> But I can't help but feel that it is missing the point.
It’s perfectly fine if _your_ point in playing music is rooted in some flavor of anti-capitalism and your intrinsic joy of your creative process. _His_ point was to write an album during a sabbatical. He succeeded and then some!
What is your a priori estimate for the percentage of news that is consumed as entertainment? As in, it does not result in a change of behavior in the consumer beyond engendering neuroticism. I'd put that number at or above 95%. News is gossip wearing a suit.
Yes, easily head and shoulders above 5.5 and 4.8. The others are like pulling teeth, comparatively (in a domain that never triggers the security fallback at least).
Yes, exactly this. If I didn't care about price at all, I'd exclusively use this model. It functions more like an actual engineer. I'm in the midst of a DB migration, and eg 5.5 continually suggests stuff like "use DB X instead of DB Y for task Z because its 30% faster" which is an impossibility of reality, given we are migrating DBs. Fable jumped in, reduced allocs by literally 46x, found multiple bugs 4.8 and 5.5 created (max file system usage, correctness issues, etc), and continually suggested awesome improvements unprompted. As in, it would finish a task and then suggest we tackle this other existing problem I didn't know about in a very specific manner... this is the first model that feels like its coming for my job.
I will stake the claim, as an engineer never having studied sociology, that in group favoritism is the (only) stable political arrangement by and large… and further, the preservation of any culture necessitates discrimination of some sort.
No one believes or acts like this will be a one time event (on any side of the issue). The history of all new forms of taxation is that eventually it will come for you.
The sovereign wealth fund would be a stakeholder in equities and estates. It would have to exercise voting privileges and be a party to lawsuits. Do you want Trump getting control of the board of eg SpaceX or Meta?
A 6% wealth tax indeed taxes more than the expected rate of return on the base assets. That is indeed equivalent to a higher rate than 100% in terms of an income tax. This math is in favor of PG’s argument.
The expected a priori utility of any social intervention is strictly negative… even if “more thoughtful” does check out in reality for higher ed, $700 billion and 15million man years yearly is rather expensive.
3 10mm bolts failing simultaneously after two decades (on direct it seems) is unexpected! If it were an installation problem, I can’t imagine it would take that long and that they’d all go at the same time. Ditto for corrosion… people take victory whips all the time.
> What type of features did you implement on your 100k LOC week?
I work on 3rd party API integrations, of which, we have hundreds, each in its own repo. We need to build thousands more at a fraction of the cost. Any given integration historically takes a human a few days up to a few months to build and is subject to ongoing maintenance. We frequently do not have access to the API and we mostly never have a representative data set if we do. Complex APIs tend to expose multiple, entwined data models. Documentation may be wrong or in a foreign language.
I've been building a new framework to do it better. Ideally, we can get an agent to spit them out in a few minutes to hours with a much reduced ops burden for managing the fleet, all with very high confidence. The later requires pushing as much into the type system as possible and leveraging static analysis. Much of the work has been embarrassingly parallelizable. Consider categorizing access patterns across the entire set or ensuring byte for byte parity (over the input space of third party API responses).
This is absolutely not a problem that a human or 2 could tackle prior to AI.
> I just can't figure how _how_ to burn that much money a month responsibly.
I always have a few agents (2-5) doing research and working on plans in parallel. A plan is a thorough and unambiguous document describing the process to implement some feature. It contains goals, non-goals, data models, access patterns, explicit semantics, migrations, phasing, requirements, acceptance criteria, phased and final. Plans often require speculative work to formulate. Plans take hours to days to a couple of weeks to write. Humans may review the plans or derived RFCs. Chiefly AI reviews the code (multiple agents with differing prompts until a fixed point is reached between them). Tests and formal methods are meant to do heavy lifting.
In my highest volume weeks, I ship low hundreds of thousands of lines of software not counting changes to deps.
> At a corporate level, I'd much rather hire a junior engineer
Any formulation of problem sufficient for a truly junior engineer to execute is better given to an agent. The solution is cheaper, faster, and likely better. If the later doesn't hold, 10 independent solutions are still cheaper and faster than a junior engineer.
There is no longer any likely path to teaching a junior engineer the trade.