. But their warnings were pretty much blown off (at least from my limited perspective).

The state of AI in 2025: Agents, innovation, and transformation — from mckinsey.com

Key findings

Most organizations are still in the experimentation or piloting phase: Nearly two-thirds of respondents say their organizations have not yet begun scaling AI across the enterprise.
High curiosity in AI agents: Sixty-two percent of survey respondents say their organizations are at least experimenting with AI agents.
Positive leading indicators on impact of AI: Respondents report use-case-level cost and revenue benefits, and 64 percent say that AI is enabling their innovation. However, just 39 percent report EBIT impact at the enterprise level.
High performers use AI to drive growth, innovation, and cost: Eighty percent of respondents say their companies set efficiency as an objective of their AI initiatives, but the companies seeing the most value from AI often set growth or innovation as additional objectives.
Redesigning workflows is a key success factor: Half of those AI high performers intend to use AI to transform their businesses, and most are redesigning workflows.
Differing perspectives on employment impact: Respondents vary in their expectations of AI’s impact on the overall workforce size of their organizations in the coming year: 32 percent expect decreases, 43 percent no change, and 13 percent increases.

Marble: A Multimodal World Model — from worldlabs.ai

Spatial intelligence is the next frontier in AI, demanding powerful world models to realize its full potential. World models should reconstruct, generate, and simulate 3D worlds; and allow both humans and agents to interact with them. Spatially intelligent world models will transform a wide variety of industries over the coming years.

Two months ago we shared a preview of Marble, our World Model that creates 3D worlds from image or text prompts. Since then, Marble has been available to an early set of beta users to create 3D worlds for themselves.

Today we are making Marble, a first-in-class generative multimodal world model, generally available for anyone to use. We have also drastically expanded Marble’s capabilities, and are excited to highlight them here:

The problem with just handing over an army of agents to junior consultants + other items re: AI in general

On 11/05/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, changing business models, collaboration, emerging technologies, experimentation, leadership, strategy, the downsides of how people use tech, tools, United States, vendors, workplace, by Daniel Christian

KPMG wants junior consultants to ditch the grunt work and hand it over to teams of AI agents — from businessinsider.com by Polly Thompson

The Big Four consulting and accounting firm is training its junior consultants to manage teams of AI agents — digital assistants capable of completing tasks without human input.

“We want juniors to become managers of agents,” Niale Cleobury, KPMG’s global AI workforce lead, told Business Insider in an interview.

KPMG plans to give new consulting recruits access to a catalog of AI agents capable of creating presentation slides, analyzing data, and conducting in-depth research, Cleobury said.

The goal is for these agents to perform much of the analytical and administrative work once assigned to junior consultants, allowing them to become more involved in strategic decisions.

From DSC:
For a junior staff member to provide quality assurance in working with agents, an employee must know what they’re talking about in the first place. They must have expertise and relevant knowledge. Otherwise, how will they spot the hallucinations?

So the question is, how can businesses build such expertise in junior staff members while they are delegating things to an army of agents? This question applies to the next posting below as well. Having agents report to you is all well and good — IF you know when the agents are producing helpful/accurate information and when they got things all wrong.

This Is the Next Vital Job Skill in the AI Economy — from builtin.com by Saurabh Sharma
The future of tech work belongs to AI managers.

Summary: A fundamental shift is making knowledge workers “AI managers.” The most valuable employees will direct intelligent AI agents, which requires new competencies: delegation, quality assurance and workflow orchestration across multiple agents. Companies must bridge the training gap to enable this move from simple software use to strategic collaboration with intelligent, yet imperfect, systems.

The shift is happening subtly, but it’s happening. Workers are learning to prompt agents, navigate AI capabilities, understand failure modes and hand off complex tasks to AI. And if they haven’t started yet, they probably will: A new study from IDC and Salesforce found that 72 percent of CEOs think most employees will have an AI agent reporting to them within five years. This isn’t about using a new kind of software tool — it’s about directing intelligent systems that can reason, search, analyze and create.

