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Which almost feels unique to AI. I can't think of another feature so blatently pushed in your face, other then perhaps when everyone lost their minds and decided to cram mobile interfaces onto every other platform.
> I can't think of another feature so blatently pushed in your face Passkeys. As someone who doesn't see the value of it, every hype-driven company seems to be pushing me to replace OPT 2FA with something worse right now.
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Seems like that is taking a very long time, on top of some very grandiose promises being delivered today.
I look back over the past 2-3 years and am pretty amazed with how quick change and progress have been made. The promises are indeed large but the speed of progress has been fast. Not defending the promise but “taking a very long time” does not seem to be an accurate representation.
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> Depends on team but seems management is pushing it The graphic "Internal structure of tech companies" comes to mind, given if true, would explain why the process/workflow is so different between the teams at Microsoft: https://i.imgur.com/WQiuIIB.png Imagine the Copilot team has a KPI about usage, matching the company OKRs or whatever about making sure the world is using Microsoft's AI enough, so they have a mandat…
Well, what you describe is not terrible way to run things. Eat your own dogfood. To get better at it you need to start doing it.
For example, if tomorrow my company announced that everyone was being switched to Windows, I would simply quit. I don’t care that WSL exists, overall it would be detrimental to my workday, and I have other options.
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This is the future envisioned by Microsoft. Vibe coding all the way down, social network style. They are putting this in front of the developers as take it or leave it deal. I left the platform, doing my coding old way, hosting it somewhere else. Discoverability? I don't care. I'm coding it for myself and hosting in the open. If somebody finds it, nice. Otherwise, mneh.
> I left the platform, doing my coding old way, hosting it somewhere else. may you please let me know where are you hosting the code ? would love to migrate as well. thank you !
You can also self-host a Forgejo instance on a €3/mo Hetzner instance (or a free Oracle Cloud server) if you want. I prefer Hetzner for their service quality and server performance.
The AI agent/programmer corpo push is not about the capabilities and whether they match human or not. It's about being able to externalize a majority of one's workforce without having a lot of people on permanent payroll.
Think in terms of an infinitely scalable bunch of consultants you can hire and dismiss at your will - they never argue against your "vision", either.
With how stochastic the process is it makes it basically unusable for any large scale task. What's the plan? To roll the dice until the answer pops up? That would be maybe viable if there was a way to automatically evaluate it 100% but with a human in the loop required it becomes untenable.
> What's the plan? Call me old school, but I find the workflow of "divide and conquer" to be as helpful when working with LLMs, as without them. Although what is needed to be considered a "large scale task" varies by LLMs and implementation. Some models/implementations (seemingly Copilot) struggles with even the smallest change, while others breeze through them. Lots of trial and error is needed to find that line for…
So eg., one line of code which needed to handle dozens of hard-constraints on the system (eg., using a specific class, method, with a specific device, specific memory management, etc.) will very rarely be output correctly by an LLM.
Likewise "blank-page, vibe coding" can be very fast if "make me X" has only functional/soft-constraints on the code itself.
"Gigawatt LLMs" have brute-forced there way to having a statistical system capable of usefully, if not universally, adhreading to one or two hard constraints. I'd imagine the dozen or so common in any existing application is well beyond a Terawatt range of training and inference cost.
Well, the coding agent is pretty much a junior dev at the moment. The seniors are teaching it. Give it a 100k PRs with senior developer feedback and it'll improve just like you'd anticipate a junior would. There is no way that FANG aren't using the comments by the seniors as training data for their next version. It's a long-term play to have pricey senior developers argue with an llm
Yeah, I'm sure 100k comments with "Copilot, please look into this" and "The test cases are still failing" will massively improve these models.
With how stochastic the process is it makes it basically unusable for any large scale task. What's the plan? To roll the dice until the answer pops up? That would be maybe viable if there was a way to automatically evaluate it 100% but with a human in the loop required it becomes untenable.
> What's the plan? Call me old school, but I find the workflow of "divide and conquer" to be as helpful when working with LLMs, as without them. Although what is needed to be considered a "large scale task" varies by LLMs and implementation. Some models/implementations (seemingly Copilot) struggles with even the smallest change, while others breeze through them. Lots of trial and error is needed to find that line for…