Welcome to your weekly Brew & AI
Each week, I’ll share how to make sense of AI - no jargon, no hype, just simple insights you can actually use.
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Grab your coffee - let’s dive in. 👇
☕ AI in the news
Meta’s $80B metaverse bet quietly pivots to… mobile apps and AI
Nearly five years after calling the metaverse “the next frontier,” Meta is shutting down the VR version of Horizon Worlds for Quest headsets, removing it from the Quest store by the end of March and discontinuing VR access in June.
Horizon will live on as a mobile‑only product, and the broader company narrative has clearly shifted from VR worlds to AI assistants, agents, and recommendation systems as the new core bet.
It’s a wild arc: from rebranding the entire company around VR to quietly sunsetting the flagship experience while everyone now talks about LLMs and agents instead.
New models keep dropping – and they’re getting cheaper, not just bigger
Outside the OpenAI bubble, a wave of March releases from labs like DeepSeek and others are pushing multi‑million‑token context, faster inference, and aggressive per‑token pricing.
A lot of these aren’t meant to wow consumers directly; they’re designed for infra teams that care about throughput, latency, and GPU cost curves.
Net effect: if you’re building AI‑powered products, raw “model rent” is getting less painful right as use cases are getting more ambitious.
☕ Trending on social
🎨 Google just launched Stitch, an AI tool that can generate app interfaces and UI designs from simple text prompts, basically, describe what you want a screen to look like and it builds it for you.
The announcement got people buzzing, with reactions ranging from genuinely impressed to skeptical about the quality of the results. Investors, meanwhile, didn't wait around to form an opinion - Figma's stock took a notable hit, signaling that Wall Street sees Google's move as a real threat to design tools that developers and designers rely on today.
📹 YouTube recently announced that creators must label their videos if they contain AI-generated content - a move the platform is framing as a transparency win for viewers.
But here's the spicy take making the rounds: some people think YouTube is essentially getting its massive user base to do free data labeling work, the kind that AI companies normally pay teams of humans to do. It's a classic "are we the product?" moment, and it's got people questioning whether this policy is really about protecting viewers or quietly building a goldmine of tagged AI content.
💑 Marie Schneegans posted about separating from her romantic partner... on LinkedIn, the platform historically reserved for job updates and thought leadership about "disrupting synergies."
The post went viral largely because people couldn't help but laugh (and cringe) at the blurring line between professional networking and personal oversharing — a trend that's been creeping onto the platform for a while now. It's a perfect snapshot of LinkedIn's identity crisis, where "I just got promoted" now shares a feed with "I just got dumped," and somehow both are framed as career growth opportunities.
☕ AI workflow of the week
Turn your changelog + support tickets into a “what should we build next?” map
PMs, founders, growth and support leads who are drowning in feedback but still default to “gut feel” in roadmap meetings.
Problem: You’re shipping features, your support inbox is full, and your changelog looks busy – but it’s hard to answer basic questions like: “What did we ship that users actually cared about?” and “What’s the next obvious thing to build for our best customers?” Doing this manually means reading hundreds of tickets, sifting through release notes, and trying to remember what happened three sprints ago.
How to run it (30–45 minutes):
1. Pull 2–4 weeks of “reality.”
Export: your changelog entries, top 100–300 support tickets (or tags), and any recent NPS / “what’s one thing we could improve?” free‑text answers. Strip out PII, then drop everything into a single doc or upload to a long‑context model.
2. Ask for an impact‑map, not a vague summary.
Prompt the model to:
Cluster tickets and comments into themes
Map each theme to: “recent change,” “missing feature,” or “UX papercut”
Score each theme on (a) volume, (b) intensity (how angry / desperate users sound), (c) revenue proximity (paying vs free users).
3. Force it into a PM‑friendly table.
Ask for a table with columns: “Theme,” “Type (new feature / improvement / bug),” “Who it affects (segment),” “Evidence (representative quotes),” “Risk of not doing,” and “Suggested solution approach.” This becomes something you can literally paste into Notion / Linear as a backlog input.☕ Try this out - prompts
This week – Turn an AI model into your brutally honest “weekend plans” consultant
You are my slightly judgmental, very honest weekend plans consultant.
Ask me 7 rapid‑fire questions about:
- how much social battery I have left,
- my budget,
- my energy level,
- what the weather’s like,
- what I’ve been procrastinating,
- who I actually like hanging out with,
- and what I secretly *wish* I was doing.
Then:
1) Roast my default weekend habits in 5 short bullets.
2) Propose 3 very specific, realistic plans for this weekend:
- title,
- exact schedule,
- where I go,
- what I do,
- who I invite (or avoid),
- and the one sentence I’ll use on Monday when someone asks “How was your weekend?”
Keep it fun but feasible – nothing that requires a personality transplant.☕ Weekly Reads
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☕ Resources
If you missed my writing, here’s everything I’ve done - bite‑sized, practical, and very AI‑obsessed. Think of this as the “in case you blinked” shelf for my recent posts, threads, and experiments.
✍ Blogs - In-depth articles and insights to expand your AI knowledge
🛠 Tools - Discover powerful AI tools to enhance your workflow
💭 Tips - Practical tips and tricks to make your AI journey smoother
💛 P.S.
That’s it for this week’s brew.
I’d love to hear what you think - what you liked, what could be better, or what you’d love to see next.
Just hit reply - I read every message over my morning coffee ☕.
Brew & AI
Making AI simple, one sip at a time