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Am I the only one super confused about how to even get started trying out this stuff? Just so I wouldn't be "that critic who doesn't try the stuff he criticizes," I tried GitHub Copilot and was kind of not very impressed. Someone on HN told me Copilot sucks, use Claude. But I have no idea what the right way to do it is because there are so many paths to choose.

Let's see: we have Claude Code vs. Claude the API vs. Claude the website, and they're totally different from each other? One is command line, one integrates into your IDE (which IDE?) and one is just browser based, I guess. Then you have the different pricing plans, Free, Pro, and Max? But then there's also Claude Team and Claude Enterprise? These are monthly plans that only work with Claude the Website, but Claude Code is per-request? Or is it Claude API that's per-request? I have no idea. Then you have the models: Claude Opus and Claude Sonnet, with various version numbers for each?? Then there's Cline and Cursor and GOOD GRIEF! I just want to putz around with something in VSCode for a few hours!



I'm not sure what's complicated about what you're describing? They offer two models and you can pay more for higher usage limits, then you can choose if you want to run it in your browser or in your terminal. Like what else would you expect?

Fwiw I have a Claude pro plan and have no interest in using other offerings so I'm not sure if they're super simple (one model, one interface, one pricing plan)?


When people post this stuff, it's like, are you also confused that Nike sells shoes AND shorts AND shirts, and there's different colors and skus for each article of clothing, and sometimes they sell direct to consumer and other times to stores and to universities, and also there's sales and promotions, etc, etc?

It's almost as if companies sell more than one product.

Why is this the top comment on so many threads about tech products?


In this case, they tried something and were told they were doing it wrong, and they know there's more than one way to do it wrong - wrong model, wrong tool using the model, wrong prompting, wrong task that you're trying to use it for.

And of course you could be doing it right but the people saying it works great could themselves be wrong about how good it is.

On top of that it costs both money and time/effort investment to figure out if you're doing it wrong. It's understandable to want some clarity. I think it's pretty different from buying shoes.


> I think it's pretty different from buying shoes.

Shoe shopping is pretty complex, more so than trialing an AI model in my opinion.

Are you a construction worker, a banker, a cashier or a driver? Are you walking 5 miles everyday or mostly sedentary? Do you require steel toed shoes? How long are you expecting them to last and what are you willing to pay? Are you going to wear them on long runs or take them river kayaking? Do they need to be water resistant, waterproof or highly breathable? Do you want glued, welted, or stitch down construction? What about flat feet or arch support? Does shoe weight matter? What clothing are you going to wear them with? Are you going to be dancing with them? Do the shoes need a break in period or are they ready to wear? Does the available style match your preferences? What about availability, are you ok having them made to order or do you require something in stock now?

By comparison I can try 10 different AI services without even needing to stand up for a break while I can't buy good dress shoes in the same physical store as a pair of football cleats.


> Shoe shopping is pretty complex, more so than trialing an AI model in my opinion.

Oh c'mon, now you're just being disingenuous, trying to make an argument for argument's sake.

No, shoe shopping is not more complicated than trialing a LLM. For all of those questions about shoes you are posing, either a) a purchaser won't care and won't need to ask them, or b) they already know they have specific requirements and will know what to ask.

With an LLM, a newbie doesn't even know what they're getting into, let alone what to ask or where to start.

> By comparison I can try 10 different AI services without even needing to stand up for a break

I can't. I have no idea how to do that. It sounds like you've been following the space for a while, and you're letting your knowledge blind you to the idea that many (most?) people don't have your experience.


Just play with the 'free tier' on whatever website does the AI thing and figure it out.

Maybe there's a need to try ten different ones but I just stuck with one and can now convince it to do what I want it to do pretty successfully.


