In This Article
Key Takeaways
- Custom GPTs still win for the largest user base and the deepest paid-distribution story.
- Claude Skills are the cleanest packaging model and the most portable thanks to MCP support.
- Gemini Gems are the easiest distribution path inside Google Workspace organizations.
- Pick one to start. Building on multiple platforms is for after you have product-market fit on the first.
If Projects, ChatGPT Projects, and Gemini Gems are about giving yourself a persistent workspace, Skills, Custom GPTs, and Gems-as-publishable are about giving everyone else a workspace you built. The shift from private use to public distribution is what turns AI tinkering into a product.
I get this question every week from students and small founders: which platform should I build on if I want to ship something real in the next thirty days? Here is the honest 2026 answer.
Why builder platforms matter for ordinary creators
For most of software history, shipping a useful app required a developer, a designer, a server, an account system, and a payment processor. The builder platforms collapse all of that into a few text fields and a file upload. A teacher with a great rubric, an attorney with a tested clause library, or a small-business owner with a customer-service playbook can now turn that knowledge into a tool other people use.
The economic shift is real. The Custom GPT directory has paid millions of dollars to thousands of creators since OpenAI's revenue-sharing program launched. Anthropic's Skills marketplace and Google's Gem distribution are catching up. The window for being early on these platforms — for occupying a category before someone else does — is open right now.
Claude Skills: portable, MCP-native
Claude Skills are Anthropic's packaged-capability format. A Skill bundles a system prompt, a knowledge base, and (optionally) tools defined as Model Context Protocol servers. Once a Skill is published, any Claude user with the right plan can install and use it.
The defining strength of Skills is portability. Because the tools are MCP servers, they are not tied to Anthropic's infrastructure. The same MCP tools you wire into a Skill can plug into LangGraph, the OpenAI Agents SDK, Microsoft's Agent Framework, or your own code. If Anthropic disappeared tomorrow, the tools survive.
The second strength is that Skills inherit Claude Opus 4.7's 1M-token context. A Skill built around a long reference library — case law, standards documents, internal policy manuals — is meaningfully more capable than the same Skill built on a model with a smaller context.
When Claude Skills shine
Long-document expert assistants. Compliance and policy tools. Anything where the breadth of reference material matters more than flashy multimodal output. Skills are the most "serious-work" of the three.
The honest weakness is distribution. Claude has fewer total users than ChatGPT, and the Skills marketplace is younger than the Custom GPT directory. If raw audience reach is your top priority, Custom GPTs still lead.
Custom GPTs: the largest distribution today
Custom GPTs were OpenAI's first packaged-capability format and have had the longest runway. A Custom GPT bundles a system prompt, a knowledge base, optional Code Interpreter and Browse, and tools you wire up via the Actions feature. Custom GPTs are usable by every ChatGPT Plus and Team subscriber — the largest paid AI user base in the world.
The defining strength is distribution. The GPT directory is the closest thing the AI world has to an app store with millions of users browsing for new tools. The revenue-sharing program — modest in absolute dollars per Custom GPT but real — gives creators a financial incentive that the other two platforms have not yet matched at scale.
The second strength is the broad tool set. Native image generation, Code Interpreter (which actually runs Python), Browse, voice mode. A Custom GPT can deliver a multimedia experience that Claude Skills and Gemini Gems are still catching up to.
When Custom GPTs shine
Consumer-facing creator tools. Anything that benefits from image generation or live web search. Tools where the size of the user base is itself a competitive advantage. Anyone who wants to test product-market fit with the largest available audience.
The weakness is consistency. GPT-5.5 is more eager to be helpful than Claude is, which can cause a Custom GPT to drift from its instructions when pressed. The context window is smaller. For long-document expert work, Claude is the better engine even if the distribution is smaller.
Gemini Gems: deepest Google integration
Gemini Gems started as a personal-workspace feature but have evolved into a publishable format inside Google Workspace organizations. A Gem bundles instructions, reference Drive files, and (in 2026) tool integrations into Google's ecosystem — Calendar, Gmail, Sheets, Docs, Drive.
The defining strength is integration. Inside a Google Workspace organization, a published Gem can be invoked from inside any Workspace app. The Gem reads your Drive without an upload, answers from your Calendar without a copy-paste, and drafts a Gmail reply with one click.
