From DSC: I used to be able to bring up Firefly on the web and use it “free” of charge — I didn’t have to go purchase tokens or credits. (I was actually paying for the Adobe Creative Cloud Pro suite of tools…so it wasn’t really free.)
But the other day I was trying to figure out what the latest pricing is at Adobe with that suite of tools and the use of credits for AI-based features. They say Adobe Creative Cloud Pro users get 4000 credits a month. Well, I have that suite and I’m still getting prompted to purchase credits. Firefly for individuals runs from $9.99 (2,000 credits/month) to $139.91 per month (50,000 credits per month). Not inexpensive, right? Below are other items along these lines.
The Era of Affordable AI Is Over. What Comes Next? — from builtin.com by Ameya Kanitkar AI providers are shifting to usage-based billing for their services. AI fluency is more important now than ever to make the most of your tools to avoid unnecessary spending.
Summary: The era of cheap, flat-rate AI is ending as providers shift to usage-based billing. Every prompt now carries a direct cost, turning casual use into major budget risks, as seen when Uber depleted its 2026 AI budget in four months. Leaders must now track real-time value and token efficiency.
For a brief window, companies had access to the most transformative technology in a generation at the cost of a streaming subscription. Tools like ChatGPT put AI within reach of anyone with a browser and time for experimentation, while GitHub Copilot came in at just $10 a month, with token costs remaining relatively low. In the beginning, experimentation felt cost-effective, easy and relatively low-risk.
But that era is ending, and the bill is coming due faster than a lot of enterprise leaders anticipated.
Tokenomics will be a hot topic of discussion on university campuses because, as Marc Watkins notes in this article, there is no realistic path forward to providing all students with access to advanced AI.
And now there is a third layer emerging. Institutions are waking up to a systems-level question they are likely not remotely prepared for. Who pays for AI? How are budgets managed when there are unclear token consumption pricing models? How is AI procured? Who decides what tools get used and by whom and who gets access and at what level?
That is the trap at the center of this conversation: everyone wants to hire someone with three years of experience, and almost no one wants to provide those three years.
And Ryan’s policy prescription is unusually concrete: pay employers to hire and train apprentices, following the countries that have scaled apprenticeship far faster than the U.S.; require colleges receiving federal student aid to provide relevant, paid, in-field work experience; and build a market of intermediaries that can make the whole thing operational.
Ryan’s view is that higher education remains critically important. But college without meaningful work experience may become a much worse bet, especially for students who cannot afford to guess wrong.
The unbundling of lawyer institutions — from jordanfurlong.substack.com by Jordan Furlong AI will strip law firms and law schools of their commodity features. Their future depends on whether they can rebuild around their highest-value functions and their trust-bearing core.
Two very different articles — one from a law professor, one from a legal technology analyst — crossed my desk last month. They each say something really important about law schools and law firms, respectively. But taken together, they point us towards what I think is an even more profound reality about lawyer institutions in the post-AI world.
At his eponymous Substack, Professor Michael Plaxton’s “To Our Next Law Dean” is really addressed to every dean of every law school, asking: After AI, how will you justify our existence? His concern is that AI is rapidly learning to perform many of the tasks law schools train students to do, and to deliver much of the general legal knowledge law schools provide at scale, including research, writing, analysis, and explanation.
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At Legal Technology Hub, Nikki Shaver’s “Law Firms Want to Change; They Just Can’t” asks whether law firms are capable of managing the transition to a post-AI legal market.
Law schools and law firms are the legal profession’s most important institutions. But they were built for a world in which legal intelligence was scarce, and that world is rapidly passing away.
The conversation focuses on how modern generative AI and Large Language Models (LLMs) act as a legal operating system to simplify contract reviews, document drafting, and client intake, while maintaining essential connections to human attorneys.
College admissions policy shapes K-12 practice. If colleges continue to privilege course sequences, seat time, and grades, high schools will remain constrained in how far they can move toward competency-based learning.
States and institutions already offer models for change. Wisconsin, Colorado, Indiana, and pilots like CUNY and Michigan Ross show that admissions can incorporate portfolios, demonstrations of learning, and durable skills.
If we could instead orient K-12 education around skill development and application rather than Carnegie Units and grades, we could create a new paradigm for where, when and how students demonstrate college and career readiness. Competency-based education moves schools and systems towards this desirable future that balances knowledge with skills.
Despite tremendous evidence of its potential, efforts to accelerate this shift have been stymied by the tyranny of college admissions requirements and processes. Parents, teachers, administrators and policymakers end up in a quandary. Anyone attempting to shift away from this traditional course sequence is criticized as trying to lock kids out of higher education and we snap back to the way things have always been done.