Soon, the most valuable employees won’t just know how to use AI; they’ll know how to manage it. And that requires a fundamentally different skill set than anything we’ve taught in the workplace before.

AI agents failed 97% of freelance tasks; here’s why… — from theneurondaily.com by Grant Harvey

AI Agents Can’t Actually Do Your Job (Yet)—New Benchmark Reveals The Gap

DEEP DIVE: AI can make you faster at your job, but can only do 2-3% of jobs by itself.

The hype: AI agents will automate entire workflows! Replace freelancers! Handle complex tasks end-to-end!

The reality: a measly 2-3% completion rate.

See, Scale AI and CAIS just released the Remote Labor Index (paper), a benchmark where AI agents attempted real freelance tasks. The best-performing model earned just $1,810 out of $143,991 in available work, and yes, finishing only 2-3% of jobs.

“…a new operating system for L&D in the age of AI?” [Hardman] + other items re: AI in our learning ecosystems

On 10/30/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, higher education, human-computer interaction (HCI), India, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, liberal arts, training / L&D, by Daniel Christian

Custom AI Development: Evolving from Static AI Systems to Dynamic Learning Agents in 2025 — community.nasscom.in

This blog explores how custom AI development accelerates the evolution from static AI to dynamic learning agents and why this transformation is critical for driving innovation, efficiency, and competitive advantage.
…
Dynamic Learning Agents: The Next Generation
Dynamic learning agents, sometimes referred to as adaptive or agentic AI, represent a leap forward. They combine continuous learning, autonomous action, and context-aware adaptability.

Custom AI development plays a crucial role here: it ensures that these agents are designed specifically for an enterprise’s unique needs rather than relying on generic, one-size-fits-all AI platforms. Tailored dynamic agents can:

Continuously learn from incoming data streams
Make autonomous, goal-directed decisions aligned with business objectives
Adapt behavior in real time based on context and feedback
Collaborate with other AI agents and human teams to solve complex challenges

The result is an AI ecosystem that evolves with the business, providing sustained competitive advantage.

Also from community.nasscom.in, see:

Building AI Agents with Multimodal Models: From Perception to Action

Perception: The Foundation of Intelligent Agents
Perception is the first step in building AI agents. It involves capturing and interpreting data from multiple modalities, including text, images, audio, and structured inputs. A multimodal AI agent relies on this comprehensive understanding to make informed decisions.

For example, in healthcare, an AI agent may process electronic health records (text), MRI scans (vision), and patient audio consultations (speech) to build a complete understanding of a patient’s condition. Similarly, in retail, AI agents can analyze purchase histories (structured data), product images (vision), and customer reviews (text) to inform recommendations and marketing strategies.

Effective perception ensures that AI agents have contextual awareness, which is essential for accurate reasoning and appropriate action.

From 70-20-10 to 90-10: a new operating system for L&D in the age of AI? — from linkedin.com by Dr. Philippa Hardman

Also from Philippa, see:

Defining & Navigating the Jagged Frontier in Instructional Design (October, 2025)
What we know about where AI helps (and where it hinders) Instructional Design, and how to manage it

Your New ChatGPT Guide — from wondertools.substack.com by Jeremy Caplan and The PyCoach
25 AI Tips & Tricks from a guest expert

ChatGPT can make you more productive or dumber. An MIT study found that while AI can significantly boost productivity, it may also weaken your critical thinking. Use it as an assistant, not a substitute for your brain.
If you’re a student, use study mode in ChatGPT, Gemini, or Claude. When this feature is enabled, the chatbots will guide you through problems rather than just giving full answers, so you’ll be doing the critical thinking.
ChatGPT and other chatbots can confidently make stuff up (aka AI hallucinations). If you suspect something isn’t right, double-check its answers.
NotebookLM hallucinates less than most AI tools, but it requires you to upload sources (PDFs, audio, video) and won’t answer questions beyond those materials. That said, it’s great for students and anyone with materials to upload.
Probably the most underrated AI feature is deep research. It automates web searching for you and returns a fully cited report with minimal hallucinations in five to 30 minutes. It’s available in ChatGPT, Perplexity, and Gemini, so give it a try.

