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Developing with GitHub Copilot Agent Mode and MCP

austen.info

21–30 of 71 posts

Re: Developing with GitHub Copilot Agent Mode and MCP

#21
post #12

Earlier quoted context omitted.

Oh, so Claude in this case was a bandaid over a communication problem (the artists not getting the memo about not suddenly showing up with new equipment that you have to support, with no prior discussion, warning, or heads-up). It absolutely is a game changer. Now the game for you is to deal with whatever equipment they throw at you, because nobody is going to bother consulting you in advance. Just use AI, bro. Good…

Chill Winston! Artists in residency are not know for being technical. They are not divas demanding support but individuals who are supposed to have access to resources, space, and support that allows them to develop as artists. The spaces they are working with often benefit from having talented creatives but this isn't a performance gig we're talking about.

I think it was just an example. The real meat behind the example is what someone said today and that I'm now stealing: AI helps with a faster tech debt generation. Having $anyone asking for $anything in a hurry it's probably the #1 cause of tech debt. If now with AI all the answers are going to be "yes, sure!" well, tech debt will go up.

Re: Developing with GitHub Copilot Agent Mode and MCP

#22
post #4

And again, the most convoluted setup for development with an example that fails to demonstrate why you should adopt such practice. It’s like doing a GDB demo with an hello world program. Or doing Linux From Scratch to show how you can browse the web. The goal of software engineering is not to write code faster. Coding is itself a translation task (and a learning workflow, as you can’t keep everything in your head). W…

I use llms for each of those steps and modeling agent workflows following them has been very successful for me.

I think I’ve become disgruntled with the anti-llm crowd because every objection seems to boil down to “you are doing software engineering wrong” or “you have just described a workflow that is worse than the default”.

Stop for a minute and start from a different premise. There are people out there who know how to deliver software well, have been doing it for decades and find this tooling immensely productivity enhancing. Presume they know as much as you about the industry and have been just as successful doing it.

This person took the time to very specifically outline their workflow and steps in a clear and repeatable way. Rather than trying it and giving feedback in the same specific way you just said they have no idea what they are doing.

Try imagining that they do and it’s you who are not getting the message and see if you get your a different place.

Re: Developing with GitHub Copilot Agent Mode and MCP

#23
post #9
post #6

Earlier quoted context omitted.

I fear for the coming 2 to 3 generation of software engineers. Will they be able to handle problems if the AI is not available or is the source of the problem? Only time will tell.

Same was said about dejanews, stackoverflow etc. and intellisense

Stack overflow didn't create a positive feedback loop where the solution to having to deal with an obscure, badly written, incomprehensible code base is creating an more incomprehensible sloppy code to glue it all together.

Neither did intellisense. If anything, it encouraged structuring your code better so that intellisense would be useful.

Intellisense does little for spaghetti code. And it was my #1 motivation to document the code in a uniform way, too.

The most important impact of tools is that they change the way we think and see the world, and this shapes the world we create with these tools.

When you hold a hammer, everything is a nail, as the saying goes.

And when you hold a gun, you're no longer a mere human; you're a gunman. And the solution space for all sorts of problems starts looking very differently.

The AI debate is not dissimilar to the gun debate.

Yes, both guns and the AI are powerful tools that we have to deal with now that they've been invented. And people wielding these tools have an upper hand over those who don't.

The point that people make in both debates that tends to get ignored by the proponents of these tools is that excessive use of the tools is exacerbating the very problem these tools are ostensibly solving.

Giving guns to all schoolchildren won't solve the problem of high school shootings — it will undeniably make it worse.

And giving the AI to all software developers won't solve the problem of bad, broken code that negatively impacts people who interact with it (as either users or developers).

Finally, a note. Both the gun technology and the AI have been continuously improved since their invention. The progress is undeniable.

Anyone who is thinking about guns in 1850 terms is making a mistake; the Maxim was a game changer. And we're not living in ChatGPT 2.0 times either.

But with all the progress made, the solution space that either tool created hasn't been changing in nature. A problem that wasn't solveable with a flintlock musket or several remains intractable for an AK-74 or an M16.

Improvements in either tech certainly did change the scale at which the tools were applied to resolve all sorts of problems.

And the first half of the 20th century, to this day, provides most of the most brilliant, masterful examples of using guns at scale.