Higher education is under siege, with many students and parents balking at high costs. In a series of op-eds, university leaders lay out their efforts to keep college affordable. This is the first in the series.
For many people across the country, paying for college is the largest investment they will ever make. Increasingly, it’s one that feels out of reach.
Over the past two decades, tuition and fees at private, national universities have jumped by 112 percent; at some “elite” and highly selective schools the annual cost of attendance now approaches $100,000.
If higher education is to rebuild public trust, affordability can’t be an afterthought. It must be at the center of our strategic focus.
Most colleges and universities are not actually organized around learning. They’re organized around teaching, research productivity, rankings, revenue, and the preservation of institutional prestige. Students sense this, even when they can’t articulate it. The public senses it, too. Academic researchers themselves have been making this argument for decades, but it has rarely felt more urgent than it does right now.
The Yale report says, wisely, that “trust is earned by doing what you say you’re going to do.” Universities say they’re about learning. The way to rebuild trust is to actually mean it and to build institutions that prove it.
The Yale committee is right that trust must be rebuilt through action over messaging. The most fundamental action, and the one most often overlooked, is this: Get learning right.
Education AI budgets are holding steady or increasing: Wasabi found that 98% of education organizations expect AI infrastructure budgets to increase or remain steady, with 46% planning increases.
Storage costs are the top AI implementation challenge: Half of education respondents cited data storage issues, including storage and access costs, as the No. 1 challenge for AI projects.
Cloud security and ROI remain pressure points: Only 47% feel confident keeping data unaltered and operational after a cyberattack, 44% lost access to public cloud data after an attack, and 37% of AI projects currently show positive ROI.
From programmes to learning ecosystems These pressures point towards a broader redefinition of higher education. Rather than viewing education as a one-time experience culminating in a degree, universities increasingly need to see themselves as partners in professional development across an entire career.
This means moving from a model centred on programmes to one focused on learning ecosystems that allow individuals to enter, leave and re-engage with higher education as their needs evolve.
Business schools may be particularly well placed to lead this shift because of their close engagement with employers and their long tradition of educating professionals at different stages of their careers.
But success will depend on more than introducing new modules or certificates. Universities must confront a fundamental question. Are the systems, structures and cultures that define higher education capable of supporting genuinely flexible learning?
The sector has already embraced the language of lifelong learning – the next step is ensuring that universities themselves are built to deliver it.
From DSC: Long-time readers of this blog have seen this graphic of mine posted over the last 12+ years: .
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Also relevant/see:
What if the undergraduate journey were a four-year internship? — from timeshighereducation.com by Michelle Seref Treating work placements and co-curricular programmes as optional or supplementary misses deeper questions about whether traditional degrees prepare students for careers. Michelle Seref explains
Attending workshops or polishing a résumé in their final semester does not make students career-ready. They need to practise how to work – how to collaborate, navigate ambiguity, manage projects and apply knowledge in context – throughout their academic experience. The reality is that career readiness is not a co-curricular programme; it is an essential part of an integrated curriculum.
To be clear, employers do not expect classrooms to become training centres. What they are asking for – implicitly and explicitly – is graduates who can function in complex environments from day one. That means graduates who can work in teams, communicate professionally with stakeholders, adapt when plans change, apply theory to real constraints and learn continuously on the job.
These capabilities do not develop through passive learning. But experiential learning is often misunderstood as a single, high-impact activity: an internship, a capstone project or study abroad. In reality, its power comes from repetition and progression. One experience introduces exposure. A sequence of experiences builds competence.
We are proposing a paradigm shift: repositioning the undergraduate journey as a four-year professional internship rather than a continuation of the K-12 classroom environment.
. From DSC: The problem with this innovative idea is that faculty often are not out in the “real world.” The best chance higher ed has to deliver on this idea is via the adjunct faculty members out there. Often, they are the ones practicing what they are teaching. They are constantly pulse-checking — and actively involved with — their industries and have more up-to-date, practical knowledge.
But this is a problem for traditional institutions of higher education, which have treated their adjunct faculty members poorly through the years. Adjunct faculty members hardly make minimum wage, have no benefits, no retirement plans, etc. — plus they have little to no say in faculty senates.
We are the leading ____ in the Midwest/Southwest/Northwest/etc. (says who? Prove it.)
Our patients’ care is important to us (no, it’s not…you only care if your customers’ accounts are paid in full. If patients’ care were actually important, you would fix what’s broken.)
Your call is important to us (no, it’s actually not. If it were actually important to you, you would have more customer service reps working so that the wait times were either non-existent or much shorter. The truth is that you would rather cut costs/headcount and have your customers wait. Be truthful about it. Stop the B.S.)