Adobe Reinvents its Entire Creative Suite with AI Co-Pilots, Custom Models, and a New Open Platform — from theneuron.ai by Grant Harvey
Adobe just put an AI co-pilot in every one of its apps, letting you chat with Photoshop, train models on your own style, and generate entire videos with a single subscription that now includes top models from Google, Runway, and Pika.

Adobe came to play, y’all.

At Adobe MAX 2025 in Los Angeles, the company dropped an entire creative AI ecosystem that touches every single part of the creative workflow. In our opinion, all these new features aren’t about replacing creators; it’s about empowering them with superpowers they can actually control.

Adobe’s new plan is to put an AI co-pilot in every single app.

For professionals, the game-changer is Firefly Custom Models. Start training one now to create a consistent, on-brand look for all your assets.
For everyday creators, the AI Assistants in Photoshop and Express will drastically speed up your workflow.
The best place to start is the Photoshop AI Assistant (currently in private beta), which offers a powerful glimpse into the future of creative software—a future where you’re less of a button-pusher and more of a creative director.

Adobe MAX Day 2: The Storyteller Is Still King, But AI Is Their New Superpower — from theneuron.ai by Grant Harvey
Adobe’s Day 2 keynote showcased a suite of AI-powered creative tools designed to accelerate workflows, but the real message from creators like Mark Rober and James Gunn was clear: technology serves the story, not the other way around.

On the second day of its annual MAX conference, Adobe drove home a message that has been echoing through the creative industry for the past year: AI is not a replacement, but a partner. The keynote stage featured a powerful trio of modern storytellers—YouTube creator Brandon Baum, science educator and viral video wizard Mark Rober, and Hollywood director James Gunn—who each offered a unique perspective on a shared theme: technology is a powerful tool, but human instinct, hard work, and the timeless art of storytelling remain paramount.

From DSC:
As Grant mentioned, the demos dealt with ideation, image generation, video generation, audio generation, and editing.

Adobe Max 2025: all the latest creative tools and AI announcements — from theverge.com by Jess Weatherbed

The creative software giant is launching new generative AI tools that make digital voiceovers and custom soundtracks for videos, and adding AI assistants to Express and Photoshop for web that edit entire projects using descriptive prompts. And that’s just the start, because Adobe is planning to eventually bring AI assistants to all of its design apps.

Also see Adobe Delivers New AI Innovations, Assistants and Models Across Creative Cloud to Empower Creative Professionals plus other items from the News section from Adobe

“OpenAI’s Atlas: the End of Online Learning—or Just the Beginning?” [Hardman] + other items re: AI in our LE’s

On 10/28/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, assistive technologies, change, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, internet, IT in HE, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, memory, online learning, online media, online tutoring, Open AI, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, reading, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vendors, virtual tutoring, vision/possibilities, web-based collaboration, by Daniel Christian

OpenAI’s Atlas: the End of Online Learning—or Just the Beginning? — from drphilippahardman.substack.com by Dr. Philippa Hardman

My take is this: in all of the anxiety lies a crucial and long-overdue opportunity to deliver better learning experiences. Precisely because Atlas perceives the same context in the same moment as you, it can transform learning into a process aligned with core neuro-scientific principles—including active retrieval, guided attention, adaptive feedback and context-dependent memory formation.

Perhaps in Atlas we have a browser that for the first time isn’t just a portal to information, but one which can become a co-participant in active cognitive engagement—enabling iterative practice, reflective thinking, and real-time scaffolding as you move through challenges and ideas online.

