Most of us have a browser tab open with Claude in it right now, and here’s the uncomfortable truth: we’re barely scratching the surface of what it can do. I came across a brilliant breakdown from an AI professional on LinkedIn, and it stopped me mid-scroll. The core idea? The tool most founders are underusing is the one they’re already paying for. Not a shiny new app. Not another integration. Not a different model from a different lab. Just Claude, sitting there, running at maybe 20% of its actual capacity.
The original poster nailed something I’ve felt for a while. People activate the tool, poke around a little, then complain it isn’t transformative. But as the author points out, the transformation was never in the tool itself. It’s in knowing how to actually deploy it.
The teams that win aren’t the ones with the most tools. They’re the ones who’ve gone deepest on the right ones.
That line from the creator stuck with me. Claude is one of those tools worth going deep on. So let me walk you through the features this expert says most people have never even touched. I’ve reorganized them into a numbered rundown so you can spot the ones you’re missing.
The 10 Claude features hiding in plain sight
- Projects. Persistent workspaces that load your files, preferences, and instructions automatically. No more re-explaining yourself at the start of every single session. Set the context once and it stays put.
- Memory. Claude holds onto useful context across your chats. As the author frames it, you set it up once, then let it quietly work in the background.
- Style Customisation. Train it on your voice a single time, and it applies that voice everywhere going forward. Great for anyone tired of editing robotic drafts into something that sounds like them.
- Claude Code. The original poster is clear that this isn’t just a code helper. It’s an autonomous agent that writes, runs, tests, and manages entire projects on its own.
- MCP. This connects Claude to your external tools and data sources. Suddenly it’s working across your whole stack, not trapped inside a chat window.
- Computer Use. Claude can navigate interfaces and take action directly on your screen. It clicks, it types, it does the thing.
- Deep Research. Multi-source reports compiled automatically. The expert stresses this isn’t a quick summary. It’s a proper research output you can actually use.
- Batch API. Overnight jobs at 50% of the cost. If you’re running real volume, the creator notes this genuinely changes your unit economics.
- Prompt caching. Saves up to 90% on repeated context. The author points out most people have never even heard of it, which is wild given the savings.
- Agent Teams. Multiple Claude instances collaborating in parallel on large projects. Think of it as spinning up a small crew instead of a single assistant.
I’ll be honest, I knew about maybe half of these before reading the post. Prompt caching and Batch API were the two that made me stop and rethink how I’d been running things.
The model lineup matters more than you think
Here’s a detail the LinkedIn creator flags that a lot of folks completely miss. It’s not just about features. It’s about picking the right model for the job. According to the breakdown, most people run everything through one model, then wonder why their results feel inconsistent.
The author lays out a simple map:
- Sonnet 4.6 for your everyday, daily work.
- Opus 4.8 for complex reasoning and heavy coding tasks.
- Haiku 4.5 for speed and scale when you need fast answers at volume.
Matching the model to the task is one of those small shifts that quietly upgrades everything. You stop fighting the tool and start using it the way it was designed to be used.
Why this actually matters for you
The bigger lesson here isn’t really about Claude. It’s about how we treat powerful tools in general. We chase the next app, the next integration, the next launch, while the thing we already pay for sits half-explored. This industry pro captured it perfectly by comparing people who use Claude to those using a fancy search bar.
So here’s a practical way to apply it. Pick just one feature from the list above that you’ve never tried. Maybe it’s setting up a Project so you stop re-pasting your brand guidelines. Maybe it’s turning on Memory. Spend twenty minutes going deep on that one thing this week. Then pick another next week. Going deep beats going wide, every time.
What I love about this breakdown is how it reframes the whole “AI isn’t living up to the hype” complaint. The hype is real. The gap is just in how we deploy it. And closing that gap costs nothing extra, since you’re already paying for the tool.
The mind behind this post also put together an infographic mapping all of it out: features, settings, model selection, and a handful of tips you can apply today. If you want the full visual guide and the finer details, go check out the original LinkedIn post. It’s worth the read.
One question the author left me thinking about, and I’ll pass it to you: what’s the feature you stumbled on late that actually changed how you work?