Users are optimistic that AI rewriting code for formal verification will improve models via better data, keep quality scalable as volumes grow, and prompt rethinking of developer practices.
Based on 3 visible X reactions from 1 accounts; directional sample.
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As the quantity of code explodes in the next few years, I hope the folks worrying about quality can rest assured that there’s evidence that our ability to verify even the most casual vibe code can keep up with the amount of slop Turns out that math was the ultimate spec
As a second order effect, the more we use tools like Freerange, the better the AI models become, because we’d feed it more correct code data & better reinforcement learning. What better to teach to AI, if not more practical maths?
I invite you to re-examine your own domain carefully and see whether a tipping point is already here for you: how much of what we do, of our existing “best practice” patterns, should be rewritten to leverage a sufficiently smart coder? Ask your agent; you might be surprised!
But AI doesn’t care; it’ll cut through the thick layers made for humans and rewrite code as fast and as well as needed The sweet spot of what constitutes “good code” is gradually shifting in the age of AI; we’ve been having delayed reactions
Users are optimistic that AI rewriting code for formal verification will improve models via better data, keep quality scalable as volumes grow, and prompt rethinking of developer practices.
Based on 3 visible X reactions from 1 accounts; directional sample.
Ask a question below.
Published answers will appear here.