Silicon Valley Technology Commentary & Archives · Est. 2006 3,047 Posts · 2006–2026

November 12, 2026

November 12, 2026 · 4 MIN READ · BY LOUIS GRAY

Webnerd.ai Debuts News View from Feeds and Blogs

Webnerd.ai Debuts News View from Feeds and Blogs

Webnerd News Showcase Edition in the midnight-cobalt and orange louisgray.com theme showing a clustered lead story, perspective badges, Picks For You, and Discover New Voices
Webnerd News (in Labs) brings visual clustering to top stories and streams.

Webnerd News Magazine on Webnerd.ai

An algorithm-free stream of updates, sorted chronologically, ensures you never miss a single post. Bringing that classic RSS reader feeling back, including recommended bundles and sharing, has reinvigorated the discovery loop for me after a dark decade dominated by social feeds fueled by ragebait, attempts at viral videos and headlines that left you questioning what stories were all about. But there's also value from automated or hand-selected curation you see from sites like Techmeme and major news hubs like CNN or Google News.

Typically, these sites are fed by their own first party sources or editor curated content. As a viewer, they may slightly adjust based on their incremental levels of personalization, but for the most part, you get the same view everyone else does -- and your headlines or top stories are the ones they see.

What if you could combine the at a glance view of what's most important, including story clustering when many sources cover the same topic, but built on a foundation of the sources you choose to read? That's the idea with a new view in Webnerd.ai -- a fun experiment that combines the feeds you personally subscribe to, augmented by the starter packs I engineered into the site from the first day, ensuring you always have something to read, and constantly have new sources to discover and subscribe to.

Building on the web platform, and offering a direct connection from the publisher to the reader is an important foundation of what makes RSS special. If everything is a feed, you can point that feed and shape it every which way. We remember this from the 2010 era wave that saw Flipboard unveil its social magazine on the iPad alongside Feedly, Plaxo Pulse, Ninua and many others, even as plenty of pundits rushed to declare classic feed readers dead. I pushed back at the time saying RSS or RIP, the Results Always Trump the Methods, arguing that consumption tools aren't a zero-sum game. Sometimes you want the raw river, item by item. Other times you want an editorial front page that groups the noise into a coherent briefing. After watching filtertainment eviscerate our informed monoculture over the past decade, building both modes on top of open feeds feels overdue.

So let's have fun with it.

Clustering Your Subscriptions With 14 Starter Packs

Webnerd News Full Coverage modal grouping Primary Reporting, Deep Analysis, Indie & Blogger Voices, and Video & Audio on a single story
Tapping Full Coverage lines up reporting, deep dives, indie bloggers, video, and podcasts on the same story.

The engine underneath Webnerd News starts with every blog, newsletter, YouTube channel, and podcast you have connected, then blends in active coverage across all 14 Webnerd.ai Starter Packs. Strict source diversity caps keep any single high-volume site from flooding the page, and if you still haven't tried Webnerd.ai yourself, and take a look without logging in, it defaults to an edition generated from my own subscriptions so you can kick the tires right away.

Instead of repeating duplicate headlines, related posts converge into a single story cluster tagged by the role each piece plays, offering:

  • Perspective Tags & Full Coverage: Every item carries a clear badge -- Reporting, Deep Dive, Indie Take, Community Pulse, Video, or Podcast. Hit Full Coverage to compare every angle side by side or step through a chronological timeline of how the story unfolded.
  • Inline Starter Pack Discovery: When a writer from a Starter Pack you don't follow lands inside a story cluster you're reading, or surfaces in the Discover New Voices rail, you see which pack brought them in alongside a one-click + Follow button that subscribes and files them straight into a matching folder.
  • Zero Unread Anxiety: Browsing Webnerd News is strictly read-only against your classic reader queue. Flipping through the magazine never marks articles read behind your back, and stories you already read earlier in the morning still stay on the board for context

This is very much day one of a broader buildout and another fun volley in vibe coding to victory. I plan to keep tuning the clustering weights, tightening how personal folder signals steer the front page, and expanding the Starter Pack catalog beyond tech and media. Take Webnerd News for a spin on your own feeds today and let me know on Bluesky what clicks, or what you'd love to see next.

Disclosures, per always: I work at Google and use Gemini and Antigravity tools a lot. I built Webnerd.ai, its Chrome Extension, and this blog's CMS with Antigravity's help. Nobody at Google reviews my posts, ever. Not even those folks who make the excellent Google News.

