⬇️ Inside this issue:

• Robert’s idea for how to build an LER infrastructure in the US

• Odeta shares how to upskill in the age of AI

• Plus read til’ the end to see our fun meme

INTERESTING READS

🏗️ Newsom’s new plan aims to create high-paying careers for Californians, degree or not.

🌀 Get a clear look at how blockchain tech powers employee verification.

‼️ There’s an accountant shortage and they’re now being called the new software engineers.

DIGITAL BADGES

How Do We Build an Infrastructure That Makes Credentials Usable?

Here’s the inconvenient truth: In the U.S., credentials often don’t work the way they should.

At Microcredential Multiverse, we talk with hundreds of organizations every month, and the same question keeps coming up:

A Broken System with No Common Language

Right now, our skills ecosystem is fragmented. More commonly, this phenomenon is called “The Skills Emergency.”

In the United States, every state, platform, and provider seems to have its own definitions, standards, and tech stacks to address this global challenge. Alongside the universal call to action for traditional learning providers—institutions, professional associations, and non-traditional PD providers—large companies like Google, IBM, Salesforce, and Walmart have addressed their own internal skills gaps by creating credentials aligned with their specific needs. Many of these credentials have delivered measurable value and career outcomes for learners and workers.

Additionally, universities, community colleges, technical schools, K–12 districts, bootcamps, accelerator providers, and state agencies have started designing solutions in strategic sectors of the local, regional, and national economy.

But these are all supply-side solutions—and they don’t always meet that supply with clear, consistent demand from employers or other consumers and recognizers of these credentials.

Going back to the skills mismatch: if employers can’t understand the outcomes of these programs—the micro-credentials and learning pathways—or don’t know how to use them, there’s no clear value proposition for learners to earn them.

Learning experience providers, learners, and employers are all sending strong signals—but without a shared way to interpret them, they end up isolated, misaligned, and stuck. What we need is a Currency-Generating Rosetta Stone for Skills: a common translation layer that allows each stakeholder to understand, trust, and respond to the signals coming from the others.

The Solution Starts with Currency

For the last decade, I’ve used a term that’s now gaining traction as supply-side capacity grows in the U.S.—credential currency.

Credential currency is evidence of demonstrated (and validated) skills and competencies that is portable, verifiable, and valuable. Not participation trophies—real credentials that learners can leverage in the labor market to unlock measurable outcomes: jobs, apprenticeships, promotions, access to degree programs, and more.

That means building a system where skills are:

• Useful: Aligned to in-demand roles

  → For example, the Fast Track Manufacturing Pathway hosted by Savannah helps transitioning service members access well-paying, high-skill jobs in civilian companies.

• Usable: Recognized and shareable across platforms

  → For example, nursing and healthcare pathways developed by Alamo Colleges support learning-to-career pathways.

• Used: Proven to lead to jobs, wages, and upward mobility

  → For example, micro-credentials offered by BCSI helped Oscar Ramirez land a role as a Quality Control Microbiology Technician at Millipore Sigma.

What Makes Credential Currency Flow

Countries getting this right—like New Zealand and those in the EU—have built intentional infrastructures. They’ve:

• Integrated micro-credentials into national education frameworks and governance

• Established portable digital wallets with on-demand, verifiable, skills-aligned records

• Created cross-border recognition systems to support transferability and recognition of prior learning

They’ve built trust, consistency, and proof into the system. And it’s working.

What an Ideal Infrastructure Looks Like in the United States

To achieve this vision of a unified skills ecosystem, the U.S. must shift from fragmented innovation to connected systems. That requires:

• Common frameworks with shared definitions of skills

• Rich metadata built on open standards, allowing humans and machines to read/write records across ecosystems

• Learning pathways that show how short-term credentials stack into degrees and careers

• Digital wallets that store, secure, and share credentials while honoring self-sovereign identity

• Verification infrastructure to build trust, reduce friction, and eliminate fraud

• Public–private partnerships to align training (supply) with labor market needs (demand)

The Call to Action: What the Wild West Needs to Grow Up

We’re not short on ideas or tech. We’re short on coordination and collaboration.

We need shared policy, strategy, and governance to drive interoperability—employers who signal which credentials they trust, and learning providers who embed transparency and market value into everything they offer.

I happen to appreciate that we have 50 unique laboratories serving diverse communities, and I don’t believe the answer is more standardization. What we need is a well-understood, common exchange rate—a shared language that allows a credential from one state or system to mean something in another.

