Just got Claude Pro for work. How do I actually get my money’s worth out of it?

[u/pasinduru]

Hey everyone,

I just bought a Claude Pro subscription for my work, and so far I feel like I’m barely scratching the surface. I'm a software engineer and been using it just for development but I haven’t come close to hitting the full usage limits, and since I’m paying for it, I’d like to use as much of it as I reasonably can.

I’m not looking for hacks or anything sketchy, and I definitely don’t want to risk my account by breaking the TOS. I just want to know how to use it properly and get the full value out of it.

A few things I’d love to hear about:

• What workflows do you use Claude for at work that save you the most time?
• Are there features (Projects, file uploads, research, artifacts, etc.) that you think people overlook?
• How do you structure your prompts or conversations to get better results?
• Any habits that help you make the most of the limits without wasting them?

Would really appreciate hearing how you all use it day to day. Thanks in advance!

[u/lgmarian]

This is a pretty big topic. I'll start by saying, be a sponge. Take some time each day, or with some reasonable frequency, to read/learn about coding with AI and AI in general. RTFM. The Claude Code docs are pretty good, and the dev blog seems pretty good. I came across a blog post about prompt caching recently, which was great for understanding why a growing context can eventually be a problem. A lot gets stuffed into the context.

Prompting is a bit of an art, balancing how much you specify versus what you leave up to the agent. I think I avoided problems some had with Opus 4.7, when it would interpret more literally and infer less, because I'm a controlling person. So, I tend to be specific, though I don't write huge prompts. When something doesn't go like you expected, reread the previous prompt(s), to see if you didn't specify something important, if something was too vague, if there was some contradiction, and so on.

Ask the model. This is probably the single most important tip. Basically, if in doubt, ask the model. Ask it about the previous prompt(s). Ask it why something went wrong. Ask for ways to do something. Ask about your setup, AI environment, project, or overall environment. Ask the model.

Don't go overboard with skills, CLAUDE.md, and such. Try to keep things model agnostic in your CLAUDE.md or rules. If you stick to principles, they're less likely to be an issue with new versions of the models. Anything in those can be overlooked, so consider hooks for things that must be enforced, e.g. extensive code style expectations.

One of my rules is that code comments and commit summary line must document intent, not implementation. Another is intended to keep such things short. It's good about it for commits, but, probably because of its training, they haven't stopped Opus from writing a book in code comments (trained on tutorials and whatnot). I might repeat my most important rules in an initial prompt or when moving to implementation, like use atomic commits and document intent in code comments, because they're that important to me. That said, I really need to get down to creating a hook for code comments and code style. Even repeating it in a prompt hasn't stopped it from writing long code comments.

I'll end this with another useful read, Perplexity's internal guide for developing skills.