Developers (often juniors) use LLM code without taking time to verify it. This leads to bugs and they can't fix it because they don't understand the code. Some senior developers also trust the tool to generate a function, and don't take the time to review it and catch the edge cases that the tool missed.
They rely on ChatGPT to answer their questions instead of taking time to read the documentation or a simple web search to see discussions on stack overflow or blogs about the subject. This may give results in the short term, but they don't actually learn to solve problems themselves. I am afraid that this will have huge negative effects on their career if the tools improve significantly.
Learning how to solve problems is an important skill. They also lose access to the deeper knowledge that enable you to see connections, complexities and flows that the current generation of tools are unable to do. By reading the documentation, blogs or discussions you are often exposed to a wider view of the subject than the laser focused answer of ChatGPT
There will be less room for "vibe coders" in the future, as these tools increasingly solve the simple things without requiring as much management. Until we reach AGI (I doubt it will happen within the next 10 years) the tools will require experienced developers to guide them for the more complex issues. Older experienced developers, and younger developers who have learned how to solve problems and have deep knowledge, will be in demand.
Good question. Personally, I feel that answer engines will go the same route as search engines and start monetizing brand mentions and I feel this will be done openly, similar to ads. That being said I feel that there is room for brands to improve their presence as well. Most models claim neutrality at the moment, but we’ve already seen anecdotal cases where some brands consistently outperform others in AI responses with no clear reasoning
On your question regarding how influence can be detected.....
That’s a big part of what we’re working on at MentionedBy.ai. We track brand mentions across multiple models over time and flag sudden shifts — e.g., a competitor showing up overnight in all responses, or factual distortions creeping in. Think of it as version control + monitoring for the "AI perception layer."
As for llm.txt abuse.....
Yes, totally possible. We expect a wave of LLM-targeted SEO — structured data, vector bait, invisible prompts, etc. One idea we’re exploring is a kind of “LLM spam index” — patterns of over-optimization or hallucination correlation that could indicate manipulation attempts.
Back when I used dial-up, I experienced a lot of stress when I was connected. I felt I had to be as effective as possible, because we had to pay for every minute spent.
When I switched to DSL the stress went away, and I found myself using internet in different ways than before, because I could explore freely without time pressure.
I think this applies to Claude as well. I will probably feel more free to experiment if I don't have to worry about costs. I might do things I would never think of if I'm only focused on using it as little as possible to save money.
No one is going to be home at 10AM on a weekday to wait for a delivery. Online e-commerce is worse experience than traditional retails if you start requiring people to sign for every shipment.
What I like most about the grip strength meme is that it’s a perfect example of how correlation doesn’t imply causation. I already had to explain to a friend how focusing on improving his grip strength is great but probably won’t help him live any longer. Having a concrete example makes the concept easy to understand.
Seconded, I've been using plappa for a couple months after Apple messed up PWAs after bringing them back (Audiobookshelf didn't want to change to next chapter when the app was in the background) and I'm generally very happy
My views on monetary versus fiscal policy, public versus private ownership, markets versus planning, methods of government and economic production are not relevant.
If you think “right wing” creates a better environment or “left wing” is independent of whether the environment dominates DNA/Darwinian ideas about being born superior
> He told his mother he wanted to organize a carnival for his friends, and mistakenly, he said, he placed an order for almost 70,000 pieces of the candy instead of reserving it.
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Experience: 7+ years as backend engineer
I am a backend engineer from Indonesia. I love new challenges and willing to learn new technologies if needed.
that’s what I mean by ‘maxis’ — the people that rarely, if ever, acknowledge epigenetics.
They focus entirely on DNA / Darwinian evolutionary theory from centuries ago, ignoring environmental evolution, or to put it another way — evolution that happens as part of your lived experience opening the door to the heretical idea that they are where they are because of birth luck
There are some fundamental different between two ecosystems.
On Google, the Google Drive and Photo are encrypted to a key owned by google.
On iCloud, the iCloud Drive and Photo are encrypted to your account key. In which, without ADP, this key is shared with Apple. When ADP is enabled, Apple does not store this key. iCloud Backup is stored with the same technology as iCloud Drive.
When it comes to lost password account recovery:
- Google can just reset your password, and your drive and photo are still accessible. All barrier are procedural, not technical.
- iCloud (with ADP), they can still reset your password, but then your icloud drive and icloud photo are loss forever.
There are some trade off ..:
- Lost password recovery experience. _Some_ user will lost their password anyway. How high should the bar be?
- Cloud first? or local device first with cloud backup?
- Are you giving the cloud data same protection as local device?
In google's solution, they put the google drive data at risk...
In apple's solution, it need extra steps to ensure you have proper account recovery flow covered.
It's not really socialism because you don't own or have any say in the company you work for. And not everybody owns stocks.
It's more like feudalism where those kings cut in the people below them so that they have a stake in the system and don't get any ideas about revolting.
To add, obviously the hardware and ISA matter on a per-task basis and might provide some competitive advantages - eg sport, conventional/western beauty standards, some intellectual capabilities, but again, survival of your genes is dominated by birth circumstances
This! DNA is like the ISA, the environment and biological processes created by it is the software and therefore dominates
DNA maxis exist because the idea of being genetically superior is deeply attractive to the privileged and powerful to justify their position independently of their circumstances of origin
It’s fascinating how NIF's legacy tech limits its relevance for actual energy generation, yet it still serves as a stepping stone. The fact that gain scales faster than linearly with input power is particularly encouraging — it suggests that advances in laser efficiency and repetition rate could unlock meaningful progress sooner than many assume. I can see why startups are jumping on this now. Curious to see how much of this can move from lab to grid in the next decade.
Is this actually happening? I figured the result would be China simply swooping in and picking up all the trade partners we've alienated. And also all the soft power we've abandoned.
Developers (often juniors) use LLM code without taking time to verify it. This leads to bugs and they can't fix it because they don't understand the code. Some senior developers also trust the tool to generate a function, and don't take the time to review it and catch the edge cases that the tool missed.
They rely on ChatGPT to answer their questions instead of taking time to read the documentation or a simple web search to see discussions on stack overflow or blogs about the subject. This may give results in the short term, but they don't actually learn to solve problems themselves. I am afraid that this will have huge negative effects on their career if the tools improve significantly.
Learning how to solve problems is an important skill. They also lose access to the deeper knowledge that enable you to see connections, complexities and flows that the current generation of tools are unable to do. By reading the documentation, blogs or discussions you are often exposed to a wider view of the subject than the laser focused answer of ChatGPT
There will be less room for "vibe coders" in the future, as these tools increasingly solve the simple things without requiring as much management. Until we reach AGI (I doubt it will happen within the next 10 years) the tools will require experienced developers to guide them for the more complex issues. Older experienced developers, and younger developers who have learned how to solve problems and have deep knowledge, will be in demand.