Because the future of work isn’t about where you learned, how long it took, or even how you did it—it’s about what you can do with the verifiable, rigorously assessed skills and competencies you’ve acquired.

The systems we build today will determine who gets seen, hired, and elevated tomorrow.

Together, let’s build a global skills infrastructure that works.

And when we get it right? Learners and workers won’t apply to jobs—the jobs will apply to them.

JOB SKILLS

Why I’m upskilling in the age of AI (and you should too)

Growing up in Lithuania in the 1990s, I vividly remember scarcity. Bananas were a luxury, and you stood in line for bread. That environment built a kind of resourcefulness and drive that has shaped how I approach change today. I call it the hunger effect. When you’ve experienced constraint, you learn to move fast and make things happen.

That same hunger pushes me to keep learning, even as a founder, even in AI. So trust me when I say I get how overwhelming it can feel to add "learn AI" to your already packed schedule.

Would I hire me in 2025?

After seeing how quickly AI is transforming the workforce, I started asking myself that question. It’s not just about flashy tools. It’s about staying relevant. And if we’re being honest, the pace of change is relentless. AI isn’t coming for jobs. It’s already reshaping how work gets done.

I’m not an insider in the LER world. Honestly, I only recently learned what a Learning and Employment Record even was. But here’s the thing. No matter what you call it or how it’s delivered, one truth stands: those who keep upskilling, the lifelong learners, will always find themselves (and their skills) in demand.

Skills-based hiring is gaining momentum. In a skills-based economy, what you can do matters more than degrees or tenure. According to LinkedIn’s 2025 Skills-Based Hiring report, shifting to a skills-first approach can expand the talent pool up to 15.9x in the U.S. alone. That means employers are increasingly prioritizing capabilities over credentials.

How I’m doing it without burning out

I’m not just upskilling for the sake of it. I’m doing it to stay sharp, adaptable, and future-ready in a world that’s changing by the minute. Whether you’re a founder, a team lead, or just trying to keep your footing in the workplace, AI isn’t a far-off threat or a shiny new toy.

It’s a reality. The faster we get comfortable using it, the better equipped we’ll be.

You don’t need to become an AI engineer overnight. But you do need to experiment, explore, and build a toolkit that lets you work smarter, not harder. In a skills-based economy, the people who stay curious and take action will always have the edge.

TECHNOLOGY

Data is the backbone of your skills ecosystem, guard it like it matters.

Digital credentials, LER platforms, and skills wallets are reshaping how we verify learning and employment. But they all have one thing in common: sensitive user data and PII that must be protected.

Academic transcripts. Personally Identifiable Information (PII). Employment records.

If you’re building—or funding—the future of credentialing, your cloud security strategy can’t be an afterthought.

That’s where Wiz comes in.

✅ Get full visibility into your cloud environment so you know exactly where vulnerabilities live

✅ Find and fix risks before you launch—not after an incident forces your hand

✅ Maintain trust with learners, funders, and partners through proactive, scalable protection

✅ Stay compliant with education data privacy standards and cloud security best practices

Wiz is already trusted by the world’s fastest-growing platforms—and now it’s ready to support your emerging or expanding LER ecosystem.

👉 Explore how Wiz can help secure your credentialing platform before trust is compromised.

VOCABULARY

Credit mobility

noun

The ability to transfer academic credits and learning achievements across institutions, systems, or states—so learners don’t have to start over when they move, switch schools, or change programs. Credit mobility supports educational continuity, reduces time and cost, and helps build equitable pathways.

🧐 Thania’s translation: “It’s like when you move cities, and your ClassPass credits and information work at any of their gyms and fitness partners. You don’t have to worry about anything, it goes with you.”

☕ Robert’s take: “Credit mobility is a structural equity issue. When credits don’t transfer, learners lose time, money, and motivation. Enabling mobility—especially across state lines and systems—is essential for access, efficiency, and completion.”

Improve your skill-based hiring vocabulary at Learn & Work Ecosystem Library.  Search by topic | glossary.

JOB OPPORTUNITIES

🔔 Open positions

• Tribal STAR Workforce Development Specialist @ SDSU - San Diego, CA

• Senior Director, Career and Workforce Readiness @ College Board - Remote

• Career Coordinator, Career Services @ Southeastern Oklahoma State University - Durant, OK

• Principal Product Marketing Manager, L&B @ Skillsoft - Remote

• Public Sector Growth Lead @ Code for America - San Francisco, CA

FUN’SIES

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