With this in mind, I put together 10 use cases for Atlas for you to try for yourself.
…

6. Retrieval Practice
What: Pulling information from memory drives retention better than re-reading.
Why: Practice testing delivers medium-to-large effects (Adesope et al., 2017).
Try: Open a document with your previous notes. Ask Atlas for a mixed activity set: “Quiz me on the Krebs cycle—give me a near-miss, high-stretch MCQ, then a fill-in-the-blank, then ask me to explain it to a teen.”
Atlas uses its browser memory to generate targeted questions from your actual study materials, supporting spaced, varied retrieval.

From DSC:
A quick comment. I appreciate these ideas and approaches from Katarzyna and Rita. I do think that someone is going to want to be sure that the AI models/platforms/tools are given up-to-date information and updated instructions — i.e., any new procedures, steps to take, etc. Perhaps I’m missing the boat here, but an internal AI platform is going to need to have access to up-to-date information and instructions.

How To Increase (Self-)Motivation [Kuepper-Tetzel]

On 10/27/2025, in education, Emotion, experimentation, faculty/staff, homeschooling/homeschoolers, K-12 related, learning, motivation, parents/guardians, productivity / tips and tricks, psychology, society, student-related, teachers, by Daniel Christian

Digest #182: How To Increase (Self-)Motivation — from lifehack.org by Carolina Kuepper-Tetzel

No matter whether you are a student or a teacher, sometimes it can be difficult to find motivation to start or complete a task. Instead, you may spend hours procrastinating with other activities and that opens an unhelpful cycle of stress and unhappiness. Stressful environments which are common in educational settings can increase the likelihood of maladaptive procrastination (1) and hamper motivation. This digest offers four resources on ways to think about and boost (self-)motivation.

Also see:

“How do we optimize an AI to support learning?” [Downes] + several other items re: AI in our LE’s

On 10/23/2025, in 21st century, 24x7x365 access, accessibility / UDL, Artificial Intelligence/Agents/LLMs/and Related, bots, Canada, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, languages and translation, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, neurodivergent/special needs, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, trends, United States, universities, writing, by Daniel Christian

There is no God Tier video model — from downes.ca by Stephen Downes

From DSC:
Stephen has some solid reflections and asks some excellent questions in this posting, including:

The question is: how do we optimize an AI to support learning? Will one model be enough? Or do we need different models for different learners in different scenarios?

A More Human University: The Role of AI in Learning — from er.educause.edu by Robert Placido
Far from heralding the collapse of higher education, artificial intelligence offers a transformative opportunity to scale meaningful, individualized learning experiences across diverse classrooms.

The narrative surrounding artificial intelligence (AI) in higher education is often grim. We hear dire predictions of an “impending collapse,” fueled by fears of rampant cheating, the erosion of critical thinking, and the obsolescence of the human educator.Footnote1 This dystopian view, however, is a failure of imagination. It mistakes the death rattle of an outdated pedagogical model for the death of learning itself. The truth is far more hopeful: AI is not an asteroid coming for higher education. It is a catalyst that can finally empower us to solve our oldest, most intractable problem: the inability to scale deep, engaged, and truly personalized learning.

Claude for Life Sciences — from anthropic.com

Increasing the rate of scientific progress is a core part of Anthropic’s public benefit mission.

We are focused on building the tools to allow researchers to make new discoveries – and eventually, to allow AI models to make these discoveries autonomously.

Until recently, scientists typically used Claude for individual tasks, like writing code for statistical analysis or summarizing papers. Pharmaceutical companies and others in industry also use it for tasks across the rest of their business, like sales, to fund new research. Now, our goal is to make Claude capable of supporting the entire process, from early discovery through to translation and commercialization.

To do this, we’re rolling out several improvements that aim to make Claude a better partner for those who work in the life sciences, including researchers, clinical coordinators, and regulatory affairs managers.

