What makes an API pleasant for developers to use?

An API can be technically correct while still being frustrating to use. Two APIs can offer almost exactly the same features, but we generally prefer the one that is easier to understand, test, integrate, and troubleshoot. An API designed with developers in mind reduces the time spent reading documentation (yes, some people still read the docs ^^ Well, partially 😉 ), guessing parameters, dealing with unexpected responses, and figuring out why a request failed.

Experience is essential when designing an API. A good API should work correctly, but above all, make its usage obvious from the very first request. Let's take a look.

Clear and consistent names

It's a bit obvious, but naming is one of the first things we developers have to deal with when working with an API. It's also a bit of a recurring topic: naming is a common problem. It was actually one of my weak points, as someone who always doubts himself. Fortunately, AI can now give us a little helping hand.

Consider two endpoints:

GET /getUserData
GET /users/123

Both could potentially return information about a user, but the second follows a more predictable resource-oriented convention.

Consistency becomes even more important when an API contains dozens or even hundreds of endpoints. For similar operations, it is preferable to keep a consistent naming and structure convention rather than mixing different models, for example:

GET /users/123
GET /getUser/123
GET /customer/123
GET /fetchUserData?id=123

This consistency allows us to quickly understand the logic of the API and more easily anticipate how other endpoints work. We should be able to understand the structure of one endpoint and make reasonable assumptions about the others. The same principle applies to parameter names, response fields, error codes, and HTTP methods.

I have already made naming and consistency mistakes in an API. Obviously, this can lead to confusion for the developers consuming it, raise questions, and create a bad first impression. And whenever a problem occurred, the API was often the first thing to be blamed, sometimes without even having proof that it was actually the source of the problem.

Predictable HTTP methods and status codes

A pleasant API to use relies on HTTP mechanisms consistently. For example:

GET /users/123
POST /users
PATCH /users/123
DELETE /users/123

The HTTP method indicates the desired operation without forcing us to learn an entirely custom vocabulary. Status codes should be just as predictable. A successful request can return:

200 OK

A new resource can return:

201 Created

A request referring to a resource that does not exist can return:

404 Not Found

An authentication problem can result in:

401 Unauthorized

Using standard HTTP mechanisms consistently makes an API easier to understand because, as developers, we already know the general meaning of these responses.

Good documentation is part of the API

Documentation is not just an optional addition to an API. For many developers, it is their first contact with the service. Good documentation should quickly answer practical questions:

• What does this endpoint do?
• Which URL should I call?
• Which HTTP method should I use?
• Which parameters are required?
• What authentication is required?
• What does the response look like?
• What errors can occur?
• Are there request limits?
• Are there important restrictions or special cases?

A simple example can often be more useful than a long theoretical explanation.

For example:

curl https://api.example.com/users/123 \
  -H "Authorization: Bearer YOUR_TOKEN"

followed by the expected response immediately gives the developer something concrete to test:

{
  "id": 123,
  "name": "John",
  "email": "john@example.com"
}

OpenAPI is now one of the most widely used standards for describing HTTP APIs. It can be used to document endpoints, parameters, responses, data schemas, and authentication mechanisms.

In addition, when an API has complete documentation containing all the necessary information, a generative AI can also be used to query it and quickly find the information being searched for.

Developers should be able to make their first request quickly

A good way to evaluate an API is to ask how long it takes a new developer to successfully make a request. If we have to create several accounts, configure complex credentials, install several dependencies, and read dozens of pages before making our first request, the API has a significant integration problem.

A good API should provide a short path between the documentation and a working request.

This is where tools such as curl, Postman collections, SDKs, interactive documentation, and code examples can be useful.

The goal is not necessarily to provide every possible integration. It is to make the first request easy to perform. Even without AI helping us, otherwise it's probably too complex.

Authentication should be clear

Authentication is often one of the first obstacles when integrating an API.

The documentation should clearly explain how to obtain credentials, where to send them, which authentication method to use, when tokens expire, how to renew them, and which permissions are required.

For example:

Authorization: Bearer YOUR_ACCESS_TOKEN

is much easier to understand when the documentation clearly explains where the token comes from and how long it remains valid. Authentication should also produce understandable errors.

A developer should not have to guess why a request failed. The API should provide enough information to diagnose the problem, for example through error codes and HTTP status codes, while avoiding the disclosure of sensitive information that could help an attacker. In some cases, particularly for security reasons, the message returned to the client should therefore remain deliberately generic.

Response structures should be consistent

An API becomes difficult to use when similar endpoints return completely different structures. For example, one endpoint might return:

{
  "data": {
    "id": 123
  }
}

while another returns:

{
  "result": {
    "user_id": 456
  }
}

Different structures can sometimes be justified, but unnecessary variations create extra work. Consistency allows us to reuse our assumptions and our code. The same principle applies to dates, identifiers, pagination metadata, nullable fields, and collections.

