Product vision is as valuable as coding excellence [Image via Gemini]

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.

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.

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.

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.