Again this "supercharging" nonsense? Maybe in Satiyas confabulated AI-powered universe, but not in the real world I am afraid...
Some people in the organization will experience the limitations and some will learn — although there are bound to be people elsewhere in the organization who have a vested interest in not learning anything and pushing the product regardless.
claude Claude
Interesting given Microsoft’s history with OpenAI
https://techcrunch.com/2025/09/09/microsoft-to-lessen-relian...
This stood out to me too, seems like a months-long project with heavy use of Claude
The Austrian army already switched to LibreOffice for security reasons, we don't need another spyware and code stealing tool.
I would say it’s more the result of anti competitive bundling of cloud things into existing enterprise contracts rather than the wave. Microsoft is far worse than it ever was in the 90s but there’s no semblance of antitrust action in America.
There are many many people who want better AI coding tools, myself included. It might or might not fail, but there is a clear and strong opportunity here, that it would be foolish of any large tech company to not pursue.
If an “objective” test purports to show that AI is more creative than humans then I’m sorry but the test is deeply flawed. I don’t even need to look at the methodology to confidently state that.
You think it is creative because you lack the knowledge of what it has learnt.
This project was in part written by Claude, so for better or worse I think we're at least 3 levels deep here (AI-written code which directs an AI to direct other AIs to write code).
Most models I've benchmarked, even the expensive proprietary models, tend to lose coherence when the context grows beyond a certain size. The thing is, they typically do not need the entire context to perform whatever step of the process is currently going on.
And there appears to be a lot of experimentation going on along the line of having subagents in charge of curating the long term view of the context to feed more focused work items to other subagents, and I find that genuinely intriguing.
My hope is that this approach will eventually become refined enough that we'll get dependable capability out of cheap open weight models. That might come in darn handy, depending on the blast radius of the bubble burst.
If this is restoring the entire context (and looking at the source code, it seems like it is just reloading the entire context) how does this not result in an infinite compaction loop?
1. It affects the fundamental ego of these engineers that a computer can do what they thought only they could do and what they thought made them better than the rest of the population. They might not realize this of course.
2. AI and all these AI systems are intelligence multipliers, with a zero around IQ 100. Zero multiplied by zero is zero, and negative multiplier just leads to garbage. So the people who say "I used AI and its garbage" should really think hard about what it says about them. I thought I was crazy to think of this hypothesis but someone else also mentioned the exact statement and I didnt think I was just being especially mean anymore.
I am an engineer and my vibe coded prototype is now in production, one of the best applications of its type in the industry, and doing really well. So well, I have a pretty large team working on it now. This project was and still is 95% written by AI. No complaints, never going back. That's my experience.
Clearly the eng community is splitting into two categories, people who think this is all never going to work and people who think otherwise. Time will tell who's right.
To anyone else reading and thinking closer to the second side, we're hiring :)
Generally when your investment fails you don’t get paid back, right?
People are correct to question it.
If anything, Microsoft needs to show something meaningful to make people believe it's worth trying it out.
I went through the whole README but couldn't find any hint about this actually making existing agents more effective/accurate or make fewer mistakes.
The whole thing, at the very least, throws the simplicity of existing tools out of the window, and make everything 20x complicated.
I seriously doubt if Microsoft has any objective metrics (benchmarks) -- even cherry-picked ones -- to show this project is not a complete waste of time.
btw the whole repo looks like it's AI generated slop.
[To cowards who downvoted me without leaving a comment: show me some numbers and prove me wrong.]
I see a possible paradox here.
For exploration, my goal is _to learn_. Trying out multiple things is not wasting time, it's an intensive learning experience. It's not about finding what works fast, but understanding why the thing that works best works best. I want to go through it. Maybe that's just me though, and most people just want to get it done quickly.
WARNING: Claude Code running in Bypass Permissions mode │ │ │ │ In Bypass Permissions mode, Claude Code will not ask for your approval before running potentially dangerous commands. │ │ This mode should only be used in a sandboxed container/VM that has restricted internet access and can easily be restored if damaged.
Caution
This project is a research demonstrator. It is in early development and may change significantly. Using permissive AI tools in your repository requires careful attention to security considerations and careful human supervision, and even then things can still go wrong. Use it with caution, and at your own risk.
and
requires careful attention to security considerations and careful human supervision
is a bit orthogonal no?
“Using permissive AI tools [that is, ones that do not ask for your approval] in your repository requires careful attention to security considerations and careful human supervision”. Supervision isn’t necessarily approving every action: it might be as simple as inspecting the work after it’s done. And security considerations might mean to perform the work in a sandbox where it can’t impact anything of value.
This is gaining stars and forks but I don't know if that's just because it's under the github.com/microsoft, and I don't really know how much that means.
I'd rather have the three word message than detailed but wrong messages.
I think I agree with you anyway on average. Most of the time a claude-authored commit message is better than a garbage message.
But it's still a red flag that the project may be filled with holes and not really ready for other people. It's just so easy to vibe your way to a project that works for you but is buggy and missing tons of features for anyone who strays from your use case.
I'd never encourage anyone to blind commit the messages But if they are correct they seem a lot more useful than 90% of commit messages.
I found the biggest mistakes that I've seen other people do are like - they move a file, and the commit message acts like it's a brand new feature they added because the llm doesn't put it together it's just a moved file
But I thought there are lots of agentic systems that loop back and ask for approval every few steps, or after every agent does its piece. Is that not the case?
That's cute
I have a repo that shows you how to do this stuff the correct way that's very easy to adapt, along with a detailed explanation, just do yourself a favor, skip the amateur hour re-implementations and instrument/silo your agents properly: https://sibylline.dev/articles/2025-10-04-hacking-claude-cod...
The secret weapon to this approach is asking for 2-4 solutions to your prompt running in parallel. This helps avoid the most time consuming aspect of ai-coding: reviewing a large commit, and ultimately finding the approach to the ai took is hopeless or requires major revision.
By generating multiple solutions, you can cutdown investing fully into the first solution and use clever ways to select from all the 2-4 candidate solutions and usually apply a small tweak at the end. Anyone else doing something like this?
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