It sounds like you're generally unfamiliar with using AI to help you at all? Or maybe you're also being disingenuous? It's insanely easy to figure this stuff out, I literally know a dozen people who are not even engineers, have no programming experience, who use these tools. Here's what Claude (the free version at claude.ai) said in response to me saying "i have no idea how to use AI coding assistants, can you succinctly explain to me what i need to do? like, what do i download, run, etc in order to try different models and services, what are the best tools and what do they do?":

Here's a quick guide to get you started with AI coding assistants:

## Quick Start Options (Easiest)

*1. Web-based (Nothing to Download)* - *Claude.ai* - You're here! I can help with code, debug, explain concepts - *ChatGPT* - Similar capabilities, different model - *GitHub Copilot Chat* - Web interface if you have GitHub account

*2. IDE Extensions (Most Popular)* - *Cursor* - Full VS Code replacement with AI built-in. Download from cursor.com, works out of the box - *GitHub Copilot* - Install as VS Code/JetBrains extension ($10/month), autocompletes as you type - *Continue* - Free, open-source VS Code extension, lets you use multiple models

*3. Command Line* - *Claude Code* - Anthropic's terminal tool for autonomous coding tasks. Install via `npm install -g @anthropic-ai/claude-code` - *Aider* - Open-source CLI tool that edits files directly

## What They Do

- *Autocomplete tools* (Copilot, Cursor) - Suggest code as you type, finish functions - *Chat tools* (Claude, ChatGPT) - Explain, debug, design systems, write full programs - *Autonomous tools* (Claude Code, Aider) - Actually edit your files, make changes across codebases

## My Recommendation to Start

1. Try *Cursor* first - download it, paste in some code, and ask it questions. It's the most beginner-friendly 2. Or just start here in Claude - paste your code and I can help debug, explain, or write new features 3. Once comfortable, try GitHub Copilot for in-line suggestions while coding

The key is just picking one and trying it - you don't need to understand everything upfront!


Ya know, in the over half a century I've been on this planet, choosing a new pair of shoes is so low on my 'life's little annoyances' list that it doesn't even rise above the noise of all the stupid random things which actually do annoy me.

Maybe the problem is I don't take shoes seriously enough? Something to work on...


You also learned about your shoe needs over the course of a lifetime. A caregiver gave you your first pair and you were expected to toddle around at most with them. You outgrew and replaced shoes as a child, were placed into new scenarios requiring different footwear as you grew up, learning and forming opinions about what's appropriate functionally, socially, economically as you went. You learned what stores were good for your needs, what brands were reputable, what styles and fits appealed to you. It took you more than a decade at minimum to achieve that.

If you allow yourself to be a novice and a learner with AI and LLMs and don't expect to start out as a "shoe expert" where you never even think about this in your life and it's not even an annoyance, you'll find that it's the exact same journey.


And in all the years that LLMs have been available I've yet to find a subscription plan confusing.


Is it though? People complain about sore feet and hear they wear the wrong kind of shoes so they go to the store where they have to spend money to find out while trying to navigate between dress shoes, minimal shoes, running shoes, hiking shoes etc etc., they have to know their size, ask for assistance in trying them on...


Because the offerings are not simple. Your Nike example is silly; everyone knows what to do with shoes and shorts and shirts, and why they might want (or not want) to buy those particular items from Nike.

But for someone who hasn't been immersed in the "LLM scene", it's hard to understand why you might want to use one particular model of another. It's hard to understand why you might want to do per-request API pricing vs. a bucketed usage plan. This is a new technology, and the landscape is changing weekly.

I think maybe it might be nice if folks around here were a bit more charitable and empathetic about this stuff. There's no reason to get all gatekeep-y about this kind of knowledge, and complaining about these questions just sounds condescending and doesn't do anyone any good.


> Why is this the top comment on so many threads about tech products?

Because you overestimate the difference that the representative person understands.

A more accurate analogy is that Nike sells green-blue shoes and Nike sells blue-green shoes, but the blue-green shoes add 3 feet to your jump and green-blue shoes add 20 mph to your 100 yard dash sprint.

You know you need one of them for tomorrow's hurdles race but have no idea which is meaningful for your need.


Also, the green-blue shoes charge per-step, but the blue-green shoes are billed monthly by signing up for BlueGreenPro+ or BlueGreenMax+, each with a hidden step limit but BlueGreenMax+ is the one that gives you access to the Cyan step model which is better; plus the green-blue shoes are only useful when sprinting, but the blue-green shoes can be used in many different events, but only through the Nike blue-green API that only some track&field venues have adopted...


When you walk into a store, you can see and touch all of these products. It's intuitive.

With all this LLM cruft all you get is essentially the same old chat interface that's like the year 2000 called and wants its on-line chat websites back. The only thing other than a text box that you usually get is a model selector dropdown squirreled away in a corner somewhere. And that dropdown doesn't really explain the differences between the cryptic sounding options (GPT-something, Claude Whatever...). Of course this confuses people!


