Mario Zechner
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17 October
16 October
From one piece @badlogicgames on X 2 beliefs · x.com
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and agents currently still suck at the software writing human skill of colaborating with another human to understand their wants and translate them to a program.
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and until we can encode that agents for writing programs will likely only be effective in the hands of software writing humans, or very technically minded humans.
15 October
5 October
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what the world really wants and needs is an official, well maintained and capable gdrive/gmail mcp.
1 October
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and i want you to know that i never liked rust before it was cool.
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you can go to a restaurant and look at and eat food. but only if you cook yourself some small stuff will you actually know food.
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New modes of interaction with agents are neededTheir words
100% agree that we need new modes of interaction with agents.
30 September
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18 September
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You often only understand a problem by experiencing the journey of building a solution for it.Their words
you often only understand a problem by experiencing the journey, i.e. building a solution for it.
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SOTA frontier models will still fuck you up bad behind your back, especially if you don't read your code anymore.
17 September
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jev is basically a general purpose classifier. and i think that is amazing.
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From one piece Thoughts on slowing the fuck down 5 beliefs · mariozechner.at
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Worse, you realize that the gazillions of unit, snapshot, and e2e tests you had your clankers write are equally untrustworthy. The only thing that's still a reliable measure of "does this work" is manually testing the product.
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You can give it a Bash tool so it can ripgrep its way through the codebase. You can give it some queryable codebase index, an LSP server, a vector database. In the end it doesn't matter much. The bigger the codebase, the lower the recall. Low recall means that your agent will, in fact, not find all the code it needs to do a good job.
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And organizations have super high pain tolerance. But human-made enterprise codebases take years to get there. The organization slowly evolves along with the complexity in a demented kind of synergy and learns how to deal with it. With agents and a team of 2 humans, you can get to that complexity within weeks.
+ 2 more
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With an orchestrated army of agents, there is no bottleneck, no human pain. These tiny little harmless booboos suddenly compound at a rate that's unsustainable. You have removed yourself from the loop, so you don't even know that all the innocent booboos have formed a monster of a codebase. You only feel the pain when it's too late.
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An agent has no such learning ability. At least not out of the box. It will continue making the same errors over and over again. Depending on the training data it might also come up with glorious new interpolations of different errors.
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