Latest Thoughts
-
š» What Happens When Google Search Traffic Falls to Zero?
Host Jason Michael Perry sits down with Andy Janaitis, founder of PPC Pitbulls, to unpack what happens when Google search traffic falls to zero ā and how businesses can survive the shift. As search engines turn into answer engines and clicks give way to conversations, Jason and Andy explore how SEO, PPC, and digital advertising […]
-
š» Whatās Really New with OpenAI?
Host Jason Michael Perry sits down with Ben Slavin, an AI entrepreneur and researcher, to unpack what OpenAIās DevDay 2025 conference really means. From Sora 2, the next-generation AI video tool, to ChatGPT 5, and connectors, they explore how OpenAI is shifting from product to platform and what that means for developers, creators, and the […]
-
š» What is a Photo?
Host Jason Michael Perry sits down with Joel Benge, a communications strategist and author, to ask what a photo even means in an age where AI can rewrite reality. From fake principal voicemails to AI-generated films, Perry and Benge explore how synthetic media is reshaping trust and what that means for security, family, and everyday […]
-
š§ Why Workslop Misses the Point on AI at Work
AI-generated workslop might be an issue, but the real performance gains are being drastically understated.
AI is the great equalizer. It takes F or D level work and pushes it up to a C or even B. For recruiters and managers, that changes the signals they used to rely on. Spelling mistakes, awkward phrasing, or obvious gaps in formatting once made it easy to weed out weak candidates. AI erases those clues. Just like phishing training that teaches us to look for typos and clunky wording, the cues weāve built BS detectors around no longer apply. Slop is moving further up the pipeline than it once did.
But the productivity gains from AI are still understated. As Ethan Mollick has pointed out, there is a growing stigma around admitting how much experts use AI. Spot an unusual phrasing or a certain punctuation mark and some people instantly dismiss the work as machine-made. That pushes AI use underground. People draft in personal tools or resort to shadow IT so they can get the benefit without the stigma. The final product looks like a polished draft, but few admit how much of it came from working alongside AI.
The reality is more people are using AI than want to own it. These tools do not replace critical thinking or fill in gaps of real experience. They are exponentially more valuable in the hands of someone who knows their domain than someone who does not. Training people to use AI to expand their value, not as a magical crutch, is the difference between slop and real output.
-
š§ H-1B, Remote Work, and the RTO Paradox
Reading the news about a $100K fee on H-1B visas, I kept seeing the same question pop up: why hire someone on an H-1B at all instead of just building an offshore team?
Early in my career, the answer was obvious: H-1B hires let you expand the expertise of your local team and grow culture right where you sit. Outsourcing chips away at that. Building a team in another country means learning a new market, a new culture, and a whole new operating model.
For decades, offices enforced geographic restrictions. If you wanted to compete for the best jobs, you moved to the meccas like San Francisco or New York City. For some roles, that may never change. But when we push back on RTO, we also remove those restrictions. Suddenly, the best person might live anywhere, as long as they can work golden hours or travel when needed.
But hereās the twist: remote work changed everything.
I run my own business now, and while it is nice when people are local, it does not stop me from working with team members in different states or countries. I am usually looking for the best person I can afford for the role. Local is lagniappe (a little something extra), not the requirement.
That is where RTO gets interesting. For some companies and roles, being in-person may feel safer, or may even reduce the competition for jobs. For others, it might limit access to talent in ways that hurt more than it helps.
So maybe the real question is not whether RTO is good or bad, but whether the geographic restrictions it enforces are worth the tradeoff.
-
Savings Unlock Calculator
The Savings Unlock Calculator looks at AI through a different lens: time, efficiency, and āsalary not spent.ā It shows how much capacity your team can unlock without adding headcount by freeing up FTEs, saving hours, and raising efficiency. The point isnāt just cost-cutting, itās about finding new room to grow with the team you already have. Try it out!
-
Growth Unlock Calculator
I built this Growth Unlock Calculator to test how AI-driven productivity gains could flow directly into top-line revenue. By plugging in team size, average revenue per employee, and adoption rates, you can see how different impact levels translate into potential growth. Try it out!
-
š§ AI Is Making Questionable Food Look Delicious
Some of the best AI use cases arenāt flashy, theyāre just quietly helpful.
If youāve ever ordered from DoorDash or Uber Eats, youāve probably seen some truly questionable food photos. Now, Uberās using AI to re-plate dishes, enhance low-quality images, and summarize reviews into clear, useful descriptions.
-
š§ AI Pricing Isnāt the Problem
AI use cases arenāt always about novelty. Sometimes the power is simple: process more information, make better decisions, and act immediately. Thatās exactly what sparked controversy last week when Delta announced plans to use AI to personalize airfare pricing. After public pushback, Delta clarified that it was using a partner to dynamically adjust prices based on demand and competitors, something airlines have done for decades.
Whatās changed is the speed.
Before AI, we saw the same pattern in retail stores like Best Buy and Walmart rolling out e-ink price labels to make price changes cheaper, faster, and less error-prone. What used to take days now takes minutes. These systems werenāt about AI. They were about enabling action at scale.
Today, companies like are building AI-powered pricing systems that go even further, integrating with ERP and supplier data to adjust prices in real time. Working with groups like PerryLabs, theyāre pushing updates across hundreds of products or stores multiple times a day. When margins shift due to something like a tariff change or supplier shortage, the system responds. Fast. Strategically. Without waiting for a human in the loop.
Thatās the pattern: AI isnāt changing how business is done or how pricing has worked for centuries, itās just enabling those decisions to happen faster than ever before.
-
š§ Weāre Still in the AOL Days of AI
AOL launched in 1983, Amazon didnāt show up until a decade later, and Google nearly two decades. Thatās the kind of timeline weāre on with AI, not just early, but early enough that we still havenāt figured out how to use it at work.
According to a new AP poll,Ā 60% of U.S. adults have used AI to search for information, butĀ only 37% have used it at work. The gap isnāt about capability, itās about confusion. Companies are rolling out vague governance policies that say, ādonāt use ChatGPT with company data,ā but then fail to offer secure, internal tools connected to their systems. The result? No context, no value, and no adoption.
When my team at PerryLabs talks with companies, we see it again and again: well-meaning governance that blocks data access, without a real plan to replace it. That creates hallucinations, frustration, and a quiet surge in shadow IT as employees turn to whatever tools they can find.Ā It’s like choosing not to give your team a performance boost, and acting surprised when you fall behind.