AI as an access tool for neurodiverse and international staff — from timeshighereducation.com by Vanessa Mar-Molinero
Used transparently and ethically, GenAI can level the playing field and lower the cognitive load of repetitive tasks for admin staff, student support and teachers

Where AI helps without cutting academic corners
When framed as accessibility and quality enhancement, AI can support staff to complete standard tasks with less friction. However, while it supports clarity, consistency and inclusion, generative AI (GenAI) does not replace disciplinary expertise, ethical judgement or the teacher–student relationship. These are ways it can be put to effective use:

Drafting and tone calibration: …
Language scaffolding: …
Structure and templates: ..
Summarise and prioritise: …
Accessibility by default: …
Idea generation for pedagogy: …
Translation and cultural mediation: …

Beyond learning design: supporting pedagogical innovation in response to AI — from timeshighereducation.com by Charlotte von Essen
To avoid an unwinnable game of catch-up with technology, universities must rethink pedagogical improvement that goes beyond scaling online learning

The Sleep of Liberal Arts Produces AI — from aiedusimplified.substack.com by Lance Eaton, Ph.D.
A keynote at the AI and the Liberal Arts Symposium Conference

This past weekend, I had the honor to be the keynote speaker at a really fantstistic conferece, AI and the Liberal Arts Symposium at Connecticut College. I had shared a bit about this before with my interview with Lori Looney. It was an incredible conference, thoughtfully composed with a lot of things to chew on and think about.

It was also an entirely brand new talk in a slightly different context from many of my other talks and workshops. It was something I had to build entirely from the ground up. It reminded me in some ways of last year’s “What If GenAI Is a Nothingburger”.

It was a real challenge and one I’ve been working on and off for months, trying to figure out the right balance. It’s a work I feel proud of because of the balancing act I try to navigate. So, as always, it’s here for others to read and engage with. And, of course, here is the slide deck as well (with CC license).

The Most Innovative Law Schools (2025) — from abovethelaw.com by Staci Zaretsky
Forget dusty casebooks — today’s leaders in legal education are using AI, design thinking, and real-world labs to reinvent how law is taught.

“[F]rom AI labs and interdisciplinary centers to data-driven reform and bold new approaches to design and client service,” according to National Jurist’s preLaw Magazine, these are the law schools that “exemplify innovation in action.”

North Carolina Central University School of Law
Suffolk University Law School
UC Berkeley School of Law
Nova Southeastern University Shepard Broad College of Law
Northeastern University School of Law
Maurice A. Deane School of Law at Hofstra University
Seattle University School of Law
Case Western Reserve University School of Law
University of Miami School of Law
Benjamin N. Cardozo School of Law at Yeshiva University
Vanderbilt University Law School
Southwestern Law School

Click here to read short summaries of why each school made this year’s list of top innovators.

Clio’s Metamorphosis: From Practice Management To A Comprehensive AI And Law Practice Provider — from abovethelaw.com by Stephen Embry
Clio is no longer a practice management company. It’s much more of a comprehensive provider of all needs of its customers big and small.

Newton delivered what may have been the most consequential keynote in the company’s history and one that signals a shift by Clio from a traditional practice management provider to a comprehensive platform that essentially does everything for the business and practice of law.
…
Clio also earlier this year acquired vLex, the heavy-duty AI legal research player. The acquisition is pending regulatory approval. It is the vLex acquisition that is powering the Clio transformation that Newton described in his keynote.

vLex has a huge amount of legal data in its wheelhouse to power sophisticated legal AI research. On top of this data, vLex developed Vincent, a powerful AI tool to work with this data and enable all sorts of actions and work.

This means a couple of things. First, by acquiring vLex, Clio can now offer its customers AI legal research tools. Clio customers will no longer have to go one place for its practice management needs and a second place for its substantive legal work, like research. It makes what Clio can provide much more comprehensive and all inclusive.

