Episode 14 dives into the blurred line between transparency and theater.

From MrBeast’s evolving global puzzle to Amazon backing away from surveillance backlash, from messy Epstein file disclosures to AI systems that simulate entire companies — this week feels like a preview of where culture and technology are heading.

Kali unpacks the political optics — shutdowns, oversight battles, public trust.

Techie breaks down the tech most people aren’t hearing about — AI teams that disagree, ghost accounts that post after death, and the systems quietly expanding behind the scenes.

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Kali and Techie start with the Super Bowl — but quickly move far beyond football.

They break down the cultural reaction to Bad Bunny’s halftime performance, the “God Bless America” moment that sparked debate, and a surprising tech theory: Did Apple quietly align the show with its live-translation AirPods feature?

From there, the episode shifts into bigger conversations:

• MrBeast and Rainbolt turning the Super Bowl into million-dollar social media scavenger hunts.

• Jeff Bezos cutting Washington Post staff and what it signals about the future of journalism

• ICE recruitment bonus complaints

• Universal Basic Income and the shrinking gig economy

• A controversial presidential repost involving Barack and Michelle Obama

• Newly surfaced Epstein document timeline questions

• And one of the wildest stories of the week: RentHuman.ai — where AI agents can hire humans to complete real-world tasks

This episode captures what it feels like to live inside nonstop headlines, collapsing trust, and a rapidly shifting tech economy.

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Kali graduates from the water cooler and joins Techie at the mic for a deeper conversation about who gets to be considered “press” in 2026. They start with Don Lemon’s arrest after livestreaming a disrupted church service and ask the uncomfortable question: if a legacy journalist can get charged, what does that mean for creators, podcasters, and citizens recording history in real time? 

From there, Kali brings in the Grammys moment—including Trevor Noah’s jokes and Trump’s public threat to sue—as another example of how comedy, politics, and media collide in the same feed. They also touch on how big institutions are shifting platforms (including the Grammys’ broadcast changes), and what that says about where culture is headed.

Techie closes with a practical tech-policy ripple: Los Angeles’ move toward refillable/recyclable printer supplies and what it could mean for consumers and the “cheap printer” economy. Finally, Kali drops a fast “hot off the press” update on the Epstein investigation and who may be pulled into testimony next. 

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In this episode of Logging In, Techie and Luna react to Tyler Oliveira’s viral video portraying a Jewish community through a sensational and confrontational lens. Rather than focusing on clicks or outrage, they slow the conversation down to examine what happens when influencer-driven “investigative journalism” strips away context, history, and responsibility.

They break down who Tyler Oliveira is, how his rise through MrBeast’s platform shaped his audience, and why framing matters when covering insular or misunderstood communities. Drawing from personal experience, Techie and Luna discuss cultural misunderstanding, selective editing, reaction-stream amplification, and how narratives can harden into stereotypes when nuance is lost.

The episode also explores why this content spreads so quickly online, how livestream reactions often reinforce misinformation, and why sensational framing can contribute to real-world harm — especially amid rising antisemitism.

Midway through, Kali delivers the Water Cooler, covering major developments in politics, protests, healthcare policy, science, and sports, highlighting the overwhelming pace of the modern news cycle.

This episode is a call for accountability — asking who gets to tell these stories, who profits from them, and what responsibility comes with turning real communities into viral content.

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In Episode 010 of Logging In, Techie and Luna dig into Apple’s evolving relationship with creators — and what happens when professional tools, subscriptions, and AI begin reshaping how creative work gets done.

The conversation starts with Apple’s new creator-focused offerings and recurring subscription model, raising familiar concerns about affordability, access, and whether these tools genuinely empower artists or quietly gatekeep creativity. From there, the discussion expands to Google’s Gemini AI and its ability to pull from personal data across apps, prompting deeper questions about privacy, consent, and how much thinking people are willing to outsource.

Midway through the episode, Kali delivers the Water Cooler, reporting on a wide range of current events including political pressure on the Federal Reserve, international tensions involving Greenland, a major nurses’ strike in New York, developments in medical and fertility research, childcare funding disputes, corporate conflicts over energy investments, consumer lawsuits, and a major NFL playoff comeback.

