Al Mac

I responded to a cold email I received that same day, and got an automated reply saying that the entire office is on vacation for three weeks.

A new era of PC. 25.0528, 121.5990

Struggling to pick what agent, model, and effort levels to use? Miss the "slot machine" feel of Claude Code when using other tools? `npx slotslop "[prompt]"`

NEW: AI consultant reveals a client accidentally spent $500,000,000.00 in a single month after failing to set employee limits on Claude usage.

The Pope is making exactly our point. LLMs “may imitate or even simulate, but they do not understand.” This is the core epistemic fault line. Most AI evaluation is still based on one assumption: if a system statistically approximates human behaviour, then it is close to human intelligence. But approximation is not intelligence. Simulation is not understanding. LLMs can produce the right answer without knowing why it is right. They can simulate empathy without feeling. They can imitate judgment without responsibility. They can generate coherent explanations without having a world to which those explanations are accountable. Stop confusing behavioural similarity with cognitive equivalence. Human understanding is embodied, affective, relational, motivational, and normative. It is not just the production of plausible text. * Full paper in the first reply

Introducing Claude Opus 4.8: it builds on Opus 4.7 with sharper judgment, more honesty about its own progress, and the ability to work independently for longer than its predecessors. Available today at the same price.

i no longer harbor resentment towards my parents, but there was really no excuse for not setting me up in life. $25 a month in an account from both parents would be $10,800 at 18 to start life with. no interest, high-yield savings, or investments, just $25 funky dollars. im no longer in the business of investing in breaking generational curses or cycles because they weren’t broken for ME!! im only invested in and mind my business when it comes from me because i realized a long time ago, im the person that’s going to save me!! $100 a month from each would be $43,200 $500 a month from each would be $216,000 $1,000 a month from each would be $432,000 sooooo yeaaa there’s no freaking excuse

I've got an agent in a loop optimizing a renderer with the goal to minimize frame times (and tests to measure). It got times down from 88ms to 2ms and allocations down from ~150K to 500. Sounds good, right? Wrong. This is exactly why agent psychosis is a big fucking problem. As an experiment, I rewrote the Ghostty core render state in Go, with access to identically laid out data structures as Ghostty and the exact same validation tests. I made a purposely naive renderer (simple, correct, but slow). 88ms per frame with 150,000 allocations (horrendous, lol)! I then kickstarted a Ralph loop to bring the frame times down. I told it it can't modify input data structures or the public API or tests (they're correct), but it can do anything else it wants. It got to work. It has worked for about 4 hours. I've spent around $350 on this experiment so far. The results? 88ms => 1.5ms 150K allocs => ~500 allocs Incredible right? Nope. My hand-written renderer I ported has frame times (same benchmark) of ~20us (0.020ms) and 0 allocations in the update path. This is the problem with psychosis and lacking systems understanding. If you don't understand the system, you're going to accept that this is an incredible result. If you understand the system, you'll see better solutions immediately and can do roughly 75x better on throughput. The people who blindly trust agent output are in the former camp. They're sheeple, overdrinking from a fountain of mediocrity. Standard disclaimer: I use AI all the time. I like AI. The point I'm making is to not blindly accept results. Think. Analyze. Learn.