Claude.ai, ChatGPT, etc. are finished B2C products. They're black boxes, encapsulated experiences. Consumers don't want to pick a model, or know what model they're using; they just want to "talk to AI", and for the system to know which model is best to answer any given question. I would bet that for these companies, if their frontend observes you using the little model override button, that gets instrumented as an "oops" event in their metrics — something they aim to minimize.

What you're looking for, are the landing pages of the B2B API products underlying these B2C experiences. That would be https://www.anthropic.com/claude, https://openai.com/api/, etc. (In general, search "[AI company] API".)

From those B2B landing pages, you can usually click through to pages with details about each of their models.

Here's the model page corresponding to this news announcement, for example: https://www.anthropic.com/claude/opus

(Also, note how these B2B pages are on the AI companies' own corporate domains; whereas their B2C products have their own dedicated domains. From their perspective, their B2C offerings are essentially treated as separate companies that happen to consume their APIs — a "reference use-case" — rather than as a part of what the B2B company sells.)


Hey, I'm open to the idea that I'm just stupid. But, if people in your target market (software developers) don't even understand your product line and need a HOWTO+glossary to figure it out, maybe there's also a branding/messaging/onboarding problem?


My hot take is that your friend should show you what they’re using, not just dismiss Copilot and leave you hanging!


Eh, this seems like a take that reeks a bit of "everyone is stupid except me".

I do know the answer to OP's question but that's because I pickle my brain in this stuff. It is legitimately confusing.

The analogy to different SKUs strikes me also inaccurate. This isn't the difference between shoes, shirts, and shorts - it's more as if a company sells three t-shirts but you can't really tell what's different about them.

It's Claude, Claude, and Claude. Which ones code for you? Well, actually, all of them (Code, web/desktop Claude, and the API can all do this)

Which ones do you ask about daily sundry queries? Well, two of them (web/desktop Claude, but also the API, but not Code). Well, except if your sundry query is about a programming topic, in which case Code can also do that!

Ok, if I do want to use this to write code, which one should I use? Honestly, any of them, and the company does a poor job of explaining why you would use each option.

"Which of these very similar-seeming t-shirts should I get?" "You knob. How are posts like this even being posted." is just an extremely poor way to approach other people, IMO.


> It's Claude, Claude, and Claude. Which ones code for you?

Thanks for articulating the confusion better than I could! I feel it's a similar branding problem as other tech companies have: I'm watching Apple TV+ on my Apple TV software running on my Apple TV connected to my Google TV that isn't actually manufactured by Google. But that Google TV also has an Apple TV app that can play Apple TV+.


It's a bit worse than a branding problem honestly, since there's legitimate overlap between products, because ultimately they're different expressions of the same underlying LLMs.

I'm not sure if you ever got a good rundown, but the tl;dr is that the 3 products ("Desktop", Code, and API) all expose the same underlying models, but are given different prompts, tools, and context management techniques that make them behave fairly differently and affect how you interact with them.

- The API is the bare model itself. It has some coding ability because that's inherent to the model - you can ask it to generate code and copy and paste it for example. You normally wouldn't use this except that if you're using some Copilot-type IDE integration where the IDE is doing the work of talking to the model for you and integrating it into your developer experience. In that case you provide API key and the IDE does the heavy lifting.

- The desktop app is actually a half-decent coder. It's capable of producing specific artifacts, distinguishing between multiple "files" it's writing for you, and revisiting previously-written code. "Oh, actually rewrite this in Go." is for example a thing it can totally do. I find it useful for diagnosing issues interactively.

- "Claude Code" is a CLI-only wrapper around the model. Think of it like Anthropic's first-party IDE integration, except there's not an IDE, just the CLI. In this case the integration gives the tool broad powers to actually navigate your filesystem, read specific files, write to specific files, run shell commands like builds and tests, etc. These are all functions that an IDE integration would also give you, but this is done in a Claude-y way.

My personal take is: try Claude Code, since as long as you're halfway comfortable with a CLI it's pretty usable. If you really want a direct IDE integration you can go with the IDE+API key route, though keep in mind that you might end up paying more (Claude Code is all-you-can-eat-with-rate-limits, where API keys will... just keep going).


