✅ Inside this issue:

• 7 ways to check AI is actually helping your org’s productivity

• Why Thania thinks your next badge should be displayed proudly at your desk

• Could AI give rural students access to more opportunities?

INTERESTING READS

🤝 Networking is a skill, so why aren’t we teaching it?

🤖 CEOs fear underinvesting in AI, but they may be investing wrong.

💸 The job hopping pay bump isn’t what it used to be.

🏠 New to managing remotely? Start with these leadership tips.

PRODUCTIVITY

7 ways to ensure AI is actually helping your company

AI is supposed to save us time and money. So why are companies blowing through AI budgets while employees spend 20 minutes arguing with a chatbot about something they could have done themselves in five?

That gap is getting harder to ignore. Forbes recently reported that only one in five AI investments delivers measurable ROI, while Inc. reported that just 7% of executives in one survey said they were seeing ROI from AI.

That tracks with MIT's finding that 95% of organizations have seen no measurable return on their generative AI spending, and with a large-scale study of 7,000 workplaces that found AI's productivity impact has so far been minimal outside a few obvious use cases.

AI can make work genuinely better when it's used well. Getting there takes more than a mandate to "use more AI." Here are seven ways to make sure it is actually helping.

1. Pick the problem before the tool

Do not start with, "We need an AI agent." Start with, "What problem are we trying to solve?" Maybe onboarding is slow. Maybe employees waste hours searching for information. Maybe your team manually processes hundreds of documents.

Define the pain point first, then decide whether AI actually belongs there. This is exactly what separates companies that see real ROI from those that don't.

2. Automate the stupid stuff first

Start with repetitive, low-risk work: cleaning data, formatting spreadsheets, categorizing information, drafting recurring reports, or moving information between systems.

An autonomous AI agent reinventing your company sounds impressive but usually isn't the win. What actually helps is making the annoying Tuesday-afternoon task disappear.

3. Give your team a shared brain

One employee has a great prompt. Another built a useful workflow. Someone else discovered the AI makes the same dumb mistake every time. And nobody shares it.

Create one place for prompts, workflows, reference documents, lessons learned, and examples of good outputs, so employees stop reinventing AI from scratch every time they sit down.

If you want a model for what this can look like, this guide walks through building a shared "second brain" knowledge base powered by Claude, where information gets captured once and stays searchable for the whole team.

4. Train people on the workflow, not just the tool

Teaching employees how to prompt is not enough. They also need to know when to use AI, how to evaluate the output, and when to set it aside and think for themselves, because otherwise AI can quietly replace critical thinking rather than support it.

A good workflow is simple: understand the problem, use AI for a specific task, review the output, verify what matters, then make the final judgment yourself. What matters most in the end is whether people are thinking more clearly with AI's help, not whether they've mastered a clever prompt.

5. Test before you unleash it

Please do not buy an AI tool on Monday and roll it out to 500 people on Tuesday.

Start with a small group who actually does the work. Ask what saves time, what creates more work, and where the system fails. A pilot should answer one question: does this make the work better?

6. Give AI boundaries

AI is good at producing an answer, but that doesn't mean it should make every decision. Think of creating “bans” for your AI. Set clear rules around hiring, firing, promotions, legal issues, employee data, financial decisions, discrimination, and other high-risk work. "The AI said so" will not be especially comforting when Legal calls.

7. Know when to stop

AI can create its own productivity trap: spending longer automating a task than doing it yourself. If something takes five minutes manually and you have spent 10 minutes troubleshooting a prompt, congratulations: your productivity tool just cost you five minutes.

Unless you are building something reusable or deliberately practicing, know when to close the chatbot and finish the darn thing. Left unchecked, this pattern tends to expand workloads rather than shrink them.

CULTURE

Is pop culture asking for physical GirlScout-esque badges? What if your digital credential came with something you could actually hold?

The other day I stumbled across this therapist I follow on Instagram who shares her dating life. She'd taken a break from her influencer journey to heal and turn her attention to a side project.

She'd started a company called Joy Finders, where adults complete challenges and get real, embroidered badges for doing them. They organize challenges into four categories, Create, Restore, Explore, and Share, and you earn beautifully designed little badges for things like cooking something new, rediscovering yourself, or exploring your city.

Kind of like recognition for adulting. Their tagline: "Life doesn't come with gold stars. So we made them."

And I freaking love that.

The signal underneath the cute idea

Outside of it being a very cute idea, there's something bigger happening here: badges are making their way into pop culture.

I didn't find it at a workforce conference or in an ed-tech pitch deck. I found it on Instagram, posted by an influencer, sitting in my feed between skincare routines and outfit checks.

When badges pop up mainstream, that's a tell.

Culture doesn't pick things up unless people already want them. I saw this and went: “oh my god, are influencers going to make badges trendy for us?!”

People want something to show for what they've done

We all like being recognized for what we do, and I think this hits especially hard for women, given how much invisible labor and "second shift" work we do without ever getting real recognition for it.

Joy Finders is essentially telling an untapped, highly skilled audience: “I see you did something. It mattered. Here's something to mark it.”

Joy Finders screams to me that they understand the psychology of recognition and the right audience to receive it.

It brought to life the question for me: What if universities and employers paired digital credentials with tangible ones?

» Continue reading the article »

BY THE NUMBERS

Experienced workers are applying for entry-level jobs

49% of applications from job seekers with 10+ years of work experience went to entry-level roles in May 2026. Indeed’s data suggests “entry-level” increasingly describes the job, not necessarily the experience level of the person applying for it.

Source: Indeed, 2026

KNOWLEDGE

What to read, watch, and listen to this weekend

📚Read: AI in Rural Education: Bridging the Opportunity Gap by edCircuit

Rural schools have long faced teacher shortages, limited course offerings, and fewer pathways to specialized learning. This piece explores where AI could expand what’s available—from personalized instruction to career exploration—while raising an important question for the skills economy: can new technology actually help geography become less of a barrier to opportunity?

📺 Watch: Crip Camp by Jim LeBrecht and Nicole Newnham

This Oscar-nominated documentary starts at a summer camp for teens with disabilities and follows campers who went on to help shape the disability rights movement in America. It’s a powerful watch on what happens when people who have been excluded from systems organize to change them—and a good reminder that accessibility has a history we should know.

🎧 Listen: How Many Jobs Are Left Out There to Cut? by How Many Works

After years of layoffs, efficiency pushes, and AI-fueled workforce changes, how much leaner can companies actually get? This episode digs into what the latest job-cutting cycle tells us about where employers are headed and what it could mean for workers trying to read the labor market.

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