lmeyerov

13 ms·

151.
by lmeyerov 1y ago
I'm a bit unclear what's different here from how vibe coders already work? Pretty early on folks recognized that most MCPs can just be CLI commands, and a markdown file is fine for describing them. So Claude Code users have markdo
152.
by lmeyerov 1y ago
Senior engineers know process, including for what you described, and that maps to plan-driven AI engineering well: 1. Note the discussion of plan-driven development in the claude code sections (think: plan = granular task list, including go
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by lmeyerov 1y ago
Posted below: GFQL is also OSS and architecturally similar, though slightly different goals and features: https://news.ycombinator.com/item?id=45560036#45561807
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by lmeyerov 1y ago
Reposting: -- Rough news on kuzu being archived - startups are hard and Semih + Prashanth did so much in ways I value! For those left in the lurch for compute-tier Apache Arrow-native graph queries for modern OSS ecosystems, GFQL [1] should
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by lmeyerov 1y ago
That's a cool concept - would be curious about a more common setup for agentic data analysis (ex: for using in Claude Code) like: * Multiple tasks vs 1 * O3/o3-mini + 4o/4o-mini instead of nano * Extra credit: Inside a fixed
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by lmeyerov 1y ago
This is a big problem for many enterprise startups. Most (90%+) are customer funded, not VC funded, and it is common to have a few big design partner customers as they figure it out. Imagine several 3yr $1.5M ($500K/yr) contracts, so a
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by lmeyerov 1y ago
We have been on a fork for louie.ai: * Small data - talk to your PDF on-the-fly etc: Getting bigger & faster via cloud APIs * Big data - for RAG: Getting smaller, bc we don't want to pay crazy fees for vector DB hosting, and doable
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by lmeyerov 1y ago
I like growth-oriented startups in that it is more of a team sport here. The promotion is pretty directly tied to: * Doing your part to make the revenue grow. For management, going from say $1M annual revenue in seed to $3M in A means the c
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by lmeyerov 1y ago
One of the first things I looked at too...
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by lmeyerov 1y ago
Exactly. We often end up doing 'direct' retrieval (ex: DB query gen) to skip the time suck , costs , and insecurity of vector RAG, and per user indexing for the same. Agentic reasoning loops means this can be better quality and f
161.
by lmeyerov 1y ago
We find it useful: * Agents still kinda suck so need the help around context management and avoiding foot guns. Eg, we make a < 500loc ai/readme.md with must haves, links to others, and meta how-to-use * Similar to IaaC, useful to s
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by lmeyerov 1y ago
if you s/counterculture/maker/g , so less about anti and more about doing, i'm with the others -- it's just bigger, with some individual subcommunities having ossified while new topics have opened their own new shin
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by lmeyerov 1y ago
It took me a month , despite having done prompt engineering for work the 2 years prior, to hit the real starting line of Claude code productivity Basically, the ability to order my thoughts into a task list long & clear enough for the L
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by lmeyerov 1y ago
The second link helps It's interesting to wonder if 80% of the question answering can be achieved as a prompts/otel.md over MCPs connected to Claude Code and let agentic reasoning do the rest Ex: * When investigating errors, only
165.
by lmeyerov 1y ago
I don't understand - otel does that unification already. Traces connected to logs etc.. I'm still missing something...
166.
by lmeyerov 1y ago
I'm curious -- let's say we have claude code hooked up to MCPs for jaeger, grafana, and the usual git/gh CLIs it can use out-of-the-box, and we let claude's planner work through investigations with whatever help we give
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by lmeyerov 1y ago
i think he means it's 'just' a thin concat most useful prompt stuff seems 'simple' to implement ultimately, so it's more impressive to me that such a simple idea of TODO goes so far! (agent frameworks ARE hard
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by lmeyerov 1y ago
Sorry to hear that =/ Work for good people with a history of moral dealing. A family member just had a life-changing payout because leadership was generous. A friend walked away from a company pre-pivot without equity for what became o
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by lmeyerov 1y ago
Yes that's how I do Claude code manually, git branch per terminal window, and very rarely multiple agents on the same branch It mostly works, except we don't have a clean flow for docker: shared system daemon & repository mean
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by lmeyerov 1y ago
I used to believe the error rate fallacy, but: 1. Multi-turn agents can correct themselves with more steps, so the reductive error cascade thinking here is more wrong than right in my experience 2. The 99.9% production requirement is so con
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by lmeyerov 1y ago
Totally We do this ~daily for: * Multitier webapps * DevOps infrastructure: docker, aws, ci systems, shell scripts, ... * Analytics & data processing * AI investigations (logs, SIEMs, ..) <--- what we sell! * GPU kernels * Compilers
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by lmeyerov 1y ago
I think he says he checks for both It's interesting as a weaker safety guarantee. He is guaranteeing write integrity, so valid WAL view on restart by throwing out mismatching writes. But from an outside observation, premature signaling
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by lmeyerov 1y ago
Yeah it is also a bit of a shibboleth: vibes coding, when I'm productive for the 80% case with Claude code, is about the LLM cranking for 10-20min. I'm instructing & automating the LLM on how to do its own context management,
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by lmeyerov 1y ago
Thank you, looking forward to reading!
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by lmeyerov 1y ago
Yeah I'm happy to see this, we have been curious as part of figuring out cloud native storage extensions to GFQL (graph dataframe-native query lang), and my intuition was parquet was pluggable here... And this is the first I'm see
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by lmeyerov 1y ago
Gotcha - and yep, I did a small internal natural qualitative experiment with our AI head. It lines up with what I was writing around the benefit being throughput after 2-3 week investment: * Setup: I did a whole cloth clean room rewrite at
177.
by lmeyerov 1y ago
It's a specialist tool. You wouldn't be surprised that it took awhile for someone to take a big to get at typed programming, parallel programming, docker, IaaC, etc. either. We have 2 sibling teams, one the genAI devs and the othe
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by lmeyerov 1y ago
yes, I keep prompt plan logs At the same time... that's not why I'm comfortable writing this. It's pretty obvious when you know what good vs bad feels like here and adjust accordingly: 1. Good: You are able to generate a long
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by lmeyerov 1y ago
As someone has been doing hardcore genai for 2+ years, my experience has been, and what we advise internally: * 3 weeks to transition from ai pairing to AI Delegation to ai multitasking. So work gains are mostly week 3+. That's 120+ ho
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by lmeyerov 1y ago
I like the decision diagram :) The callout on enterprise automation is interesting b/c it's one of the $T sized opportunities that matters most here, and while I think the article is right in the small, I now think quite different

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