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Developer documentation is either poor in quality or an expensive burden on companies. The root cause is simple: developer documentation is a tax—an unavoidable cost that doesn’t create value on its own but merely enables it elsewhere. It’s like packing peanuts; necessary to prevent damage during transit but ultimately wasteful if a transportation method that did not require them existed.
On the UI front, modern systems have evolved to require minimal documentation thanks to good design. Meanwhile, advancements like OpenAPI Specification (OAS) have improved the landscape in the API space. However, we believe there’s still significant progress to be made.
Our Vision for the Future
We envision a future where developer documentation follows three key principles:
1. Documentation is Native: Documentation should be seamlessly embedded within code, not documents or sites. Examples include OAS, native language type definitions, helpful API error responses, and detailed descriptions at the function, argument, and attribute levels.
2. Documentation is Implicitly Written & Maintained by AI via Observation: Whether through monitoring API calls or analyzing code usage, documentation should be dynamically generated by observing runtime behavior. Real insights come from how APIs and events are used at scale.
3. Information is Retrieved On-Demand via AI-Assisted Experiences: Instead of static, hosted documentation, information should be accessible through AI-driven suggestions within IDE’s chat interfaces and voice commands. This allows developers to query documentation in human language on-demand when the data is needed. Additionally, it should be presented as helpful examples in their native programming languages, relevant to their specific tasks at hand.
The Benefits of This Approach
By implementing these principles, we unlock several key advantages:
- Faster Developer Onboarding and Integration: Developers can quickly understand and utilize the documentation, speeding up integration efforts.
- Lower Production and Maintenance Costs: AI-driven documentation significantly reduces costs by automating content generation and updates, minimizing manual effort.
- Improved Accuracy and Confidence: With AI continuously monitoring and updating documentation, it remains precise and up-to-date, minimizing errors and enhancing developer confidence.
Bringing the Vision to Life
While significant advancements have been made, there’s still work ahead to realize this vision across three key areas fully:
Native Documentation
Current State: We generate type definitions in TypeScript, Python, C#, and Java, with snippet management available through IDE-based experiences.
Future Plans: We aim to expand support for more languages and enhance error reporting by integrating product-specific error codes for an even smoother experience.
Implicit Documentation
Current State: Today, API models and descriptions are generated through observation in Postman or imported via O A S into Poly through CI/CD pipelines.
Future Plans: We plan to analyze runtime data to detect discrepancies between cataloged and runtime models, improving interface resilience. Additionally, we intend to analyze client-side code usage to enrich API documentation further.
AI-Assisted Retrieval
Current State: Poly can retrieve A P I and event information and product documentation through various slash commands and integrations with GitHub Copilot Chat.
Future Plans: We foresee deeper integration into client code to provide more context-aware results and help developers architect integrations more effectively. We aim to integrate more deeply into editors like Cursor, enabling a more seamless development experience. Additionally, we plan to support AI agents that can analyze developer intent and provide architectural guidance before generating integration solutions.
Work With Us
If you’d like to explore how we can help with your integration projects, email us at hello@polyAPI.io or Sign up for free to get started. Have questions about our platform, or roadmap? We’d love to hear from you!