lmeyerov

6 ms·

31.
by lmeyerov 3mo ago
AOP is a big influence for how we are designing hooks, including custom ones, for louie.ai's agent harness. More principled structure to what is already expected. I'm unclear on AOP in general, esp as proposed here. That's a
32.
by lmeyerov 3mo ago
We almost went with Om for our seed round, and he remains on my list of "one of the good ones". It's rare to meet folks where that becomes so apparent so quick.
33.
by lmeyerov 4mo ago
curious how folks like to measure this stuff wrt load testing? We are actively revisiting our traffic simulation approach, and a surprisingly non-obvious part has been which charts to focus on. Our case is a gpu-server-backed interactive an
34.
by lmeyerov 4mo ago
Multiple projects are coming to the same point it seems. Motherduck has been marketing "dives" since the beginning of the year ( https://motherduck.com/blog/duck-dive-and-answer/ ) and in the Louie.ai team
35.
by lmeyerov 4mo ago
Any thoughts on layering on-GPU work stealing or cudf on top? For gfql (graph query language mapping down to cudf calls), we're trying to jettison the hot loop of python->cpu->gpu, so been loosely watching cuTile evolve!
36.
by lmeyerov 4mo ago
I don't have a horse in this race, but for anyone who has worked in it, "science advances one funeral at a time" comes to mind here
37.
by lmeyerov 4mo ago
This is a funny one because it seems less into what fable is being clever on and more about the bitter lesson and data flywheels Our UX agentic engineering flow, as many others, is playwright doing things, and as part of the ux review skill
38.
by lmeyerov 4mo ago
tesla not paying bills: https://www.cnn.com/2025/07/31/us/elon-musk-company-unpaid-l... x not paying bills: https://www.cnbc.com/2023/02/24/musks-twitter-has-been-sued-...
39.
by lmeyerov 4mo ago
? Very much agreed, the IPO pop is a manufactured pricing event focused on investor dynamics rather than direct fair market pricing, making it more of a gamble than normal. Including gambles in index funds defeats the point. Maybe the confu
40.
by lmeyerov 4mo ago
Mostly by having a pulse for the last 10-20 years as someone in the bay area seeing it repeatedly play out as tech IPOs get dumped onto retail investors repeatedly, including the 'good' ones. Being lucky enough to participate in I
41.
by lmeyerov 4mo ago
4-8 quarters for most tech IPOs to settle. IPOs are manufactured for the good times around young co's, so not surprising, and economic stability isn't a question of days/weeks/months. And yes often a falling knife This i
42.
by lmeyerov 4mo ago
R1 work generally doesn't have a replication crisis, and generally incrementalism is the bigger issue there, which is in turn tied to penny pinching The bigger issue is failure to significantly increase r&d funding, vs last decade+
43.
by lmeyerov 4mo ago
Useless russian-troll-style argument: - With no workers working, no worker fraud problem, sure. If you cut core scientific processes, politicize science, and destablize paycheck predictability enough to chase everyone good out of science, t
44.
by lmeyerov 5mo ago
Fwiw, the cost per answer, which is what ultimately matters, is going down. In a competitive market with oss and multiple frontier labs, it is hard to maintain a premium long-term. The big question is how subsidies vs technology improvement
45.
by lmeyerov 5mo ago
oss models don't directly matter when multiple at-scale frontier API providers have to compete on price: they are limited in defensible margin They do matter in that oss researchers enable faster cross-pollination of good inferencing e
46.
by lmeyerov 5mo ago
Not really. Claude Code harness with Sonnet 4.5 model showed you don't really need bigger GPU rollouts, and it's only a matter of time for OSS combos to hit that. Overtime, this will only get better, and the set of enterprise task
47.
by lmeyerov 5mo ago
It's felt awhile similar to what we see in parallel computing: - shift towards throughput-oriented vs latency-oriented. Can juggle more tasks, but increasingly hard to speed up individual ones. - strong scaling is tough. Might even see
48.
by lmeyerov 5mo ago
I think that ship has sailed as well -- botsbench.com shows Sonnet 4.5+ with Claude Code harness does pretty well, and Sonnet roughly tracks the edge of what self-hosted models do on the upper tier of affordable GPUs, like running 1-2 DGX S
49.
by lmeyerov 5mo ago
It's tough. We run botsbench.com , which tracks AI progress on a top CTF, and I gave a talk at CCC a few months ago on our own results doing AI speed runs, so I think about this a lot. In our own trainings we give (AI agents for secur
50.
by lmeyerov 5mo ago
Yep, a few views here: - one wave is code reduction via DRY removals and architectural fixes, and another is adverserial to get rid of false additions, so this helps AI bloat either way - as the other comment says, underspecification is a p
51.
by lmeyerov 5mo ago
Yes, being comprehensive, so early or blatant cheapo findings do not distract from other ones. That's important for base results. Splitting in both file and task is (currently) important. Additionally, we run in a loop until it stops f
52.
by lmeyerov 5mo ago
That feels like true in theory, but in practice, we see the reverse for advanced projects where AI is helping us a lot. A decent chunk of our core IP falls into the bucket you're describing: We have been building a GPU-accelerated grap
53.
by lmeyerov 5mo ago
Yes and no I've seen productivity surveys of senior programmers that share the reverse, and that matches our experience. A common finding is that gardening projects are a lot cheaper now when they're just a few extra terminal tab
54.
by lmeyerov 5mo ago
1. Probably most of https://github.com/simonw , but take care to seperate adopted / semi-professional from exploratory personal work 2. That sounds like your company has a weak engineering culture and is early on its u
55.
by lmeyerov 5mo ago
That's the failure to automate. The AI isn't telepathic, so agentic engineers not automating this stuff is skipping out on the engineering part. You setup the environment and then you do the work. Unless you are switching employer
56.
by lmeyerov 5mo ago
Maybe a failure to automate? The volume of people successfully adopting agentic engineering practices suggests this stuff isn't rocket science, but it is a learned skill and takes setup. A year later into heavy AI coding, my experience
57.
by lmeyerov 5mo ago
> I also don’t think Claude Code is the right harness for this deep and broad scanning work. We find that it struggles to maintain clarity when considering many different bugs at the same time. The skill we do splits it into multiple pas
58.
by lmeyerov 5mo ago
The baseline Claude prompt being compared to feels pretty laughable so not sure what is learned. Maybe compare to a more realistic baseline for the DIY side for more compelling benchmarketing? We started with a DIY code review skill because
59.
by lmeyerov 5mo ago
We did this from the earliest days for louie.ai, which is an adjacent space of Investigations. Sandboxing the LLM was secondary to the primary reason: the threat model for servers. I suspect most people building agentic products are in this
60.
by lmeyerov 5mo ago
I'm curious what flows folks find most productive here? We are a heavy vibe coding team, with heavy review. That has smoothed out for our backend work, but frontend feels much earlier. We have AI driving a usual mix of storybook, penci

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