What is also true is that the problems never went away. Nor did better guns made the lives of the common soldier any better.

The work of people like nurse Nightingale did.

And most of that work was that the solution to increasingly devastating battlefield casualties and dropping battlefield effectiveness wasn't giving every soldier a Maxim gun — it was better hygiene and living conditions. Washing hands.

The Maxim gun was a game changer, but it wasn't a solution.

The solution was getting out of the game with stupid prizes (like dying of cholera or typhoid fever). And it was an organizational issue, not a technological one.

* * * * *

To end on a good note, an observation for the AI doomers.

Genocides have predated the guns by millenia, and more people have died by the machete and the bayonet than by any other weapon even in the 20th century. Perhaps the 21st too.

Add disease and famine, and death by gun are a drop in the bucket.

Guns aren't a solution to violence, but they're not, in themselves, a cause of it on a large enough scale.

Mass production of guns made it possible to turn everyone into a soldier (and a target), but the absolute majority of people today have never seen war.

And while guns, by design, are harmful —

— they're also hella fun.

Re: Developing with GitHub Copilot Agent Mode and MCP

#24
I've had success using BrowserMCP

https://browsermcp.io

It really feels magical when the AI agent can browse and click around to understand the problem at hand

Also, sometimes an interactive command can stop agents from doing things. I wrote a small wrapper to always return so agents never stop from working

https://github.com/mohsen1/agentshell

Re: Developing with GitHub Copilot Agent Mode and MCP

#25
post #19
post #12

Earlier quoted context omitted.

Oh, so Claude in this case was a bandaid over a communication problem (the artists not getting the memo about not suddenly showing up with new equipment that you have to support, with no prior discussion, warning, or heads-up). It absolutely is a game changer. Now the game for you is to deal with whatever equipment they throw at you, because nobody is going to bother consulting you in advance. Just use AI, bro. Good…

Excellent point! His approach worked in practice, but it would never work in a theoretical situation where proving a point is more important than just solving the problem, so it's obviously worthless.

"Use the cameras you used last time for this gig, we'll work out something for the next one"

If uttering a sentence like this is a "theoretical" solution for you, I don't know what to tell you, except that you're not going to have a good time in any job until you learn the practicality of saying "no" the hard way.

And if you're living your life where the only "solution" to any problem created by stupidity, miscommunication, and bad planning of other people is saying "yes, sir!” and enabling them to do more if it —

— best of luck growing out of serfdom one day.

Re: Developing with GitHub Copilot Agent Mode and MCP

#26

Earlier quoted context omitted.

OP's comment also seems to be firmly stuck in 2023 when you'd prompt ChatGPT or whatever. The fact that LLMs today, when strapped into an agentic harness, can do or help with all of these things (ideation, architecture, use linters, validate code, evaluate outputs, and a million other things) seems to elude them.

Dothey do requirement gatherings? Like talking to stakeholder and getting their input of what the feature should, translating business jargon to domain terms? No. Do they do the analysis? Removing specs that conflict with each other, validating what's possible in the technical domain and in the business domain? No. Do they help with design? Helping coming up with the changes that impact the current software the least…

I mean, if you "program" (prompt) them to do those stuff, then yeah, they'll do that. But you have to consider the task just like if you handed it over to a person with absolutely zero previous context, and explain what you need from the "requirements gathering", and how it should handle that.

None of the LLMs handle any of those things by themselves, because that's not what they're designed for. They're programmable things that output text, that you can then program to perform those tasks, but only if you can figure out exactly how a human would handle it, and you codify all the things we humans can figure out by ourselves.

Re: Developing with GitHub Copilot Agent Mode and MCP

#27
post #14
post #7

Earlier quoted context omitted.

Unnecessarily critical take on a quality write-up Much of the criticism of AI on HN feels driven by devs who have not fully ingested what is going with MCP, tools etc. right now as not looked deeper than making API calls to an LLM

This is the crypto discussion again. "All our critics are clueless morons who haven't realised the one true meaning of things". Have you once considered that critics have tried these tools in all these combinations and found them lacking in more ways than one?

The huge gap between the people who claim "It helps me some/most of the time" and the other people who claim "I've tried everything and it's all bad" is really interesting to me.

