I just spent my entire Sunday rebuilding workflows I use for The AI Corner, personal tasks, and my day job inside Claude Skills.
Worth every minute. Claude Skills just launched and they're game changing for workflow consistency and flexibility across AI toolsets and capabilities.
What are Claude Skills?
Think of a Claude Skill as an ability that Claude can unlock, like giving it a new power or special training. Once Claude has been taught this new ability, it instantly knows the ability exists, what it does, and it will automatically invoke that Skill whenever it’s relevant. This is the game changing part:
Creating a presentation: Claude instantly loads your brand guidelines and applies them without you asking.
Analysing data: Your analysis framework is already active and ready to use.
Writing content: Your blog or report guidelines shape the piece around your company’s preferred flow (introduction, context, key points, and takeaway) without you needing to explain it.
Literally speaking, a Claude Skill is a:
Zipped folder that contains instructions and resources teaching Claude how to perform a specific task consistently and accurately.
Inside that folder is a SKILL.md (markdown) file (which holds the main instructions), plus any supporting materials: code scripts, image assets, data files, or documentation.
Once the folder is uploaded, Claude loads only what it needs: first the name and description, then the full SKILL.md if relevant, then bundled files as required.
The formula: Skill = prompt + tools + assets.
Major benefits:
This means you can package effectively unlimited context without bloating your conversation window.
Skills can contain Python scripts that execute. PDF extraction becomes deterministic. Data transformations become reliable.
This isn't a saved prompt. It's a portable AI workflow built in natural language instead of a drag-and-drop builder.
Example workflow: turning podcast transcripts into multiple content formats.
For example, when turning podcast transcripts into the relevant meta data and information for YouTube, Spotify, The AI Corner newsletter, and a summary post for LinkedIn, this usually requires copy-pasting transcripts and outputs from one Claude Project or Custom GPTto the next, with a lot of back and forth to improve the output to my liking.
With Claude Skills, I've nearly automated this process from transcript through to end product, along with other checks, for uploading into the relevant apps.
Previously, I had to create and manage three separate Claude Projects plus run manual tasks to handle each output:
One Project for digesting and turning the transcript into the YouTube and Spotify meta data content.
One Project for producing the AI Corner newsletter summary to promote the podcast.
One Project for creating a LinkedIn post to promote the podcast.
I also had to manually visit LinkedIn, find the podcast guest’s profile URL, double check spellings for name, company, and relevant details, and then paste that information into the prompt to make the content more relevant.
I'd also copy paste information from previous episodes as examples to inform quality.
Now, that entire process is fully automated (screenshot below for Claude's process in action). Using the newsletter-podcast-formatter Skill, Claude:
Reads and understands the uploaded transcript.
Generates the three content pieces I need in my preferred formats. The accuracy of the outputs is excellent.
Searches LinkedIn automatically to find the correct guest profile, ensuring accurate spelling, company name, and other relevant details.
Incorporates that context directly into the generated content.
Handles additional workflow steps I’ve added to streamline publishing and ensure consistency.
Adding to this Skill, I'm confident I can automatically create the thumbnail to match.
This Skill also integrates directly with Google Drive for reference searching:
A folder has been created in GDrive containing reference files, such as past thumbnails, writing examples, and style guidelines. I've set up a Relay.App workflow to extract published content from The AI Corner and other channels to be ingested into a Google Doc, which the Claude Project that I run this workflow has added as a File to provide context to the content creation workflow.
The Skill automatically searches and reads from those files each time it runs.
When I update or replace those reference files, the Skill instantly uses the new material: no need to edit prompts or rebuild workflows.
How to actually use Skills
First and foremost, Skills are only accessible to users on a paid plan.
Head to Settings
Select the Capabilities tab
Under the Skills section, toggle on/off the Skills that apply to you. You'll see pre-built options, such as: brand guidelines, canvas design, internal comms, Skill creator, etc.
Upload your own custom Skills that you need.
The fastest and easiest way to create your own Skills:
Leverage the pre-built Skill Creator skill (it's brilliant). It's a meta-skill that builds Skills for you through conversation.
Open a 'New Chat' with Claude. Tell it what you want in detail. It creates the folder structure, writes the SKILL.md file, bundles any code or assets needed that you provide.
Then you download, zip, and upload it in the Capabilities section referenced above.
Tip: Right-click and 'Star' the conversation you use to create the Claude Skill file. Rename the chat as 'Claude Skills Creator', and it'll be easily accessible near the top of your chats whenever you have the urge to create a Skill on the fly.
The ability to now leverage Skills, Projects and Styles for their respective specific roles in the AI workflow process provides users with massive amounts of control for accurate and consistent outcomes.
Claude Skills vs Claude Projects
This needs clarifying, and admittedly I struggled to understand it at first.
Claude Projects are:
Persistent workspaces for ongoing work.
They hold your knowledge base, documents, and chat history.
Context persists across conversations.
You manually select a Project to work in.
Projects are perfect for long-term research, evolving topics, and continuous knowledge building.
Claude Skills are:
Automated workflows that activate globally across any Chat in Claude.
They load automatically when Claude detects relevance. No manual selection (but you can call on them with natural language, e.g. 'use the linkedin-content-ideas skill'.
Skills are token-efficient because they only load detailed instructions when needed.
Available across your entire Claude account, every Project, every conversation.
Here's how I use them together now:
Projects = context houses.
Skills = the actual workflows.
Example: How Projects and Skills Work Together
Take my Podcast Transcript Project as an example. This Project holds everything related to The AI Corner podcast. Chats containing:
Podcast planning
Podcast transcripts
Past episode notes
Content templates
Audience insights.
