1,108 karma · joined April 16, 2013
I worked for a company that would have phone support for users, and we'd be watching their screens giving gentle suggestions to them as they were using our app for how to do what they needed to do. We never offered up what we were doing, but given users' poor descriptions of what they were doing, FullStory was an amazing customer service tool.
I think it's more like, "We don't want our harness to need to be able to interpret every version of our conversation format indefinitely."
No idea if the extra time "normal" fuel prices would have allowed Spirit to find a way to stay afloat, but the fuel price spike stole any time they had to figure it out.
We prepare security measures based on the perceived effort a bad actor would need to defeat that method, along with considering the harm of the measure being defeated. We don't build Fort Knox for candy bars, it was built for gold bars.
These model advances change the equation. The effort and cost to defeat a measure goes down by an order of magnitude or more.
Things nobody would have considered to reasonably attempt are becoming possible. However. We have 2000-2020s security measures in place that will not survive the AI models of 2026+. The investment to resecure things will be massive, and won't come soon enough.
Just look at Martha Stewart Living during her incarceration.
Celebrities are great at building brands, but they need to back away from their personal successes have bootstrapped the new brand before something they do becomes a liability.
Subway made their own celebrity spokesperson (Jared) and hitched their wagon to him for far too long. One or two years is understandable, but Subway had him so long it merged its identity with Jared until the truth about Jared was revealed.
I pay the company to verify me, I am their customer. They take on the liability of the OS makers and app makers of age verification.
If you have a valid token signed by a licensed IDS that verified your age in your OS, that's all anyone needs to know.
If they would do a 55/45 beef/plant-based meat blend and burgers, I think adoption rate would pick up significantly. Anybody who questions the taste is going to see that beef is the main ingredient. If the product comes in significantly cheaper than beef alone, more consumers will try it and look to it as an affordable way of eating beef.
For the bigger picture, 65 cows will stretch as far as 100 cows previously did, lowering suffering, environmental damage, inputs, etc.
For the people who like the 55/45 blend, it would open the door to an 80/20 blend plant vs. beef, and a 100% plant-based product.
There is so much undefined in how agentic coding is going to mature. Something like what you're doing will need to be a part of it. Hopefully this makes some impressions and pushes things forward.
Excellent idea, I just wish GitHub would show notes. You also risk losing those notes if you rebase the commit they are attached to, so make sure you only attach the notes to a commit on main.
"Utilities" doesn't indicate the audience or the intended longevity of use of the tool like "houseplant" and "bouquet" do.
Both indicate they are built for personal use cases, suggesting potentially low reusability. The longevity of "houseplant" suggests it's intended for ongoing use, while "bouquet" suggests a limited use tool.
With work, either could be made reusable for others, but I think it's implied that the scope is an edge case or uncommon case that likely only applies to its creator or a very limited audience.
I see value in the terms, but these terms may themselves be houseplant terms, not sure if general adoption is useful to someone not building houseplant software, they are mostly hobbiest terms by definition.
This is a token operation meant to project the idea that manufacturing is coming back to the United States. This is appeasement by Tim Apple.
> But the strategy is incoherent in a way that bothers me. The framing is "machine intelligence is a threat to the human species, therefore poison the training data." But poisoned training data doesn't make AI disappear — it makes open and smaller models worse while barely denting organizations with the resources to detect and filter adversarial data. Google, Anthropic, OpenAI all have data quality pipelines specifically designed to catch this kind of thing. The people most hurt would be smaller open-source efforts and researchers with fewer resources. So the actual effect is likely to concentrate AI power further among the largest players — the exact opposite of what someone worried about existential risk from AI should want.
Nobody is throwing out their phone or computer. Software will still be needed.
That said, there will be a lot of noise, with 100 choices in each category, how does one rise to the top? Is it simply the one that sticks around the longest and doesn't become abandonware?
Perhaps in reality more like a 3x advantage, due to human inefficiencies and the overhead of scaling the business to handle more clients.
Given that, 3x increase of productivity implies we either need 1/3 the accountants, or the accountancy supply brings down prices and more clients start hiring accountants due to affordability.