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Microsoft Amplifier

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Re: Microsoft Amplifier

#131

Post by stillsut »

thethimble wrote: post #115
stillsut wrote: post #110

I've actually written my own a homebrew framework like this which is a.) cli-coder agnostic and b.) leans heavily on git worktrees [0]. 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 gen…

There is a related idea called "alloying" where the 2-4 candidate solutions are pursued in parallel with different models , yielding better results vs any single model. Very interesting ideas. https://xbow.com/blog/alloy-agents

Exactly what I was looking for, thanks.

I've been doing something similiar: aider+gpt-5, claude-code+sonnet, gemini-cli+2.5-pro. I want to coder-cli next.

A main problem with this approach is summarizing the different approaches before drilling down into reviewing the best approach.

Looking at a `git diff --stat` across all the model outputs can give you a good measure of if there was an existing common pattern for your requested implementation. If only one of the models adds code to a module that the others do not, it's usually a good jumping off point to exploring the differing assumptions each of the agents built towards.

Re: Microsoft Amplifier

#132

Post by system2 »

hansmayer wrote: post #85
ramraj07 wrote: post #76

Earlier quoted context omitted.

For some reason youre assuming Im not an engineer which is funny and revealing. 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 spli…

Hey no need to prove yourself to a stranger on the Internet. I'll take your word for it, including your "pretty large team working on it", which for some reason is necessary, although you have "vibe coded 95%" of your application. So if you were to be taken by your word, the LLMs are fantastic and you can do 95% production-ready on your own, just using the LLMs, but for some reason, you'll still need a "pretty large…

[flagged]

Re: Microsoft Amplifier

#133

Post by nine_k »

thethimble wrote: post #117
nine_k wrote: post #108

Earlier quoted context omitted.

As a token of careful attention, run this in a clean VM, properly firewalled not to access the host, your internal network, GitHub or wherever your valuable code lives, and ideally anything but the relevant Anthropic and Microsoft API endpoints.

And even then if you give it Internet access you're at risk of code exfiltration attacks.

Definitely do not give it access to code you are afraid of leaking. Take an open-source code base you're familiar with, and experiment on that.

Re: Microsoft Amplifier

#134

Post by rco8786 »

rs186 wrote: post #92
rco8786 wrote: post #29

A lot of snark in these comments. Has anyone actually tried it yet?

The repo is full of big AI words without any metrics/benchmark. 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’m not blaming them. I’m asking if anyone has tried it.

Re: Microsoft Amplifier

#136

Post by yunnpp »

qlm wrote: post #42
dr_dshiv wrote: post #31

Earlier quoted context omitted.

Based on clear, operational definitions, AI is definitely more creative than humans. E.g., can easily produce higher scores on a Torrance test of divergent thinking. Humans may still be more innovative (defined as creativity adopted into larger systems), though that may be changing.

This is absurd to the point of being comical. Do you really believe that? 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.

His comment must be fueled by his own lack of creativity. He has engulfed himself in the AI, and his own knowledge gap prevents him from even scratching the surface of his own stupidity.

Re: Microsoft Amplifier

#137

Post by ramraj07 »

LtWorf wrote: post #104
ramraj07 wrote: post #76

Earlier quoted context omitted.

For some reason youre assuming Im not an engineer which is funny and revealing. 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 spli…

phd in medical engineering doesn't scream "computer science expert" to me.

[flagged]

Re: Microsoft Amplifier

#138

Post by catlifeonmars »

genghisjahn wrote: post #129
anditherobot wrote: post #127

Earlier quoted context omitted.

Have you tried Scoped context packages? Basically for each task, I create a .md file that includes relevant file paths, the purpose of the task, key dependencies, a clear plan of action, and a test strategy. It’s like a mini local design doc. I found that it helps ground implementation and stabilizes the output of the agents.

I read this suggestion a lot. “Make clear steps, a clear plan of action.” Which I get. But then instead of having an LLM flail away at it could we give to an actual developer? It seems like we’ve finally realized that clear specs makes dev work much easier for LLMs. But the same is true for a human. The human will ask more clarifying questions and not hallucinate. The llm will role the dice and pick a path. Maybe we…

> Maybe we as devs would just rather talk with machines.

This is kind of how I feel. Chat as an interaction is mentally taxing for me.

Re: Microsoft Amplifier

#139

Post by sanex »

danmaz74 wrote: post #95
nightshift1 wrote: post #69

I think that letting an LLM run unsupervised on a task is a good way to waste time and tokens. You need to catch them before they stray too far off-path. I stopped using subagents in Claude because I wasn't able to see what they were doing and intervene. Indirectly asking an LLM to prompt another LLM to work on a long, multi-step task doesn't seem like a good idea to me. I think community efforts should go toward mak…

When the task is bigger than I trust the agent to work on it on its own, or for me to review the results, I ask it to create a plan with steps. Then create a md file for each step. I review the steps, and ask the agent to implement the first one. Review that one, fix it, then ask it to update the next steps, and then implement the next one. And so on, until finished.

I do the same thing with my engineers but I keep the tasks in Jira and I label them "stories".

But in all seriousness +1 can recommend this method.

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