‘Adventures In Legal Tech’: How AI Is Changing Law Firms — from abovethelaw.com
Ernie the Attorney shares his legal tech takes.

Artificial intelligence will give solos and small firms “a huge advantage,” according to one legal tech consultant.

In this episode of “Adventures in Legal Tech,” host Jared Correia speaks with Ernie Svenson — aka “Ernie the Attorney” — about the psychology behind resistance to change, how law firms are positioning their AI use, the power of technology for business development, and more.

Legal software: how to look for and compare AI in legal technology — from legal.thomsonreuters.com by Chris O’Leary

Highlights

Legal ops experts can categorize legal AI platforms and software by the ability to streamline key tasks such as legal research, document processing or analysis, and drafting.
The trustworthiness and accuracy of AI hinge on the quality of its underlying data; solutions like CoCounsel Legal are grounded in authoritative, expert-verified content from Westlaw and Practical Law, unlike providers that may rely on siloed or less reliable databases.
When evaluating legal software, firms should use a framework that assesses critical factors such as integration with existing tech stacks, security, scalability, user adoption, and vendor reputation.

ASU Law appoints a director of AI and Legal Tech Studio, advancing its initiative to reimagine legal education — from law.asu.edu

The Sandra Day O’Connor College of Law at Arizona State University appointed Sean Harrington as director of the newly established AI and Legal Tech Studio, a key milestone in ASU Law’s bold initiative to reimagine legal education for the artificial intelligence era. ASU, ranked No. 1 in innovation for the 11th consecutive year, drives AI solutions that enhance teaching, enrich student training and facilitate digital transformation.

The American Legal Technology Awards Name 2025 Winners — from natlawreview.com by Tom Martin

The sixth annual American Legal Technology Awards were presented on Wednesday, October 15th, at Suffolk University Law School (Boston), recognizing winners across ten categories. There were 211 nominees who were evaluated by 27 judges.

The honorees on the night included:

How a Gemma model helped discover a new potential cancer therapy pathway [Google]

On 10/21/2025, in Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, experimentation, Google, health, platforms, research, science, tools, by Daniel Christian

How a Gemma model helped discover a new potential cancer therapy pathway — from blog.google by Shekoofeh Azizi and Bryan Perozzi
We’re launching a new 27 billion parameter foundation model for single-cell analysis built on the Gemma family of open models.

Today, as part of our research collaboration with Yale University, we’re releasing Cell2Sentence-Scale 27B (C2S-Scale), a new 27 billion parameter foundation model designed to understand the language of individual cells. Built on the Gemma family of open models, C2S-Scale represents a new frontier in single-cell analysis.

This announcement marks a milestone for AI in science. C2S-Scale generated a novel hypothesis about cancer cellular behavior and we have since confirmed its prediction with experimental validation in living cells. This discovery reveals a promising new pathway for developing therapies to fight cancer.

From siloed tools to intelligent journeys: Reimagining learning experience in the age of ‘Experience AI’ [Gonick]

On 10/17/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, changing business models, CMS/LMS, collaboration, colleges, community colleges, digital learning, education, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, memory, multimedia, personalized/customized learning, platforms, student-related, teaching & learning, United States, universities, vision/possibilities, by Daniel Christian

From siloed tools to intelligent journeys: Reimagining learning experience in the age of ‘Experience AI’ — from linkedin.com by Lev Gonick

Experience AI: A new architecture of learning
Experience AI represents a new architecture for learning — one that prioritizes continuity, agency and deep personalization. It fuses three dimensions into a new category of co-intelligent systems:

Agentic AI that evolves with the learner, not just serves them
Persona-based AI that adapts to individual goals, identities and motivations
Multimodal AI that engages across text, voice, video, simulation and interaction

Experience AI brings learning into context. It powers personalized, problem-based journeys where students explore ideas, reflect on progress and co-create meaning — with both human and machine collaborators.

Learning Ecosystems

Announcements from Adobe — esp. focused on AI

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