Oxide pays for your LLM use through a company account. If you don't know what to use, use Claude Code in the terminal or in VS Code. We also have an OpenAI account if you want to try their Codex product.
(Logistics elided.)
Run Claude Code in a repo (whether you know it well or not) and ask a question about how something works. You'll see how it looks through the files to find the answer.
The next thing to try is a code change where you know exactly what you want but it's tedious to type. Describe it in detail and let Claude figure it out. If there is similar code that it should follow, tell it so. From there, you can build intuition about more complex changes that it might be good at.
First of all, read Anthropic's amazing Prompting best practices doc.
Sonnet 4.5 is the default and it is very solid. Opus 4.5 is pretty new as of Dec 2025 and it is clearly even better. They cut the price of Opus by 2/3 with 4.5 ($5/M input, $25/M output), so it is no longer absurdly priced compared to Sonnet ($3/M input, $15/M output). They claim the higher price may actually net out because it uses fewer tokens, perhaps because it is less likely to waste time on wrong directions.
Claude Code sometimes automatically uses the cheaper, faster Haiku 4.5 for
subtasks like exploring a codebase. You can set it as the main model for the
chat with /model, but the speed/intelligence tradeoff isn't worth it. There
is also Sonnet 4.5 with a 1M context window available, but long context weakens
performance substantially, so you are almost certainly better off managing your
context to make it fit in 200k.
While you can tell Claude to run a command, it's a lot simpler and quicker to
use ! to run it yourself. This is equivalent to running the command in another
terminal and pasting the output into the chat. You can use this a million ways,
but here are a few examples:
!cargo nextest run <test_name>followed by "why is this test failing?"!cargo checkfollowed by "fix this"- Stub out functions by hand, then use
!jj diffor!git diffto give Claude the work so far and say "complete these functions" (with more detail, see tip below)
We've learned through decades of experience with search engines to be very careful about what we type into a prompt. This is the opposite of what you want with LLMs — they are capable of pulling nuance out of everything you say. So instead of figuring out the shortest prompt that will do the thing, ramble about the problem, tradeoffs, your hopes and fears, etc. Dictation software like MacWhisper is great for this.
A couple of caveats:
- When I say "prompt" here, I am talking about the prompting you write by hand in natural language, which is hard to overdo because it's naturally small. It is possible to overdo filling the context window up with, e.g., log files.
- This assumes you have enough experience for your rambling to have a good signal to noise ratio. Beginners can take the rambling approach too, but they will likely need to spend more time refining the plan.
As the chat goes on, each message gets more expensive while Claude gets
dumber. That's a bad trade, especially if
what's filling up the context is a bunch of fighting about what you don't want
Claude to do. Use /context and /cost or the ccusage statusline trick to
keep an eye on your context window. CC natively gives a percentage but it's sort
of fake because it includes a large buffer of empty space to use for compacting.
Compacting tells Claude to reduce size of the conversation so far by summarizing the key points and replacing the chat history with the summary. The problem is that compacting often doesn't actually shrink the context enough because it keeps a ton of irrelevant stuff. This is all noise that can throw Claude off.
Instead, figure out what you want to save from the current conversation and
use /reset or /new to start over with an empty context window. A simple
approach: have Claude maintain a PLAN.md as it works, then start fresh with
just that file and the diff so far.
The Anthropic people call this "multi-context window workflows", which is a horrible name, but the practice is really useful and surprisingly few CC users seem to know about it.
Track cost in real time with ccusage
Spending too much is a good sign that Claude is spinning its wheels and
you should think about how to prompt it better. By default, the TUI does
not want to show you what you're spending in real time — you have to
run /cost manually to see it. Add this to ~/.claude/settings.json
for a statusline at the bottom showing real-time session cost:
"statusLine": {
"type": "command",
"command": "npx ccusage@latest statusline"
}
Run npx ccusage in the terminal to see daily/weekly/monthly usage tables.
We are trying usage-based billing rather than monthly subscription plans. It's cheaper (CC team is $150 per seat) and it's easier to administer because we don't have to worry about who gets a seat. Plus there's no $20 or $50 or $100 psychological hurdle to getting started. Another advantage of pay-as-you-go is that you will virtually never hit rate limits — Anthropic are happy to sell us as much usage as we want to pay for.
Note that this setup does not include a subscription to Claude chat on web/mobile. That would be $25 per seat. You can expense a personal subscription if you want that.
Create an API key at https://platform.claude.com/ in the API keys sidebar.
Most tools accept it directly or via the ANTHROPIC_API_KEY env var.
GPT-5 is cheaper than Sonnet and quite good, though people seem to generally prefer Claude Code.
(Logistics elided.)
OpenCode works with multiple providers, including Cerebras, Groq, DeepSeek, and Moonshot (Kimi K2). It's fun to try other models, but I find myself coming back to Claude Code every time.
- Effective context engineering for AI agents (Anthropic, Sept 2025)
- Link to an internal talk on LLMs from September
- Here's how I use LLMs to help me write code (Simon Willison)
- Using AI Right Now: A Quick Guide (Ethan Mollick)
- How to Build an Agent (Thorsten Ball, Amp)
- How I think about LLM prompt engineering (François Chollet)
- Interpretability: Understanding how AI models think (Anthropic)
- The future of agentic coding with Claude Code (Anthropic)
- Interview with Claude Code team (Latent Space)
- Is RL + LLMs enough for AGI? — Sholto & Trenton (Dwarkesh, May 2025)
- How LLMs actually think — Sholto & Trenton (Dwarkesh, March 2024)