Is anybody else bored of talking about AI?
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Dark ModeSoftwareIs anybody else bored of talking about AI?Is anybody else bored of talking about AI?
Mar 24, 2026
3 minute readAt serious risk of sounding like a heretic here, but I’m kinda bored of talking about AI.I get it, AI is incredible. I use it every day, it’s completely changed my workflow. I recently started a new role in a
tricky domain working at web scale (hey, remember web scale?) and it’s allowed me to go from 0-1 in terms of
productivity in a matter of weeks.With that being said, it’s all starting to feel a bit… routine. I’m not here to argue that the pace of change has
been incredible, but on a day-to-day basis I’ve sorta ran out of things to talk about. What makes this worse is it’s
completely taken over mindshare across my section of the internet.Hacker News, my favourite haunt, used to be full
of interesting projects and problems being solved but this seems to have devolved into three different people’s
(almost identical) Claude code workflow and yet another post about how you got OpenClaw to stroke your cat and
play video games so you had way more time to… configure AI tooling. This all feels a little self-fulfilling.Kagi small web
is another great example of this effect. Here’s a challenge, open it up and press the ‘next’ button 20 times.
What percentage of posts are AI related?Before you write me off as ‘old man yells at cloud’, understand where I’m coming from. In the good old days (2023),
before we called anybody who could open a Claude code terminal an ‘AI engineer’, being a ‘Product Engineer’ was the
hot new term. The idea was that engineers should move away from obsessing over code to obsessing over the product
value they were delivering. I loved this, it made loads of sense to me, but we seem to have regressed. It’s no longer
the code we’re obsessing over, it’s the overgrown auto-complete we’ve developed to make the easiest part of being an
engineer easier.It’s like if I went onto the woodworking subreddit and they’d all stopped showing pictures of the tables they’d
created and just started posting about the hammer they were using. But they were all using basically the same hammer
in the same way, so they were just screaming the same shit at each other at the top of their voices.What makes this worse, is our bosses have bought into it this time too. My managers never cared much about database
technologies, IDE’s or javascript frameworks; they just wanted the feature so they could sell it. Management seems to
have stepped firmly and somewhat haphazardly into the implementation detail now. I reckon most of us have got some sort
of company initiative to ‘use more AI’ in our objectives this year. Management’s involvement in the SDLC has always
been a thing, DORA metrics have been around for a while. But historically, it’s always been about the outputs.
Faster deploys, time to respond. Now we’re measuring the number of tokens used per-dev, which is no more useful than
lines of code ever was.I guess what I’m saying, other than just having a general whinge, is tell me more about the cool shit you’re building
rather than the tools you’re using to build it. And don’t forget that the whole purpose of coding, like any other
craft, is to create something that delivers value for someone. Even if that someone is just yourself.… And yes, I’m painfully aware of the irony of a post about moaning about posts about AI. Sorry.Llms
Claude
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Jake Saunders’ blog post, “Is Anybody Else Bored of Talking About AI?” presents a compelling, albeit slightly contrarian, perspective on the current discourse surrounding artificial intelligence, particularly within the tech industry. The core of Saunders’ argument revolves around a perceived shift in focus, away from tangible product development and towards an excessive preoccupation with the tools—specifically large language models (LLMs) like Claude—utilized to generate output. He expresses frustration with a trend where online conversations, notably on platforms like Hacker News, have become dominated by iterative discussions about LLM workflows, largely devoid of substantive problem-solving or innovative project contributions.

Saunders argues that this trend has eroded the traditional role of a “Product Engineer”—a concept he describes as having faded from prominence as the focus shifted from product value to the ease afforded by AI-powered autocomplete tools. He uses the analogy of a woodworking subreddit, where members are obsessing over a specific hammer rather than the furniture they are producing, highlighting a disconnect between the tools and the intended outcome. The author suggests that management’s increased involvement in the Software Development Lifecycle (SDLC), now extending beyond strategic outputs like deployment speed and responsiveness to include metrics such as token usage per developer, further exacerbates this issue. This shift, he contends, reduces engineering to a task of optimizing AI tool usage rather than delivering genuine value.

The post’s central plea is a call for a return to focusing on “the cool shit you’re building” – the actual products and solutions being created – rather than the tools being used to create them. Saunders stresses the fundamental purpose of coding and other crafts: to generate value, even if that value is realized by the individual. He acknowledges the irony of writing a piece critical of discussions *about* AI, recognizing the self-referential nature of the situation. Throughout the piece, Saunders subtly critiques the prioritization of technological trends over demonstrable results, suggesting a potential regression in engineering best practices.

The author utilizes several illustrative examples to support his claims, including his own experience in a web-scale domain, highlighting the rapid productivity gains facilitated by AI, and pointing to Kagi’s website as an example of the over-saturation of AI-related content. His use of terms like “LLM’s shouldn’t always land the plane” suggests a belief that AI should be considered a supporting element rather than the central driver of technological advancement. The post does not offer solutions but instead articulates a concern regarding the current trajectory of the conversation, advocating for a more balanced, value-oriented approach within the tech industry.