Silicon Valley Technology Commentary & Archives · Est. 2006 3,045 Posts · 2006–2026

November 10, 2026

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

Can AI Deliver Bug Free Code?

Can AI Deliver Bug Free Code?


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

AlphaProof Code and the Shift Toward Software VerificationAll 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 library, 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 As automated verifiers mature, running unverified raw code on production networks may soon as outdated as leaving my index directories open with r-w-x (read, write, execute for you non-nerds) to the whole web.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 issue, 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.

November 08, 2026

November 08, 2026 · 3 MIN READ · BY LOUIS GRAY

Personal Finance is Evolving from ATMs to LLMs

Personal Finance is Evolving from ATMs to LLMs

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The world of finance will evolve. The LLMs are happy to help. [Image via Gemini] 

In the AI era, there's a great divide emerging between the old way and the new way, and practically no industry is more closely aligned with the "old way" with tried and trusted capabilities than that of finance, where security and history are king, integration of new technologies usually comes via massive consulting contracts, and everything had better be FDIC insured. The old way screams of buttoned up suit wearing ties on Wall Street, while we've seen newer generations try forge their own paths, through crypto, gaming through prediction markets or taking long-shot option bets popularized on forums like r/wallstreetbets.

Amidst this bifurcation, AI thinks it knows best. Anthropic  rolled out Personal Finance in Claude, as covered by ZDNET, enabling subscribers to wire their live bank, credit card, and investment accounts straight into a conversation window via Plaid, and helping users make sense of what to date has been a host of CSV exports or PDF extractions from antiquated institutions. Does this sound familiar? It should, only with some new wrinkles, for on the surface this feels like the rebirth of a product category Silicon Valley spent a decade abandoning.

Back in May 2008, when Mint first connected checking accounts, credit cards, and brokerage balances into a single one-stop financial hub, I signed up immediately. I remember amidst the financial crisis, how just six months later, Mint's math say my brutal weeks of portfolio losses and projected I would be bankrupt in sixty days. Luckily that didn't happen, even if it feels like it sometimes.

Later, in 2010, I defended trusting Mint and Blippy with my financial data because a unified ledger beat flying blind across ten separate logins. My early adoption of Mint and Blippy even led to CNN coverage about the "end of privacy," using me as a test case for someone who lived out loud online, even sharing otherwise mundane transactions.

Fast forward 15+ years, and large language models genuinely solve the formatting headaches that tripped up those early Web 2.0 dashboards. Letting Claude (or any other LLM, really) reason across messy Plaid feeds in plain English -- spotting quiet subscription creep, comparing grocery bills across quarters, or separating a one-off tax transfer from monthly burn -- is a much cleaner interface than clicking through static pie charts.

I've even built my own one-person financial app in Antigravity, which scoops up my bank account balances, daily stock swings, and reminders for mortgage and car payments. I can click this Progressive Web App I built for myself and see exactly where I am on the +/- for the day, and see if it's even worth getting out of bed. That we can code up ideas and turn them into reality for practically any task is a brand new world.

But finance earned its conservative reputation. What happens when we trade direct accounting for probabilistic interpretation? If Mint mislabeled a charge in 2008, the bad data sat right there in the table for you to fix.

If a chatbot summarizes six months of bank feeds, a skipped recurring fee or a fuzzed category total may hind behind confident, reassuring prose, and assure the end user all is well, only for the IRS to potentially disagree later. Your transaction ledger is the ultimate truth  about where you go, what you value, and what you can afford. Once frontier AI labs hold your live spending graph alongside your daily prompts, the chatbot becomes the stickiest lock-in in consumer tech. Read-only access is step one, but how soon will you ask your LLM to ask you which mutual funds to choose, trade on your behalf or even tell you what time is the right time to sell your house?

Disclosures per always: I work at Google. Anthropic and other other AI companies are often partners, competitors or customers. Don't interpret my interest as being filtered with that lens.

November 08, 2026

November 08, 2026 · 2 MIN READ · BY LOUIS GRAY

Human Curation from the Webnerd.ai Stream: v2

Human Curation from the Webnerd.ai Stream: v2

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My job: Finding the best articles and amplifying them out. [Image via Gemini]

Signal From the Stream: Handcrafted Words in a High-Wattage World

With Webnerd.ai bringing fast paced consumption and sharing back to my daily routine, the muscle of scanning, filtering and amplifying is back. This week is no different.

After a decade's effort in building out siloed social networks that aim to keep their content boxed in, independent blogging has endured and continues to push back. I'd be remiss if I didn't point out Paul Ford's post, The Web Is More Than Enough, where he showcased launching an entire browser-based office suite where all activity lives right in the URL, reminding us that the open web remains the most durable application platform on earth. Over at Techdirt, Mike Masnick called out Reddit bricking up login walls, saying its defensive posture runs against Aaron Swartz's open access roots.

What we all saw this week with the US midterm elections is that closed networks force closed thinking. Republicans learned that X is the echo chamber. It was an inevitable result after Elon's acquisition and government meddling chased away all the left-leaning free thinkers to new places.  As Andy Baio called out, we know closed social feeds confuse algorithmic echo chambers with real-world consensus.

(I told you already that X was toxic, but maybe the right wing has figured this out now too?)

We are all continuing to learn where AI fits in our workflow and how much we invest in it. This is true at the corporate level as well. Tomasz Tunguz ran the math on an 80-gigawatt AI ceiling for 2027, showing how doubling GPU rental rates are pushing inference bills to new heights, while cheap AI intrusion tools are straining security teams at unprecedented levels.

AI is doing incredible things in terms of resetting expectations for employees at all levels. It's reset expectations for middle managers and reset expectations for new hires. At Anthropic, Felix Rieseberg said he has retired traditional coding interviews because hunger beats whiteboard tenure in an agentic world. And John Battelle captured the emotional knot of modern tech workers in Baring It All To Claude, which can mean trusting a model with your life's work, and hoping for the best.

When platforms wall themselves off and algorithms chase outrage, sitting down with an RSS reader and sharing good writing by hand isn't nostalgia. It's how we keep the web human. I'll be doing my part over at Webnerd.ai, and sharing out to RSS or Bluesky or wherever you like. That's what standards are for.

Disclosures per always: I work at Google. No doubt some of the companies mentioned here are partners, competitors or customers. Don't interpret my interest as being filtered with that lens. I built Webnerd.ai (and have no plans to monetize it).