A vast number of American corporations don’t actually care about their customers — their concern focuses solely on obtaining their customers’ money.
One of the ways this plays out is that they hide behind the labyrinths that are designed into the call pathways in their Voice Response Units (VRUs). VRUs have been abused. Corporations hide behind them. It’s hard to actually reach a person or hold a person accountable for something.
And now, with executives getting rid of entry-level jobs in customer service, they seek to cut costs further as they implement AI-based systems…which rarely give us what we’re looking for.
But even in written communications, times seem to be changing…and not for the better. I had a customer service rep write me a letter recently (regarding an incident with our daughter’s experience at a blood lab). But in the letter, she didn’t even provide her last name or a direct phone # in her correspondence. This would NEVER have happened in business letters back in the day — her last name would have been present, for sure — and likely a direct phone #. This isn’t her fault. It’s her leadership’s fault. BTW, the issue was passed along to the lab’s leadership…and she closed her ticket out. But there was no mention of an actual fix or resolution. Nice hand washing job, don’t you think?
Another case in point. This time, involving Apple. (BTW, I’ve been a long-time Apple fan…until the last several years. They have lost some of their focus on customer service.) I wanted to ask a question about a purchase that showed up on our Visa bill from apple.com/bill. Do you think I could find an 800# to talk with someone at Apple? Nope. You can try to find things via their online-based support systems, but often their documentation doesn’t match up with one’s devices. I couldn’t even use their chat feature — their systems told me that their chat feature wasn’t available (and it was 11:30am EST).
I’m sure if you thought about it, you could come up with your own recent examples of poor customer service experiences — or examples of companies that you did business with who didn’t deliver what they said they would deliver.
The issue runs deeper than we think. It actually has to do with whether people actually care about each other or not. And here in America, actually caring about others seems to be in short supply.
Putting college on the fast track — from hechingerreport.org by Jon Marcus As students grow impatient, colleges try three-year bachelor’s degrees
Some colleges and the accreditors and states that oversee them are adding and approving three-year bachelor’s degrees that require fewer credits than the traditional four-year kind.
Institutions facing enrollment declines hope the new three-year degrees will attract students unwilling to spend the usual amount of time and money that it takes to graduate. States need those graduates to fill jobs.
Nearly 60 universities and colleges are planning, considering or have already launched reduced-credit, three-year bachelor’s degrees in some disciplines. They’re calling them “applied” or “career-focused” bachelor’s degrees.
While earning bachelor’s degrees with fewer credits may appeal to some students, the idea is so new that there’s a key unanswered question: whether employers, graduate schools and licensing agencies will accept them.
From DSC: Given the often high price of obtaining a degree these days…whether it’s a 4-year program or a 3-year program, the key is whether a student can get a good job coming out of that program. I think the required time doesn’t help as much as making the necessary changes to offer more responsive curricula, relevant programs, and real-world learning experiences (including apprenticeships and internships). I appreciate the experiment to lower the overall costs, but like so many other “innovations,” it’s playing at the fringes. It’s really the same old, same old — just on a shorter time frame.
At current prices, families are FORCED to consider employment prospects. They are demanding a ROI, because they have to.
I was at a meeting earlier this year with other parents and family members who were interested in a particular program at a Michigan-based university. One set of parents really wanted to know if their student would be getting a good job coming out of the program. They didn’t want to take a second mortgage out if the investment wasn’t going to pay off.
We welcome back Sabastian Niles, President and Chief Legal Officer at Salesforce, to discuss his recent “Open Letter to Law Firms.” As the legal industry hits a critical inflection point, Sabastian argues that the era of “AI theater” and small-scale pilots is over.
The conversation dives deep into the Innovator’s Dilemma facing law firms, the shift toward agentic AI, and how firms must reimagine their business models to remain competitive. Sabastian highlights that legal professionals are uniquely positioned to lead the charge in trusted AI transformation, provided they embrace transparency, data integration, and shared efficiency gains with their clients.
Three Realities for the Modern Legal Firm To lead in this landscape, there are three realities every firm leader must understand:
Competition is intensifying: …
Client expectations will reshape the market: Clients are no longer asking whether firms use AI. Rather, they’re expecting to see the benefits of that transformation passed directly to them. They expect more for less but are not simply seeking lower costs – they want more insight, more speed, and more value for every dollar of their budget. And law firms, which operate at the center of data, ethics, and risk, have outsized influence over the structure and deployment of trusted AI across all industries. Some clients, like Salesforce, are even creating agentic tools to improve the law firm’s experience when working with clients. …
Unified client intelligence is at the heart of legal strategy: …
Are AI First Firms a Threat To Biglaw? — from legallydisrupted.com by Zach Abramowitz and Logan Brown Episode 49 features AI first law firm founder Logan Brown
Is Big Law about to become the Yellow Pages? Hey, I didn’t say it, but ex-Cooley lawyer turned AI first law firm Logan Brown did. The question is do I agree?