November 11, 2026

November 11, 2026 · 3 MIN READ · BY LOUIS GRAY

When Code Is Cheap, Product Vision Gets More Valuable

When Code Is Cheap, Product Vision Gets More Valuable

Conducting the product lanes in a sunlit studio [Image via Gemini]
Product vision is as valuable as coding excellence [Image via Gemini]

When Code Is Cheap, Product Vision Wins the Hiring Market

As long as I've been in Silicon Valley, engineers have been king. The most sought after, and highest paying, roles have gone to the code orchestrators with the highest talent, who have been able to turn ideas into reality. Expertise could be claimed due to the number of coding languages they knew, and effort could be arbitrarily counted by the number of lines of code, with only its complexity up for debate. The most flexible and most capable engineers have deftly adjusted their expertise to meet the industry's latest demand, from dedicated apps for the top operating systems at the time, to mobile applications, social network tools, ride sharing apps, autonomous driving, crypto, or whatever business fad or innovation has driven the newest industry.

But now we're in an odd spot. Many of the software engineers I know and have worked with for years are telling me they scarcely code at all, with AI-assisted coding (vibe coding if you must call it that) making it possible for them to tell agents what to do and how to build at unprecedented scale. Meanwhile, recent college graduates sporting computer science degrees are finding entry level opportunities have practically disappeared.

Every technology shift has downstream impact, and the seismic shift toward AI-driven tooling means the roles in demand in this new world have evolved. Lenny Rachitsky's breakdown of the tech job market puts hard numbers behind a shift many of us have seen with our own eyes or felt when looking at our in boxes and LinkedIn messages. Demand for traditional software engineers is plateauing, open mobile and front-end roles have been nearly cut in half, and now product managers are suddenly the ones seeing the biggest hiring surge. 

When I wrote about vibe coding acting as automatic transmission for apps last month, the takeaway wasn't that humans were obsolete, but that the mechanical act of shifting gears was no longer the bottleneck. If a coding agent can build out an app or deliver a mobile view in an afternoon, paying a premium for narrow implementation stops making sense. As Gergely Orosz pointed out in response to Lenny (see Techmeme), specialists who only know one slice of the stack are getting squeezed out in favor of generalists who can steer AI across the whole system.

There is no such thing as a sure thing in a turbulent time. Back in 2018, I looked at Silicon Valley's divergent career arcs and how quickly comfortable middle-tier roles can evaporate when the industry's priorities tilt. We are watching that exact thing play out today in real time.

Telling a machine what to build requires knowing what is actually worth building. If code generation gets cheap, product judgment becomes the scarce resource, which is why product managers and customer-facing builders are having a moment, living in the messy human problem space where no model can hallucinate real user empathy. As I argued in my October piece on human evolution in an AI revolution, the winners won't be the folks guarding the roles and tools of yesterday, but those who are flexible enough to see how the world is changing and be part of that movement themselves.

November 10, 2026

November 10, 2026 · 2 MIN READ · BY LOUIS GRAY

Can AI Deliver Bug Free Code?

Can AI Deliver Bug Free Code?


The bug verification desk is now unmanned. [Image via Gemini]
The bug verification desk is now unmanned. [Image via Gemini]

Can AI Deliver Bug Free Code?All software has bugs. It has always been that way, and much of the recent discussion around AI's impact on software engineering has been about unveiling security holes that plague popular software and may have sat for years -- hardly the setup for promising complete code verification.

I saw the headlines around DeepMind's AlphaProof Code announcement this morning, saying they confirmed Signal's security protocol to be solid, and initially glanced past it, as someone who typically doesn't use Signal. But the post has ignited a foundational discussion about how software will be built and verified going forward in the usual places, including Hacker News, which has zeroed in on a major turning point: moving from classic test-driven development to automated, machine-driven formal proof generation.

The reaction across the developer community spans healthy skepticism to long-term optimism, mirroring a lot of what we've seen in response to AI advancements, ranging from disdain and disbelief to  nodding acceptance. But zero bugs? If AlphaProof Code looked at my code and found no errors, I'd assume the verification itself was flawed. That'd be as impossible as sending one of my draft blog posts to an editor and being told it was perfect.

More broadly, AI systems can now be used to verify human-written libraries, and neural models can now write top quality code, taking the spot we've reserved for decades for well trained and well paid humans.

This shift connects directly to what I explored in Vibe Coding: Automatic Transmission for Apps, where higher abstractions free engineers from manual routine mechanics to focus on high-level architecture. It also reinforces the broader reality I wrote about in An AI Tech Revolution? The Solution: Human Evolution. Technology shifts require human adaptation rather than passive observation. As automated verifiers mature, running unverified raw code on production networks may soon be as outdated as leaving my index directories open with r-w-x (read, write, execute for you non-nerds) to the whole web.