Wow. After 50 replies to what I thought wasn't such a weird question, your rundown is the most enlightening. Thank you very much.


FWIW it's probably because a lot of us have been following along and trying these things from the start so the nuances seem more obvious but also I feel that some folks feel your question is a bit "stupid", like "why are you suddenly interested in the frontier of these models? where were you for the last 2 years?"

And to some extent it is like the PC race. Imagine going to work and writing software for whatever devices your company writes software for in whatever toolchain your company uses. Then 2-3 years after the PC race began heating up, asking "Hey I only really write code for whatever devices my employer gives me access to. Now I want to buy one of these new PCs but I don't really understand why I'd choose an Intel over a Motorolla chipset or why I'd prioritize more ROM or more RAM, and I keep hearing about this thing called RISC that's way better than CISC and some of these chips claim to have different addressing modes that are better?"


Also when it comes to API integrations, I find some better than others. Copilot has been pretty crummy for me but Zed's Agent Mode seems to be almost as good as Claude Code. I agree with the general take that Claude Code is a good default place to start.


Claude Code running in a terminal can connect to your IDE so you can review its proposed changes there. I’ve found this to be a nice drop in way to try it out without having to change your core workflow and tools too much. Check out the /ide command for details.


If anything, Anthropic has the product lineup that makes the most sense. Higher numbers mean better model. Haiku < Sonnet < Opus which translates to length/size. Free < Pro < Max.

Contrast to something like OpenAI. They've got gpt4.1, 4o, and o4. Which of these are newer than one another? How do people remember which of o4 and 4o are which?


Which Nike shoe is best for basketball? The Nike Dunk, Air Force 1, Air Jordan, LeBron 20, LeBron XXI Prime 93, Kobe IX elite, Giannis Freak 7, GT Cut, GT Cut 3, GT Cut 3 Turbo, GT Hustle 3, or the KD18?

At least with those you can buy whatever you think is coolest. Which Claude model and interface should the average programmer use?


What's the average programmer? Is it someone who likes CLI tools? Or who likes IDE integration? Different strokes for different folks and surely the average programmer understands what environment they will be most comfortable in.


> Different strokes for different folks and surely the average programmer understands what environment they will be most comfortable in.

That's a silly claim to me, we're talking about a completely new environment where you prompt an AI to develop code, and therefore an "average programmer" is unlikely to have any meaningful experience or intuition with this flow. That is exactly what GP is talking about - where does he plug in the AI? What tradeoffs are there to different options?

The other day I had someone judge me for asking this question by dismissively saying "dont say youve still been using ChatGPT and copy/paste", which made me laugh - I don't use AI at all, so who was he looking down on?


To me that's the silly argument. How many different tools have you ever used? New build system? New linter? How did you know if you wanted to run those on the command line or in your IDE?

And it seems the story you shared sort of proves the point: the web interface worked fine for you and you didn't need to question it until someone was needlessly rude about it.


> How many different tools have you ever used? New build system? New linter? How did you know if you wanted to run those on the command line or in your IDE?

In what way is this analogous? Running scripts is vastly different than AI codemod. I could easily answer how when and why a build system would be plugged in, and linting and formatting are long-established pathways.

On the flipside there are barely even established practices, let alone best ones, for using AI. The point being offered is that AI companies offer shockingly little guidance on how to use their apparently amazing tool.

I personally have never used AI to author code, so I don't really know how the story I provided proves anything to you. I like it to answer questions about why something isn't working to help give me some leads, and it is good at telling you how to use a new framework quickly, but that's a pretty different practice than it authoring code. Seems like you're kinda dodging the question too.


The environment isn't the only difference, it's not "do you prefer CLI or IDE or Web" because they behave differently. Claude Code and Claude web and Claude through Cursor won't give you identical outputs for the same question.

It's not like running a tool in your IDE or CLI where the only difference is the interface. It would be like if gcc ran from your IDE had faster compile times, but gcc run from the CLI gives better optimizations.

The fact that no one is recommending any baseline to start with proves the point that it's confusing. And we haven't even touched on Sonnet v Opus


Because few seem to want to expend the effort to dive in and understand something. Instead they want the details spoonfed to them by marketing or something.

