Victor Mota @vimota
co-founder, @coplane - the intelligence layer for the enterprise back office. previously: @Stripe, Google (BigQuery and Kaggle) vimota.me Austin and New York Joined March 2008-
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(If slop was linear, that would mean: instead of adding x lines, it always adds 1.9x, or whatever the constant is. But the slop grows faster than linear, because in addition to the slop for the current change, it also adds slop to interact with and preserve the old slop.)
One thing I love about our model at @coplane : by embedding with our customers to bring AI to their internal operations with our platform we get immediate feedback about how good our “thing that builds things” is at building things and driving ROI!
this dynamic is really crazy right now even things for building other things are getting wrapped with another layer trying to be the access point everyone is flailing, full of anxiety, zero restraint
@charliermarsh Been using it for a couple weeks and it’s been so nice!!
Just like “writing is thinking”, the process of iterating on a problem while coding (agentically or not) crystallizes your understanding of the problem and, as a side effect, the solution.
The problem with the "if it works who cares what the code looks like" mindset for agentic work is that it assumes the agent has a perfect understanding of "works." Realistically, things are underspecified, agents make bad assumptions, etc. To be fair, agents are pretty good at
Revealing admission from Anthropic re the future where all internal software is custom built from scratch. "the principle that the software you build yourself is often the weakest" This is why enterprises will prefer to rely on platforms like @coplane designed with the right primitives to get work done reliably.
@NickVanWig @zeeg -1000 engineer slop canon x.com/vimota/status/…
Skill used to be a natural speed limit to what you could do in software engineering - but that's no longer true. A junior engineer could only write so many lines of code that compiled and worked, and their skill was the rate limiter. As they got better the scope of what they
I want to love Fable, and haven't truly put it through the wringer, but so far it has a lot of the Opus smells I don't like.
@WillManidis I read this originally as Effective Altruists and it still made sense
@polynoamial x.com/vimota/status/…
Assuming the problem is trivially verifiable - wouldn't a better metric be compute-normalized solve rate. Given test-time-compute is a log axis, total compute used to get on average 1 solution for the 0.1 pass@1 (ie. 10x) may be much less than the total for 0.5 (ie. 2x an
@_lopopolo @scaling01 Similarly they never seem to suggest a refactoring! x.com/vimota/status/…
Good articulation of a problem with AI not being self-limiting enough. It feels like we haven't yet given a name to the issue of LLMs being too incremental and reward-hacky rather than pushing back on ideas and suggesting rework of existing code. It feels like the core thing
you can whine about ensloppification or you can take advantage of the generationally low bar that exists for everything now when we post a job opening 9/10 applications are total slop, all it takes is one thoughtful email to get properly looked at - but no one puts in the effort
there's a good chance society does away with factory farming and animal cruelty as AI gives us more empathy for non-human intelligence
@zebulgar 100% this .. something about opus specifically gets people hooked
Another thing: what you get from writing things yourself isn't just the code. It's an improved understanding of what the code does. That mental model is what lets you come up with further improvements, or invent a different way of doing things. You can't come up with ways to improve a blackbox you don't understand. For most projects this doesn't really matter, because the code is the only thing you need. But if you're doing something novel, if you're doing research, the code is not the most important part. Understanding what the code does is the most important part.
@patrickc But sad indeed! Used to love that place
Firebolt just published a fascinating breakdown they completely rebuilt their data warehouse platform architecture with a verifiable agent harness for an agent-centric future. They propose that for the agentic future - one where agents both develop and use the platform - database infrastructure should be monolithic and single tenant. Interestingly, they also rebuilt their catalog and metadata service using the new Ducklake spec in order to benefit from an open standard and a verified oracle.
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