Is it a problem of knowledge? Is it a problem of hype that makes people over-estimate their productivity? Is it a problem of UX, where it's hard to figure out how to use these tools correctly? Is it a problem of the user's skills, where low-skilled developers see lots of value but high-skilled developers see no value, or even negative value sometimes?

The experiences seem so different, that I'm having a hard time wrapping my mind around it. I find LLMs useful in some particular instances, but not all of them, and I don't see them as the second coming of Jesus. But then I keep seeing people saying they've tried all the tools, and all the approaches, and they understand prompting, yet they cannot get any value whatsoever from the tools.

This is maybe a bit out there, but would anyone (including parent) be up for sending me a screen recording of exactly what you're doing, if you're one of the people that get no value whatsoever from using LLMs? Or maybe even a video call sharing your screen?

I'm not working in the space, have no products or services to sell, only curious is why this vast gap seemingly exists, and my only motive would be to understand if I'm the one who is missing something, or there are more effective ways to help people understand how they can use LLMs and what they can use them for.

My email is on my profile if anyone is up for it. Invitation open for anyone struggling to get any useful responses from LLMs.

Re: Developing with GitHub Copilot Agent Mode and MCP

#28

Earlier quoted context omitted.

Chill Winston! Artists in residency are not know for being technical. They are not divas demanding support but individuals who are supposed to have access to resources, space, and support that allows them to develop as artists. The spaces they are working with often benefit from having talented creatives but this isn't a performance gig we're talking about.

I think it was just an example. The real meat behind the example is what someone said today and that I'm now stealing: AI helps with a faster tech debt generation. Having $anyone asking for $anything in a hurry it's probably the #1 cause of tech debt. If now with AI all the answers are going to be "yes, sure!" well, tech debt will go up.

the answer was "yes, sure" before AI too. the difference is whether you're going to do overtime staying up to 2AM trying to make things work.

Re: Developing with GitHub Copilot Agent Mode and MCP

#29
post #25
post #19

Earlier quoted context omitted.

Excellent point! His approach worked in practice, but it would never work in a theoretical situation where proving a point is more important than just solving the problem, so it's obviously worthless.

"Use the cameras you used last time for this gig, we'll work out something for the next one" If uttering a sentence like this is a "theoretical" solution for you, I don't know what to tell you, except that you're not going to have a good time in any job until you learn the practicality of saying "no" the hard way . And if you're living your life where the only "solution" to any problem created by stupidity, miscommun…

> If uttering a sentence like this is a "theoretical" solution for you, I don't know what to tell you, except that you're not going to have a good time in any job until you learn the practicality of saying "no" the hard way.

but no one wants to say no here. the thing is going to happen one way or another, if only because everyone involved is passionate about making sure artists can reach their dreams. if we can't do this, we just close shop.

Re: Developing with GitHub Copilot Agent Mode and MCP

#30
post #4

And again, the most convoluted setup for development with an example that fails to demonstrate why you should adopt such practice. It’s like doing a GDB demo with an hello world program. Or doing Linux From Scratch to show how you can browse the web. The goal of software engineering is not to write code faster. Coding is itself a translation task (and a learning workflow, as you can’t keep everything in your head). W…

I use llms for each of those steps and modeling agent workflows following them has been very successful for me. I think I’ve become disgruntled with the anti-llm crowd because every objection seems to boil down to “you are doing software engineering wrong” or “you have just described a workflow that is worse than the default”. Stop for a minute and start from a different premise. There are people out there who know h…

Criticism is not refutation. It's identifying flaws (subjectively or objectively) . I'm all for it if you can show me that those flaws don't exist or are inconsequential.

Workflows are personal and the only one who can judge them are the one who is paying for the work. At most, we can compare them in order to improve our own personal workflow.

My feedback is maybe not clear enough. But here are the main points:

- Too complicated in regards to the example provided, with the actual benefits for the complication not explained.

- Not a great methodology because the answer to the queries are tainted by the query. Like testing for alcohol by putting the liquid in a bottle of vodka. When I search for something that is not there, I expect "no results" or an error message. Not a mirage.

- The process of getting information, making decisions, and then acting is corrupted by putting it only at some irrelevant moments: Before even knowing anything; When presented with a restricted list of options with no understanding of the factors that play in the restriction; and after the work is done.

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