I absolutely loathe this timeline we're stuck in.


This is like being told to buy Nike shoes. Then when you proudly display your new cleats, they tell you "no, I meant you should by basketball shoes. The cleats are terrible."


Because I think that claude has gone beyond tech niche at this point..

Or maybe that's me, but still whether its through the likes of those vibe coding apps like lovable bolt etc.

at the end of the day, Most people are using the same tool which is claude since its mostly superior in coding (questionable now with oss models, but I still use it through kiro).

People expect this stuff to be simple when in reality its not and there is some frustation I suppose.


Not sure is this is sarcasm I'm assuming not.

You're comparing well understood products that are wildly different to products with code names. Even someone who has never wore a t-shirt will see it on a mannequin and know where it goes.

I'm sorry but I cannot tell what the difference is between sonnet and opus. Unless one is for music...

So in this case you read the docs. Which is, in your analogy, you going to the Nike store and reading up on if a tshirt goes on your upper or lower body.


Surely anyone interested in taking out a Claude subscription knows broadly what they're going to use an LLM for.

It's more like going to the Nike store and asking about the difference between the Vaporfly 3 and the Pegasus 41. I know they're all shoes and therefore go on my feet, but I don't know what the difference is unless one is better for riding horses?


On the contrary, I'm confused about why you're confused.

This is a well-known and documented phenomenon - the paradox of choice.

I've been working in machine learning and AI for nearly 20 years and the number of options out there is overwhelming.

I've found many of the tools out there do some things I want, but not others, so even finding the model or platform that does exactly what I want or does it the best is a time-consuming process.


You need Claude Pro or Max. The website subscription also allows you to use the command line tool—the rate limits are shared—and the command line tool includes IDE integration, at least for VSCode.

Claude Code is currently best-in-class, so no point in starting elsewhere, but you do need to read the documentation.


> You need Claude Pro or Max.

Actually, to try it out, prepaid token billing is fine. You are not required to have a subscription for claude code cli. Even just $5 gave me enough breathing room to get a feeling for its potential, personally. I do not touch code often these days so I was relieved not to have to subscribe and cancel again just to play around a little and have it write some basic scripts for me.


Correct. Claude Code Max with Opus. Don’t even bother with Sonnet.


I wouldn't be too prescriptive. I have Pro, and it's fine. I'm not an incredibly heavy user (yet?); I've hit the rate limits a couple times, but not to the point where I'm motivated to spend more.

I haven't tried it myself, but I've heard from people that Opus can be slow when using it for coding tasks. I've only been using Sonnet, and it's performed well enough for my purposes.


Sonnet works fine in many cases. Opus is smarter, and custom 'agents' can be set to use either.

I prefer configuring it to use Sonnet for things that don't require much reasoning/intelligence, with Opus as the coordinator.


Opus is slow, so sessions should be used in parallel, likely across work trees. You shouldn't sit and wait on an Opus agent.


> use Claude. But I have no idea what the right way to do it is because there are so many paths to choose.

Anthropic has this useful quick start guide: https://docs.anthropic.com/en/docs/claude-code/quickstart


What exactly did you try with GitHub copilot? It’s not an LLM itself, just in interface for an LLM. I have copilot in my professional GitHub account and I can choose between chat-gpt and Claude.


Claude Code has two usage modes: pay-per-token or subscription. Both modes are using API under the hood, but with subscription mode you are only paying a fixed amount a month. Each subscription tier has some undisclosed limits, cheaper plans have lower usage limits. So I would recommend paying $20 and trying the Claude Code via that subscription.


I’m looking for cursor alternatives after confusing pricing changes. Is Claude code an option? Can be integrated on an editor/ide for similar results?

My use case so far is usually requesting mechanic work I would rather describe than write myself like certain test suites, and sometimes discovery on messy code bases.


Claude Code is really good for this situation.

If you like an IDE, for example VS Code you can have the terminal open at the bottom and run Claude Code in that. You can put your instructions there and any edits it makes are visibile in the IDE immediately.

Personally I just keep a separate terminal open and have the terminal and VSCode open on two monitors - seems to work OK for me.


No Opus in the $20 tier though sadly


As far as I can tell - that seems to have changed today!


Actually I think I was wrong, the PR material was just vague about it.