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Instead of the traditional billable hour, they charge flat fees like $100 for a contract review or $50 to ask a lawyer a quick question via chat. She’s already got over 40 attorneys on the platform. And in a departure from the traditional partnership track, she actually chose to raise venture capital so she could scale the firm like a tech company and tackle the access-to-justice gap.
From DSC: LOVE to hear anything and everything regarding efforts to address the access-to-justice gap here in the United States!!! Along these lines, also see:
“Legal services are out of reach for many people and small businesses, and the gap is widening,” Anthropic said in its announcement. “We’re working with the Free Law Project, Justice Technology Association and other legal aid and public service organizations to help make legal services more affordable and available.”
That makes this the first time that a leading AI company is explicitly naming access to justice as a foundational pillar, JTA says, with Anthropic positioning the initiative as “investing in the premise that AI should expand access to justice — making legal services more affordable and available.”
What AI hallucinations in law actually are
In a legal context, AI hallucinations are one of two things. They’re either citations to cases or statutes that don’t exist, or citations to real authorities for propositions those authorities don’t actually support.
The first kind is the one making headlines. A lawyer or pro se litigant uses a general-purpose chatbot like ChatGPT, Claude, Gemini, Copilot, or Grok to help draft a brief. The model, predicting the statistically likely next word, decides a citation belongs in a particular spot, and produces one. The reporter might be real. The volume number might fall within the right range. The Bluebook formatting is often better than what most associates produce. The case itself just doesn’t exist.
The second kind is older than AI. Lawyers have always occasionally cited a case for a proposition that the case doesn’t stand for. AI has made this kind of error easier to commit and easier to catch.
A dangerous mind — from by Jordan Furlong Generative AI is a tireless genius with no boundaries. Use it carelessly, and it can usurp your voice, overwrite your ideas, and steal your originality. Make sure you safeguard your capacity to think.
Don’t let the genius do the hard work for you. The more incisive and unique your own thinking — the more you battle and struggle and eventually succeed in getting your ideas and insights out — the more you can benefit from the AI’s complementary improvements. The great irony of Gen AI is that it actually makes your own cognitive processes your most valuable asset.
So safeguard your mind. Defend your right to think as only you can. And if you don’t want AI to replace you, then don’t send it a written invitation.
The pilot phase is over. After two years of experimentation for legal departments, 2026 will be the year AI moves from “interesting tool” to “operational infrastructure,” whether they’re ready or not. We surveyed predictions from Gartner, Forrester, McKinsey, and other leading legal tech analysts to identify where expert consensus is forming. The implications for AI governance, outside counsel relationships, and regulatory compliance are significant.
The TalentLMS 2026 Annual L&D Benchmark Report — from talentlms.com From year-over-year training benchmarks to learner–leader gaps, see the data that defines the new era of learning. To turn insight into action, the report lays out 10 evidence-backed interventions to hardwire development. Plus, lift the lid on Learning Debt: What it is and how to spot it.
Executive summary
The skills economy is being rewritten in real time. AI is reshaping what people need to know, do, and deliver, faster than organizational structures can adapt. The result is a workplace caught between acceleration and inertia. Companies are racing to reskill for an AI-driven future while relying on structures built for yesterday’s world.
This TalentLMS 2026 L&D Benchmark Report captures that inflection point. Based on data collected through 2025, and compared with earlier findings from 2022 to 2024, it explores how learning is evolving and what’s holding it back.
Our research integrates two vantage points: HR leaders overseeing learning initiatives and employees receiving formal training. Together, they offer a dual perspective on how learning is managed and how it’s experienced.
The analysis also draws on insights from external research and leading L&D practitioners, anchoring the report in both evidence and practice.
Combined, the findings point to a structural fault line: Learning is expanding in scope but contracting in space. Organizations are multiplying programs, tools, and ambitions, yet the conditions for learning — time, focus, and cognitive bandwidth — keep shrinking.
The data from this report underscores this critical conflict: According to half of the surveyed employees and learning leaders, high workloads leave little room for training, even when it’s needed.
Employees work inside a permanent sprint, where attention is fragmented and reflection is sidelined. The space for learning is collapsing under the weight of doing. Sixty-five percent of employees say performance expectations have risen this year, yet lack of time remains the biggest barrier to learning.
The numbers confirm what employees and learning leaders both feel: Technology can advance overnight. But people and cultures can’t.