The second strength is administrator control. Workspace admins can publish Gems organization-wide, restrict them to specific groups, and audit usage. For a school district, a hospital network, or a government agency, this admin control is the difference between "we use Gemini" and "we use Gemini safely."
When Gemini Gems shine
Internal tools inside a Google Workspace organization. Cross-app workflows that touch Gmail, Drive, and Sheets. Anything where the friction with the existing file system is what slowed adoption.
The weakness is consumer distribution. There is no public Gemini Gems marketplace today. If you want strangers to discover and install your tool, this is not the platform.
Side-by-side at a glance
The summary I keep on a sticky note.
- Best for paid distribution to consumers: Custom GPTs > Claude Skills > Gemini Gems.
- Best for serious knowledge tools (long documents, careful reasoning): Claude Skills > Custom GPTs > Gemini Gems.
- Best for inside-an-organization deployment: Gemini Gems > Claude Skills > Custom GPTs.
- Best for multimedia output (images, voice, code execution): Custom GPTs > Gemini Gems > Claude Skills.
- Best portability across frameworks: Claude Skills (via MCP) > Custom GPTs (via Actions) > Gemini Gems.
- Easiest first build: Custom GPTs > Gemini Gems > Claude Skills.
- Best fit for federal or regulated work: depends on your existing cloud — Azure shops use Microsoft, Google shops use Gemini, Anthropic-on-Bedrock is increasingly common.
Which one to ship on
Here is the decision tree.
If you are a creator trying to build an audience and earn, ship a Custom GPT first. The directory is where the discovery happens. Build for the largest pond before you scale.
If you are an expert with a deep reference library — an attorney, a financial advisor, a researcher, a teacher with a curriculum, ship a Claude Skill. The 1M-token context lets the reference library be genuinely deep. The output quality on serious work is higher.
If you are building for inside your company and your company is on Google Workspace, ship a Gem. The friction-free integration with the apps your colleagues already use will drive adoption faster than any marketing.
If you do not know yet, start with Custom GPTs. The lowest-friction first build, the largest test audience, and the broadest tool set. You will learn what kind of builder you are. Move to Claude Skills when you outgrow the context window. Add a Gem when your team-mates need it inside their Workspace.
Building your first app on each — a 30-minute path
Each platform has a 30-minute first-build path. Pick one and try it this week.
Custom GPT. Sign in to chatgpt.com with Plus. Click "Explore GPTs" then "Create." Fill in the four fields the wizard asks: name, description, instructions, knowledge files. Toggle the capabilities you need (Browse, Image Generation, Code Interpreter). Click "Create." Test in the preview pane. Publish to the directory or keep private.
Claude Skill. Sign in to claude.ai with Pro or Team. Click "Skills" in the sidebar, then "Create Skill." Write the instructions, upload reference files, and define any MCP tools you want the Skill to call. Save and test. Publish if your plan supports the marketplace.
Gemini Gem. Sign in to gemini.google.com with Google AI Pro or Workspace. Click "Gems" in the sidebar, then "New Gem." Name it, write the instructions, attach Drive files, configure tool access. Save and test. If your Workspace admin role allows, publish to your organization.
The first build will not be the version you ship. That is fine. The point of the first build is to learn the platform's shape — what it is good at, where it pushes back, what the publishing flow feels like. Take the first build to a friend who is not in tech, watch them use it, and rebuild. That is how products become real.
Common questions
Will the platform I pick lock me in? Less than you fear. If you write your tools as MCP servers and your instructions in plain English, porting between platforms is a half-day exercise. Avoid platform-specific features for the first version, then add them later if they earn their keep.
How do I choose between a Skill and a Project? A Project is for your own use. A Skill is for distribution. If you only want the workspace for yourself or your team, a Project is enough. If you want others to install and use the tool, you need a Skill (or a Custom GPT, or a Gem). See my workspace comparison for the workspace side.
Can I charge for my Custom GPT? The OpenAI revenue-sharing program pays creators based on usage in the GPT Store, with terms that have changed several times. Charging directly inside ChatGPT is not supported; the revenue is the platform's share of plan revenue. Many creators monetize externally — using the Custom GPT as a lead magnet that drives traffic to their own paid offering.
What if my app fails? Most first apps do. The fast iteration loop — build, watch one user, rebuild — is what separates apps that find product-market fit from apps that don't. The platform you pick matters less than the speed of your iteration loop.