but it might be, say, 20% more productive in 20% of your workday, or 1000% more productive 2 days per month (the days when that perfect dream spec hits your desk that you can just paste into claude and get a slick working system back), which works out to just 4% more productive overall, or whatever, which is hard to measure with all the noise.

in the end companies will pay for these tools because their employees will be demanding them, same as they demand other things that make their workday more pleasant - email, coffee, air conditioning, a conveniently located office, etc.

that said, I see the intelligence itself being rapidly commodified/free. the companies that extract rent in the sector will be the ones that effectively bundle and sell corporate-friendly features with the core intelligence - compliance, tracking, productivity, systems integration, authentication, etc. etc. etc. Which is a competency companies like Salesforce, Microsoft, Google already possess, so they are likely to win. Plus a weird Euro variant of course.

i could see a long tail of impenetrable chaos as private correspondence gets hacked, ppl get divorced, fired, fight back, flood the zone with their own reputationslop so they have a grounds for denial, decide to take it ALL down to distract. recursive waves of tyranny/chaos. this isnt the singularity we were promised!

What if it doesn't understand what you're asking it to do and keeps failing and you have to keep rolling back? Can you understand the 20,000 lines it's generated so you can make the change yourself without tearing your hair out? Can you fix bugs in it that it can't, without starting from zero and having to understand the whole codebase?

I have just gotten off 3 years as a developer for that kind of project, and I used the best AI tools diligently every day. It often saved me time. Like from some small drudgery of half day of flailing about in config land. Or it could generate some nice rails controllers and a javascript front end from a well-written spec. writing tests was also a strong suit.

but just as often it failed to understand the depth of the product and its myriad concerns and led me down the garden path, reducing my efficiency.

Aside from that, a large part of my job was the parts that weren't coding - wrestling with specs that were far from ready for primetim, chaotic internal processes, deployment, internal coordination/communcation, talking to customers, etc.

In the end it seemed like it saved me maybe 20% of my time overall. Nothing to sneeze at.

I get that greenfield apps that have no customer contact can be created with a phrase now. That's pretty amazing. But I would love to see Opus 4.6 up against a real beast of a codebase that you're far from a master of.

Then there will be the AI wranglers who act almost like DevOps engineers for the AI - producing software in a different way ...

Later in the book, the China story was a close second. In order to get into China (to "grow") - exec team agreed to host Facebook's servers in China where the government could get access to customer private data, so they could stifle dissent.

Tons of other weird/bad/embarrassing stuff too. The author, a member of the core executive team, was seriously complicit but redeemed herself in my view with this no-holds-barred account of the complete lack of ethics up top.

In general a damning portrait of the executive team as just not giving a shit about anything except for growth and willing to actively participate in dictatorship in order to make it happen.

I thought the difference must be in how Claude Code does the agentic stuff - reasoning with itself, looping until it finds an answer, etc. - but I have spent a fair amount of time with Claude Code now and found that agentic experience to be about the same between Cascade and Claude Code.

What am i missing? (serious question, i do have Claude Code FOMO like the OP)

https://www.amnesty.org/en/

https://waymo.com/blog/2024/05/fleet-response?utm_source=cha...