What does Opus do extra?


It's a much larger, more capable LLM than Claude Sonnet.


I mean day to day. How is the coding experience different?


VSCode has a pretty good Gemini integration - it can pull up a chat window from the side. I like to discuss design changes and small refactorings ("I added this new rpc call in my protobuf file, can you go ahead and stub out the parts of code I need to get this working in these 5 different places?") and it usually does a pretty darn good job of looking at surrounding idioms in each place and doing what I want. But gemini can be kind of slow here.

But I would recommend just starting using Claude in the browser, talk through an idea for a project you have and ask it to build it for you. Go ahead and have a brain storming session before you actually ask it to code - it'll help make sure the model has all of the context. Don't be afraid to overload it with requirements - it's generally pretty good at putting together a coherent plan. If the project is small/fits in a single file - say a one page web app or a complicated data schema + sql queries - then it can usually do a pretty good job in one place. Then just copy+paste the code and run it out of the browser.

This workflow works well for exploring and understanding new topics and technologies.

Cursor is nice because it's an AI integrated IDE (smoother than the VSCode experience above) where you can select which models to use. IMO it seems better at tracking project context than Gemini+VSCode.

Hope this helps!


Claude Code is the superior interface in my opinion. Definitely start there.


Lets see: We have GitHub, and GitHub Enterprise Server, and a GitHub API. Then there's the command line and a desktop version, and one that is just browser based I guess. Then you have different pricing plans, Free, Team, and Enterprise? How is Enterprise different than GitHub Enterprise Server? It's very easy to find evidence to confirm our bias.

Claude code is actually one of the most straightforward products I've used as far as onboarding goes. You download the tool, and follow the instructions. You can use one of the 3 plans, and everything else is automatic. You can figure out token usage and what models and versions to use and how to use MCP servers and all of that -- there's a lot of power -- but you don't need to do ANY of that to get started trying it out.

You're not being:

> That critic who doesn't try the stuff he criticizes

You're being:

> That critic who is trying to confirm their biases


Download Claude Code

Create a new directory in your terminal

Open that directory, type in "Claude" to run Claude

Press Shit + Tab to go into planning mode

Tell Claude what you want to build - recommend something simple to start with. Specify the languages, environment, frameworks you want, etc.

Claude will come up with a plan. Modify the plan or break it into smaller chunks if necessary

Once plan is approved, ask it to start coding. It will ask you for permissions and give you the finished code

It really is something when you actually watch it go.


Yes. You basically need an LLM to provide guidance on product selection in this brave new world.

It is actually one of my most useful use cases of this tech. Nice to have a way to ask in private so you don’t get snarky answers like: it’s just like buying shoes!


Cursor + Claude 4 = best quality + UX balance. Pay up for 20/month subscription.

Cursor imports in your VSCode setup. Setting it up should be trivial.

Use Agent mode. Use it in a preexisting repo.

You're off the races.

There is a lot more you can do, but you should start seeing value at this point.


If you're looking for a coding assistant, get Claude Code, and give it a try. I think you need the Pro plan at a minimum for that ($20/mo; I don't think Free includes Claude Code). Don't do the per-request API pricing as it can get expensive even while just playing around.

Agree that the offering is a bit confusing and it's hard to know where to start.

Just FYI: Claude Code is a terminal-based app. You run it in the working directory of your project, and use your regular editor that you're used to, but of course that means there's no editor integration (unlike something like Cursor). I personally like it that way, but YMMV.


Claude Code CLI.


Thanks. With the CLI, can you get Copilot-ish things like tab-completion and inline commands directly in your IDE? Or do you need to copy/paste to and from a terminal? It feels like running a command on the IDE and then copying the output into your IDE is a pretty primitive way to operate.


My advice is this:

1) Completely separate in your mind the auto-completion features from the agentic coding features. The auto-completion features are a neat trick but I personally find those to be a bit annoying overall, even if they sometimes hit it completely right. If I'm writing the code, I mostly don't want the LLM autocompletion.

2) Pay the $20 to get a month of Claude Pro access and then install Claude Code. Then, either wait until you have a small task in mind or your stuck on some stupid issue that you've been banging your head on and then open your terminal and fire up Claude Code. Explain to it in plain English what you want it to do. Pretend it's a colleague that you're giving a task to over Slack. And then watch it go. It works directly on your source code. There is no copying and pasting code.