'Files' in the Project contain access to live documents in Google Drive and structured data in GitHub, all connected to the podcast. Together, they give Claude real-time context.
When I start working in that Project, Claude automatically activates the right Skills:
A Transcript Summariser Skill that digests the raw transcript into key themes and takeaways.
A Content Repurposing Skill that turns those insights into formatted content for YouTube, the newsletter, and LinkedIn.
A Guest Research Skill that finds the correct LinkedIn profile, company, and background for each guest.
All of this happens inside one conversation. Multiple Skills stack intelligently, maintaining context as Claude moves through each stage.
Before Skills, I had to manage this manually across multiple Projects. This is all now executed in a single thread.
The good, and the quick fixes for the bad
The good
Accuracy: noticeably better than the instructions given in Projects. In Projects, Claude would follow your setup instructions about half the time. Sometimes it worked well, but often the output was basic or missed the intent entirely. Skills are much more precise. They understand nuance and consistently deliver results that align with your defined logic.
Context handling: no need to cram system instructions or background information into every Project. Previously, you had to load Projects with long blocks of context just to keep Claude on track. Even then, the model could lose or misinterpret instructions once you changed topics. With Skills, context lives inside the Skill itself. Claude pulls in only what is relevant, keeping the conversation clear and focused.
Creative control: Skills don’t override your prompts mid-conversation like Projects sometimes did. In Projects, Claude would often cling to the original instruction even when you wanted to move in a different direction or explore a new idea. It would steer you back to the original context when you were trying to be more creative. Skills fix this by keeping structure when needed but allowing flexibility when you want to take the conversation somewhere new.
Consistency: Claude sticks closely to Skill instructions, giving far more reliable results.
Composability: you can combine multiple Skills (brand guidelines, writing frameworks, analysis models) and functions (web search etc.) in one conversation.
Automation: Claude stacks relevant Skills automatically, checking brand colours, applying writing frameworks, and using your analysis methods all at once.
Fixing the rough bits
Auto-invocation: The bad: Skills don’t always trigger automatically, even when the use case is obvious. The quick fix: Mention the Skill name directly in your prompt (e.g. “Use the Podcast Summariser Skill for this”).
Skill setup clarity: The bad: Claude doesn’t always know when to use a Skill unless you define it clearly. The quick fix: When building Skills, spend extra time on the “Claude should use this Skill when the user asks to…” section of the .md file. Be specific, give examples, and test different phrasing.
Painful folder structure: The bad: Building Skills manually can be fiddly and easy to break if you get the structure wrong. The quick fix: Use the Skill Creator tool. It builds and validates the structure automatically, so you don’t have to touch any files.
How Skills has completely shifted my AI tool usage
Six months ago, my usage was split about 50/50 between Claude and ChatGPT. Learning how to use Claude Code as a non-technical person pushed that to 60/40. Now, with Claude Skills, this will shift my usage closer to 90/10.
That shift happened fast, and it happened for three specific reasons.
The connector explosion: The Model Context Protocol (MCP) turned Claude into something that actually knows what's happening in my workspace. It pulls live context from Google Workspace, GitHub, Slack, and a growing list of systems I already use. No more uploading files. No more copying and pasting between tabs.
Claude Code is still settling in: I'm still learning how to think in Claude Code's language. It's not intuitive for non-technical users yet, but the potential of where it interacts with Claude Skills creates unlimited potential. Skills become the bridge between what Claude knows and what Claude Code can build. You're not just asking for code anymore. You're handing Claude a repository of proven patterns, style guides, and frameworks that it can execute against.
GitHub as a prompt repository: This is where it gets interesting. Start treating prompts like code. Version them. Store them. Improve them over time. When you use GitHub to house your best prompts and Claude Code to execute them, you've built a system that compounds. Your best workflows become reusable assets that get sharper with every iteration. This has proven much more effective in Claude than in ChatGPT.
With these developments and more, what people miss is the divide between power AI users and the everyday AI user is about widening dramatically: we're not all using the same tools anymore. Two people can both "use Claude" and be operating in completely different universes. One person is asking questions. The other is building systems that answer questions automatically, execute workflows, and improve themselves over time.
The gap between these two groups isn't going to narrow. It's going to accelerate. Generic AI users will keep treating Claude like a better search engine. They'll ask it questions, get answers, and move on.
Power users are building infrastructure. They're connecting APIs through tools like n8n, Relay.app, and Autohive. They're writing Skills. They're versioning prompts in GitHub. They're creating autonomous workflows that run while they sleep. Research, content creation, and data handling collapse into a single flow instead of being scattered across six different apps and twelve browser tabs.
I haven't fully tested the slide deck or creative asset Skills yet, but early reports on X look promising. If they perform as expected, that's another entire category of work that moves from manual execution to systematic generation. Claude becomes the command centre for everything: reasoning, building, creating, and pulling live data in one place.
This isn't about being "technical" anymore. It's about understanding that AI is a platform, not a product. The people who grasp this early are building unfair advantages that compound daily. They're not working harder. They're building systems that work for them. Every workflow they automate becomes a permanent upgrade. Every Skill they write becomes reusable leverage.
The productivity gap between someone using Claude casually and someone engineering with it is already 10x. In twelve months, it'll be 100x. The people who learn to treat AI as infrastructure rather than a chat tool will be operating in a different economic reality. They'll produce more, faster, with higher quality, whilst spending less time doing it.
Written by Mike ✌
Passionate about all things AI, emerging tech and start-ups, Mike is the Founder of The AI Corner.
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