We're getting more say in our own tools.

GitHub just shipped a major upgrade to Copilot's brain — and it's one of the more useful changes they've made in a while. Instead of just throwing more tokens at every problem, the model now gets better at figuring out what actually matters in your codebase before it starts writing.

The new context handling means Copilot looks at your repo more carefully before responding. It pulls in the relevant files, picks the right model for the job, and routes each request accordingly. You'll notice it especially when asking about something specific — like a function in a particular module — instead of getting a generic answer that could apply anywhere.

This is the kind of update that doesn't get much press but quietly changes how people work. If you're writing code for a living — especially if you're juggling multiple projects or working in a team — it saves you the step of explaining yourself every time.

Why this matters for us: Less back-and-forth with the tool means less time explaining your code and more time actually writing it — whether you're solo or building alongside the primos at the side hustle.

Paul Meade, the Apple vice president in charge of the Vision Pro headset, is reportedly leaving the company to join OpenAI's hardware team.

Meade has been the public face of Apple's spatial computing effort since the headset launched. He's been pushing the Vision Pro as a serious computing platform — positioning it for developers, creators, and enterprise users, not just as a consumer gadget.

OpenAI's hardware push is part of a broader push by AI companies to control the devices where their models live. ChatGPT's already on phones and tablets. The Vision Pro could be the next frontier — a head-mounted computer where AI agents can actually see and interact with the world. Meade's departure signals that OpenAI sees spatial computing as the next battleground for AI, not just an Apple problem.

Why this matters for us: As AI moves into our glasses and headsets, the companies building that hardware will shape how we interact with the models we rely on for work, schooling, and daily life.

Instagram is testing more ways to customize Your Algorithm — the feature that lets you tell the app what to show and what to hide. It's a step toward giving users actual control over their feeds, instead of letting the algorithm decide what primos see.

The update lets you fine-tune what shows up in Explore, Reels, and your main feed. You'll be able to mute topics, hide certain creators, and adjust how much of each type of content appears. It's not a full rebuild — just a set of dials rather than a whole new dashboard.

Why this matters for us: Instagram is the main news source for millions of Brown and Black families, and every tweak to the algorithm changes what stories reach us, which voices get amplified, and what gets buried.

LastPass, the password manager millions of families and small businesses rely on, has had its data stolen yet again. The breach is another round of the same problem: customer vaults are locked, but the keys were left on the table. People who trusted the service to keep their passwords safe are now scrambling to reset them—again.

This isn't the first time. It's the pattern. Password managers are convenient, but when they go down, la gente goes with them. Bank logins, social media accounts, email passwords—all of it sitting in a vault that no longer has a lock. For Brown families, immigrant small businesses, and folks who juggle multiple accounts across work and home life, this means more time spent resetting passwords and more risk of things getting left behind.

Microsoft is also helping take down a major infostealer network that has been quietly harvesting credentials from millions of devices. The infostealers work like digital pickpockets—hitching a ride on everyday software and pulling out passwords, cookies, and session tokens. John Bolton, the former national security advisor, also pleaded guilty in his classified-materials case, marking another high-profile moment in a long-running legal battle over government secrets.

Why this matters for us: when the password managers we depend on fail, la gente pays the price—more time, more hassle, and more exposure for the families, businesses, and communities that can't afford to be locked out.

Scientists have found that the distinctive rhythm of human laughter — that "ha ha ha" pattern — didn't evolve separately in us. It comes from a common ancestor that lived at least 15 million years ago.

The research compared recordings of laughter from humans and other great apes, tracing the acoustic pattern back through the family tree. What sounds like a purely human quirk is actually older than that — it's something we inherited along with our cousins, not something we invented on our own.

It's a quiet reminder that we're not as separate from the animal world as we pretend to be. When we laugh, we're doing the same thing our primate relatives do. The rhythm of our joy is shared, not singular.

Why this matters for us: We laugh because we're related to chimps, not because we're civilized — esto es parte de la sangre.

Margaret Atwood recently had a run-in with AI that stuck with her. At the Baileys Literary and Cultural Festival in Portugal, she asked Claude for information about the British detective series Father Brown. Claude gave her something. She later figured out it was wrong.

The thing that got her: Claude didn't know it was wrong. Atwood called it "garbage in, garbage out." The model stitched together words from its training data and presented them as fact. No internal alarm bell. No moment of doubt. Just a confident answer that happened to be off.

This is the quiet problem with LLMs. They're not wrong the way a person is wrong — a person can second-guess, check a source, say "wait, let me think." Claude just generates. It doesn't have a model of the world, so it has no way of knowing when it's lying. Atwood's not dismissing AI. She's just clarifying what it actually does: it predicts what comes next, not what's true.

Why this matters for us: la gente is already putting AI into everything — from customer service to job applications — and most of us are dealing with answers that sound right but are wrong, so knowing how these tools work is part of reading the room now.