3) Bookmark the Claude website. The next time you'd Google something technical, ask it Claude instead. General questions like "how does one typically implement a flizzle using the floppity-do framework"? "I'm trying to accomplish X, what are my options when using this stack?". General questions like that.

From there you'll start to get it and you'll get better at leverage the tool to do what you want. Then you can branch out the rest of the tool ecosystem.


Interesting about the auto-completion. That was really the only Copilot feature I found to be useful. The idea of writing out an English prompt and telling Copilot what to write sounded (and still sounds) so slow and clunky. By the time I've articulated what I want it to do, I might as well have written the code myself. The auto-completion was at least a major time-saver.

"The card game state is a structure that contains a Deck of cards, represented by a list of type Card, and a list of Players, each containing a Hand which is also a list of type Card, dealt randomly, round-robin from the Deck object." I could have input the data structure and logic myself in the amount of time it took to describe that.


I think you should embrace a bit of ambiguity. Don't treat this like a stupid computer where you have to specify everything in minute detail. Certainly the more detail you give, the better to an extent. But really: Treat it like you're talking to a colleague and give it a shot. You don't have to get it right on the first prompt. You see what it did and you give it further instructions. Autocomplete is the least compelling feature of all of this.

Also, I don't remember what model Copilot uses by default, especially the free version, but the model absolutely makes a difference. That's why I say to spend the $20. That gives you access to Sonnet 4 which is where, imo, these models took a giant leap forward in terms of quality of output.


Is Opus as big a leap as sonnet4 was?


Thanks, I shall give it a try.


One analogy I have been thinking about lately is GPUs. You might say "The amount of time it takes me to fill memory with the data I want, copy from RAM to the GPU, let the GPU do it's thing, then copy it back to RAM, I might as well have just done the task on the CPU!"

I hope when I state it that way you start to realize the error in your thinking process. You don't send trivial tasks to the GPU because the overhead is too high.

You have to experiment and gain experience with agent coding. Just imagine that there are tasks where the overhead of explaining what to do and reviewing the output are dwarfed by the actual implementation. You have to calibrate yourself so you can recognize those tasks and offload them to the agent.


There's a sweet spot in terms of generalization. Yes, painstakingly writing out an object definition in English just so that the LLM can write it out in Java is a poor use of time. You want to give it more general tasks.

But not too general, because then it can get lost in the sauce and do something profoundly wrong.

IMO it's worth the effort to know these tools, because once you have a more intuitive sense for the right level of abstraction it really does help.

So not "make this very basic data structure for me based on my specs", and more like "rewrite this sequential logic into parallel batches", which might take some actual effort but also doesn't require the model to make too many decisions by itself.

It's also pretty good at tests, which tends to be very boilerplate-y, and by default that means you skip some cases, do a lot of brain-melting typing, or copy-and-paste liberally (and suffer the consequences when you missed that one search and replace). The model doesn't tire, and it's a simple enough task that the reliability is high. "Generate test cases for this object, making sure to cover edges cases A, B, and C" is a pretty good ROI in terms of your-time-spent vs. results.


Is there any more agent-oriented approach where it just push/pulls a git repo like a normal person would, instead of running it on my machine? I'd like to keep it a bit more isolated and having it push/pull its own branches seems tidier.


Claude does the coding, and edits your files. You just sit back and relax. You don't do any tab completion etc.


> I just want to putz around with something in VSCode for a few hours!

I just googled "using claude from vscode" and the first page had a link that brought me to anthropic's step by step guide on how to set this up exactly.

Why care about pricing and product names and UI until it's a problem?

> Someone on HN told me Copilot sucks, use Claude.

I concur, but I'm also just a dude saying some stuff on HN :)


If you want your own cheap IDE integration, you can set up VSCode with Continue extension, ollama running locally, and a small agent model. https://docs.continue.dev/features/agent/model-setup.

If you want to understand how all of this works, the best way is to build a coding agent manually. Its not that hard

1. Start with Ollama running locally and Gemma3 QAT models. https://ollama.com/library/gemma3

2. Write a wrapper around Ollama using your favorite language. The idea is that you want to be able to intercept responses coming back from the model.