Today, I am sometimes contacted about old APIs that lack consistency, particularly to answer questions and clear up misunderstandings for integrators. The time spent designing an API properly is therefore never wasted: it saves us a lot of time in the long run.

Errors should help developers solve the problem

Error messages are particularly important because we usually encounter them when something is already not working.

Compare:

{
  "error": "Invalid request"
}

with:

{
  "error": {
    "code": "INVALID_EMAIL",
    "message": "The email address is not valid.",
    "field": "email"
  }
}

The second response provides much more useful information. A good API error should ideally clearly indicate what went wrong, which part of the request caused the problem, whether it is relevant to retry, and what the developer should change to fix the request.

Error codes can also make programmatic processing easier, as applications should not have to analyze sentences intended for humans to determine what happened.

OpenAPI can improve the developer experience

OpenAPI provides a machine-readable description of an HTTP API.

Instead of documenting an endpoint only with text, an OpenAPI specification can describe its path, HTTP method, parameters, request body, responses, and schemas.

This specification can then be used by different tools to generate documentation, clients, perform validation, provide testing interfaces, and much more.

For developers, this means that the API contract does not have to exist only as a collection of documentation pages. A properly maintained OpenAPI specification can become an additional reference source for the API.

In addition, AI can directly use this specification to identify the information required for an API call and generate, for example, the expected parameters, headers, or request body.

Pagination should be predictable

Pagination is a frequent source of unnecessary complexity.

An API might return:

{
  "items": [],
  "page": 2,
  "per_page": 50,
  "total": 1250
}

Another might use cursor-based pagination:

{
  "items": [],
  "next_cursor": "abc123"
}

Neither approach is universally better. What matters is that the behavior is clearly documented and consistent.

Developers need to know how many items are returned, how to request the next page, whether results can change between two requests, when pagination ends, and whether the cursors used to browse the results can expire.

Pagination may seem like a detail when designing an API, but it can become a major integration problem when its behavior is not clearly defined.

Rate limits should not be a surprise

Most production APIs need some form of request rate limiting. The problem is not necessarily having limits. The problem is hiding them. Developers should know which limits apply and what happens when they are exceeded.

For example:

HTTP/1.1 429 Too Many Requests
Retry-After: 30

can provide a useful indication to the client.

The documentation should also explain whether limits apply per user, API key, IP address, endpoint, or according to another criterion. A pleasant API to use makes these constraints visible before they become production incidents.

Versioning should be understandable

APIs evolve.

Endpoints change, fields are added, behavior is modified, and eventually, breaking changes may become necessary.

A pleasant API to use should have a clear versioning strategy.

For example:

/api/v1/users
/api/v2/users

is immediately understandable.

Other strategies are possible, but we should not have to discover the versioning rules through trial and error.

More importantly, breaking changes should be communicated sufficiently in advance whenever possible.

Deprecation notices, migration guides, and clearly defined timelines can make a big difference for those maintaining existing integrations.

Backward compatibility matters

Adding features does not necessarily mean breaking existing clients.

For example, adding a new field to a response is often less disruptive than changing the meaning or type of an existing field (Well, I admit I've done this several times in the past, but we had certain constraints with large clients, so there was no other way ...).

An API should therefore carefully distinguish between additive changes and breaking changes.

Developers appreciate APIs that evolve without constantly forcing them to rewrite integrations that already work.

Webhooks should be reliable

APIs are not limited to request-response interactions. Many services also need to notify applications when an event occurs. Webhooks are commonly used for this purpose.

A pleasant webhook system should clearly document:

• event types;
• data format;
• authentication or signatures;
• retry behavior;
• timeouts;
• duplicate deliveries;
• event ordering;
• how delivery failures are handled.

Duplicate events are particularly important. Applications should generally be able to receive the same event multiple times. Good documentation should make this behavior explicit rather than leaving us to discover it in production.

Security should not make the API impossible to use

Security and developer experience are not necessarily opposed.

An API can require strong authentication while still providing clear instructions and useful error messages.

Developers should understand which permissions are required and why a particular request is rejected.

For sensitive operations, more granular permissions can even improve the developer experience by making access rules predictable.

The key is for security mechanisms to be documented rather than becoming unexplained obstacles.

Conclusion

A pleasant API to use is above all predictable. We should be able to make reasonable assumptions about its behavior without spending our time guessing what it expects. As developers, we should be able to spend our time building our applications rather than trying to understand how the API works internally.

I hope these few tips will help you with your next developments. Good luck with your next integrations, and perhaps with your next API!