The Ledger, every show
Every statement that passed quotation and attribution checks, across all 44 shows. Pick shows below, then mix any filter with any other.
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every show 44 of 44
Liu: Single Developers Will Build Apps That Currently Require Large Teams
“If your goal is to build software as it exists today, then yes, I think in the future, a single human will be able to build applications that today require large numbers of people to coordinate.”
Liu: Software Teams Will Remain Large as Scope and Ambition Expand
“And so I still think we will have large teams of software developers in the future. They will just You know, each individual will be responsible for far more feature scope than they are today, and the system as a whole will be more sophisticated and more power…”
Beyang Liu: CS fundamentals will grow in importance in AI era
“My, maybe a bit contrarian hot take here is that CS Fundamentals if anything, are gonna grow in importance. You know, the stuff you learn in the coding bootcamp, maybe that gets, you know, automated away, but the fundamentals of knowing, you know, which data s…”
Liu: Cody matches GitHub Copilot completion acceptance rates using open-source StarCoder
“Like today, Cody uses StarCoder for inline completions, and with the benefit of the context that we provide, we actually show, like, comparable completion acceptance rate metrics. It's kind of like the standard metric that folks use to evaluate inline completi…”
Liu: Reliable AI coding workflows require search-based algorithmic backbones
“The way that we get to this, like, more reliable, multi-step workflows that can do things beyond, you know, generate unit test is, is, it's really gonna be, like, a search-based approach, where, where you use an LLM as, kind of, like, an advisor or a proposal …”
Beyang Liu: Statistical learning and convex optimization will re-emerge in AI
“I'm still waiting for the statistical learning and maybe some of the convex optimization stuff to reemerge. I wouldn't count it entirely out yet. I feel like the pendulum always swings back the other way. It's swung away from statistical learning and convex op…”
Liu: AI coding assistants must pull context beyond Git repositories to succeed
“And I don't think the AI developer will be any different. It will need to pull context from all these different sources.”
Liu: Post-hype reality check will expose the limits of AI search techniques
“And I don't know, I think in the next year or two, maybe as like the, as we get past like the peak AI hype, we'll start to see the gap emerge or become more obvious to more people about like how, how, how many of like the newfangled techniques actually work in…”
Liu: All production code AI tools today are developer inner-loop assistants
“And so if you look at the landscape of code AI today, the systems that are actually in production and in use they're all inner loop tools. So anything that is, you know, in your editor doing inline completions or chat, that's kind of assisting you in the proce…”
Liu: AI engineering tools will automate tedious maintenance before complex features
“There will be kind of like a range of issues that can be supported in terms of complexity, right? Like there's certain like bugs and issues that, you know, in whole are kind of a form of toil. Like no one wants to do them because it's kind of like busy work, e…”
Liu: Sourcegraph Cody uses StarCoder 7B, matching larger models with context
“The primary model that Cody uses for inline completions right now is StarCoder seven billion. And with the benefit of context that actually matches the performance of you know, larger proprietary models.”
Beyang Liu: AI will compress boilerplate middleware in software engineering
“I think what AI will do is it will compress the middle because in the middle is really just a lot of, like, abstractions and middleware and other things that are today necessary and today, you know, require a lot of human labor to implement.”