3. Create a system prompt that tells the model things like "if the user is asking you to create a file, reply in this format:...". Generally to start, you can specify instructions for read file, write file, and execute file

4. In your wrapper, when you send the input chat prompt, and get the model response back, you look for those formats, and make the wrapper actually execute the action. For example if the model replies back with the format to read file, you read the file from your wrapper code and send it back to the model.

Every coding assistant is basically this under the hood with just a lot more fluff and their own IDE integration.

The benefit of doing your own is that you can customize it to your own needs, and when you direct a model with more precision even the small models perform very well with much faster speed.


OP is asking for where to get started with Claude for coding. They're confused. They just want to mess around with it in VSCode. And you start talking about Ollama, PAT, coding your own wrapper, composing a system prompt etc.!?


OP is trying to get LLMs to assist with coding. Implying that coding is something he is capable of, and coding your own wrapper is a great way to get familiarity with these systems.


Download Cursor and try it through that, IMO that's currently the most polished experience especially since you can change models on the fly. For more advanced usecases, CLI is better but for getting your feet wet I think Cursor is the best choice.


Thanks. Too bad you need to switch editors to go that path. I assume the Cursor monthly plans are not the same as the Claude monthly plans and you can't use one for the other if you want to experiment...


Cursor is built on VSCode.


Kilo Code for VSCode is pretty solid. Give it a try.


You just described all of your options in detail - what's the problem? Pick one. Seems like you've got a very thorough grasp on how to get started trying the stuff out, but it requires you to choose how you want to do that.


Github Copilot and Claude code are not exactly competitors.

Github Copilot is autocomplete, highly useful if you use VS Code, but if you are using e.g. Jetbrains then you have other options. Copilot comes with a bunch of other stuff that I rarely use.

Claude code is project-wide editing, from the CLI.

They complement each other well.

As far as I'm concerned the utility of the AI-focused editors has been diminished by the existence of Claude code, though not entirely made redundant.


This isn't correct. GitHub Copilot now totally competes with Claude Code. You can have it create an entire app for you in "Agent" mode if you're feeling brave. In fact, seeing as Copilot is built directly into Visual Studio when you download it, I guess they have a one-up.

Copilot isn't locked to a specific LLM, though. You can select the model from a panel, but I don't think you can plug in your own right now, and the ones you can select might not be SOTA because of that.


I didn't mean it doesn't attempt to compete, I mean it doesn't actually compete. Claude code for agents, Copilot for autocomplete (depending on your editor/IDE).

For single-line autocomplete, which is how I use it, pretty much anything will do the job. I use Copilot only because it integrates well with VS Code. I find the other features to be inferior.


I use Copilot for the same reason (it's already there in Visual Studio). But I think we're talking about different things -- did you try Agent mode in Copilot? (the naming of all these things is getting confusing)


Sonnet 4 in copilot agent mode has been doing great work for me lately. Especially once you realise that at least 50% of the work is done before you get to copilot, as architectural and product specs and implementations plans.


Is Copilot's Agent Mode any good, though?


Ehhh... I wouldn't use it for anything important right now. It often screws up by truncating code files then asking itself "where did all those functions go?" and having to rewrite them from scratch.

When it works, it's great though. I've used it to vibe-code some nice little desktop apps to automate things I needed and it produced way more polished UI than I would have spent the time doing, and the code is pretty much how I would have written it myself. I just set it going and go do some other task for 10 mins and come back to see what changes it made.


Opencode https://github.com/sst/opencode provides a CC like interface for copilot. It's a slightly worse tool, but since copilot with Claude 4 is super cheap, I ended up preferring it over CC. Almost no limits, cheaper, you can use all the Copilot models, GH is not training on your data.


> Github Copilot is autocomplete... comes with a bunch of other stuff that I rarely use.

That bunch of other stuff includes the chat, and more recently "Agent Mode". I find it pretty useful, and the autocomplete near useless.


honestly - copilot free mode; and just play with the agentic stuff can give you a good idea. Attach it to Roo and you'll get a good idea. Realize that if you paid to use a better model; you'd get better results as free doesn't have a ton of premium tokens.


try asking it ?


All the tools, copilot,claude, gemini in vscode are all completely worthless unless in Agent Mode. I have no idea why none of these tools dont default to Agent mode.




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