Bug free or not on the first try, we are seeing AI do more. AI is writing, reading, coding and now debugging. I'm betting that even if this pass manages to come back with zero known issues, the definition of what is a bug and what is not will change. 

Disclosures, per always: I work at Google and use Gemini and Antigravity tools a lot. DeepMind is a huge part of Google's AI effort and behind AlphaProof. Nobody at Google reviews my posts, ever.

November 09, 2026

November 09, 2026 · 4 MIN READ · BY LOUIS GRAY

The Internet Turned Into TV, but Television Has No Blue Links

The Internet Turned Into TV, but Television Has No Blue Links

Routing blue links past unplugged TVs [Image via Gemini]
Routing blue links past unplugged TVs [Image via Gemini]

One of my favorite web authors, Ryan Broderick, who I read religiously, dropped another one of his truth bombs today in Garbage Day, decrying the continued decimation of text-based content that once defined the web, only to see it morph into something that is video first, or as he says "officially TV now". As we've observed over the last two-plus decades, Web behavior has rotated from newsgroups and reading full text articles, following links across the web, to short-form video consumption and Netflix-style episodic bingeing, with powerful algorithms suggesting you keep watching -- with sleep as the natural enemy.

Like I've said recently, you can't force old habits on new people who have been raised in a world of infinite bandwidth and infinite choice any more than you can ask kids to turn off the cartoons or put down the YouTube and pick up a newspaper. In today's post, Ryan calls time on the old "internet of libraries, replaced by an "internet of televisions", where, as he puts it, no one is famous, everyone is a celebrity on rented terms, and getting real traction with written words gets harder by the month -- made even more real as the hub and spoke model of RSS readers and centralized discovery lost momentum each year in favor of chasing ephemeral likes and practically non-monetizable "views", whose definition changes regularly to suit the platform.

Just a few weeks ago, I highlighted Garbage Day when saying how filtertainment eviscerated our informed monoculture. Every leap in bandwidth eventually fills the container you give it. We marched from static text sites passed around via links and email, to real-time social streams, to pocket screens pumping high-definition video straight into our earbuds. Not that this really comes as a surprise. In 2010, I warned about accelerating information streams on connected devices with "no off button, ever." When you give a tired population a choice between demanding prose and effortless video dopamine, the couch wins almost every night.

Video winning the mass-market feed isn't a mystery, if that's the market you want.

What breaks the open web for writers is a simpler mechanical truth: television has no blue links. When someone leans back into an algorithmic Reel, a video podcast on YouTube, or a zero-click chatbot answer, there is no natural exit ramp carrying a curious mind three hops deeper to an unfamiliar blog. I traced the roots of this choke point back in 2018, examining how a decade of silos throttled open content distribution and left the web linking less and talking more.

Publishing has always rested on creation, discovery, and distribution. Once Google Reader, FriendFeed, Digg, and Technorati disappeared, dominant platforms stopped acting as filtered pass-throughs. They actively throttled outbound URLs to hoard watch time, training creators to perform natively inside the silo for instant feedback while an essay on your own domain sat waiting for visitors who never arrived.

Waiting around for algorithmic cable boxes to hand text writers organic reach is a losing game. If the giant social apps want to be television, those of us who still think, build, and connect through reading have to wire up our own switchboard again. That conviction is why I built Webnerd.ai, which I introduced last month as a personal project that has no expectations of millions of users, but rejuvenates that feeling of discovery and sharing.

Do your part by cutting out the broadcast middleman: subscribe directly to blogs, personal newsletter inboxes, feeds and publications in folders you control, backed by practical AI summaries and stream audio that save time while still sending clicks straight to the original author.

Even more important is solving the traction gap where open-web discovery always worked best -- from person to person. Algorithms optimize for passive session length, while human readers vouch for voices worth keeping. Curated starter bundles help newcomers find active blogs on day one, while one-click sharing inside the app or right from the browser toolbar with the Webnerd.ai Chrome Extension turns every reader into a distribution node. When I flag a great piece, it lands on my public shared stream, cross-posts to Bluesky, and feeds its own subscribable RSS stream, keeping those blue underlines traveling across the open web.

Broadcast TV never killed books or independent magazines, and Instagram's binge button won't kill sharp writing either. Let the big platforms fight over the living room. The library is still open -- we just have to pass the good reads around ourselves.

Disclosures, per always: I work at Google and use Gemini and Antigravity tools a lot. I built Webnerd.ai, its Chrome Extension, and this blog's CMS with Antigravity's help. Nobody at Google reviews my posts, ever.