As the episode unfolds, Techie and Luna connect technology’s convenience culture to creativity, relationships, and emotional labor — asking whether efficiency is starting to replace imagination, and what’s lost when tools begin doing the thinking for us.

A thoughtful look at where modern tech is heading — and the human cost of making everything easier.

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In Episode 009 of Logging In, Techie and Luna kick off the year with CES season — and the headline they didn’t expect: LEGO stepping on stage to announce a new “smart brick.” It’s screen-free and powered by proximity tech, but it still raises a big question: does adding lights and sounds make creativity better… or does it train kids to expect the toy to do the imagining for them?

From there, the conversation shifts to a very different CES surprise: Dell publicly acknowledging that consumers are confused by AI marketing — and in many cases simply don’t care. As “AI everything” collides with real life, Techie and Luna talk about who actually benefits from AI features, who feels overwhelmed by them, and whether a backlash is brewing for simpler, quieter tech.

A playful (and slightly exhausted) check-in on where tech is headed — and whether we’re building tools that help humans, or replace them.

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What are we actually learning when stories go viral — and who decides what counts as “evidence”?

In Episode 008 of Logging In, Techie and Luna unpack a viral video by content creator Nick Shirley, who accused Somali-owned daycare centers in Minnesota of fraud, using a misspelled word on a childcare sign as a key signal of alleged illegitimacy. Rather than adjudicating guilt or innocence, the episode focuses on something more fundamental: how people are learning to interpret information online.

The conversation explores how algorithms reward confidence over context, how visual “gotchas” like spelling errors become stand-ins for truth, and how audiences are being trained — often unintentionally — to draw sweeping conclusions from incomplete data. From YouTube journalism and crowd-sourced investigations to the real-world harm caused when virality outpaces verification, the episode asks whether the internet is teaching people how to think critically, or simply how to react quickly.

At its core, this episode is about learning: what we absorb, what we miss, and how easily the tools meant to inform us can end up distorting reality instead.

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Technology often presents itself as helpful — crowdsourcing answers, finding discounts, filling in gaps where systems fall short. But what happens when that help causes harm?

In Episode 007 of Logging In, Techie and Luna unpack two very different stories with the same underlying question. First, they reflect on how Reddit’s role in investigations has changed over time, comparing the Boston Marathon bombing aftermath with a recent local case in Rhode Island at Brown University and asking whether online crowds have actually learned from past mistakes — or if the risks have simply shifted.

In the second half, the conversation turns to the Honey browser extension and growing concerns about how coupon tools operate behind the scenes. From affiliate code overrides to data collection and lawsuits involving PayPal, the episode explores how “saving money” online can quietly impact creators, businesses, and users alike.

Across both topics, the episode asks a bigger question: when technology steps in to help, who is it really helping — and who pays the price?

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Some weeks don’t leave much room for headlines, hot takes, or polished conversations.

In Episode 006 of Logging In, Techie and Luna take a quieter approach, processing local events and the emotional weight that comes with living online during moments of real-world violence. Rather than diving into a specific tech topic, the episode becomes a check-in — about how constant notifications, breaking news, and algorithm-driven feeds shape the way people absorb fear, grief, and uncertainty.

Recorded in the aftermath of a shooting close to home, the conversation reflects on how technology changes the pace of processing hard events, how information overload can blur reality, and why sometimes the most honest response is simply slowing down. This episode isn’t about solutions — it’s about acknowledging where things are, and making space for being human in public.

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You open the same shopping app, add the same items, and somehow end up with a different total than someone else.

In Episode 005 of Logging In, Techie and Luna break down how shopping apps quietly personalize prices, fees, and promotions based on who you are, where you live, and what the algorithms think you’ll tolerate. From Instacart and social-driven pricing to loyalty programs, surge fees, and discounts that aren’t really discounts, the episode exposes how modern commerce tests consumers individually instead of treating everyone the same.

The conversation widens to the human cost of invisible pricing systems: gig workers squeezed from both sides, shoppers unknowingly paying premiums, and the slow disappearance of transparency in everyday transactions. When prices depend on profiles instead of products, what does “fair” even mean?

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