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Documentation, APIs & AI
This document discusses challenges with API integration and proposes augmented approaches using AI. It notes that API integration takes a long time on average of 700 days due to difficulties understanding documentation, requirements, and ecosystems. Common obstacles include domain modeling, use cases, documentation quality, and access issues. The document advocates improving documentation to explain business and product aspects beyond technical references. It envisions next-gen integration using AI like NLP to help analyze APIs and generate integration code on demand. This could enhance documentation with interactive capabilities and help applications autonomously discover and connect APIs.
Documentation, APIs & AI
- 1. Zdeněk “Z” Němec,February ‘23 API Documentation & AI Augmented API docs & API integration superface.ai
- 2. Founder & CTOof Superface.ai • Pioneered the API- fi rst approach at Apiary.io → Oracle • Founder of API consulting Good API • Helped several Fortune 100 companies with their API strategy and execution • Founder and CTO of Superface.ai Zdeněk “Z” Němec superface.ai
- 3. SaaS API integrationsfatigue superface.ai
- 4. APIs are heftyburden Accelerated by global pandemic, the need for API integrations grew in 80,4% of companies 700 days Average time needed by a SaaS app to build API integrations superface.ai
- 5. Why integrations takesso long? superface.ai
- 6. The truth aboutAPI integration Analysis Development Testing Deployment time budget Expectation Analysis Development Reality superface.ai
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- 8. Superface research Top 6obstacles when integrating APIs 1. Understanding the API domain model and language 2. Answering the question “Can this API ful fi ll my use-case?” 3. The need to understand the entire ecosystem and documentation of API vendor in order to integrate even a small functionality 4. Ambiguity of my own product requirements 5. Quality of documentation, outdated API specs 6. Access hurdles, certi fi cation, API provider terms superface.ai
- 9. What are weanalyzing? Implemenation Product Business Business rules, commercials, limits, regulations, certi fi cation, SLAs How to connect, API calls, JSONs, API Spec what API o ff ers, what capabilities, what use-cases it carters to superface.ai
- 10. API documentation today Technicalby the (wrong) default • Most often, API docs focus on the technical aspects • The least important one, and the one that changes the most often • API docs are not focusing enough on the product’s capabilities and domain • Business side is usually under-documented Implemenation Product Business superface.ai
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- 13. Minimizing the analysistoday? The tools we have today • Improving the API documentation • Document the business and product aspects in addition to technical reference • SDKs, cURL, Postman collections, examples • Standardization & harmonization • Uni fi ed APIs • “APIs in front of APIs” • Nylas, Hyperswitch, Metapack, Merge superface.ai
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- 15. Next-gen API analysis •Analysis will be always needed (for non-commodities) NLP-based augmented human operator Employing LLM/AI to assist in the proces of analyzing and integrating API NLP – Natural Language Processing LLM - Large Language Model Self-integrating apps machine-to-machine communication Enabling applications to autonomously discover & connect APIs superface.ai
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- 17. AI client code-gen GitHubCopilot superface.ai
- 18. AI API interactiondesign Jurassic-X superface.ai
- 19. AI API integration OpenAIGPT-3 / ChatGPT superface.ai
- 20. Superface EDGAR integration code ondemand analyze API API Your App direct API call EDGAR superface.ai “How to ful fi ll order?" +
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- 23. API documentation +NLP superface.ai
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- 25. API documentation +NLP superface.ai
- 26. superface.ai How AI changeAPI docs?
- 27. …when it doesn’tneed the technical parts? Implemenation Product Business superface.ai
- 28. • Documentation ofbusiness aspects • Explanation of domain models • Focus on use-cases superface.ai
- 29. Thank you! Let’s talk! Zdenek“Z” Nemec Twitter: @zdne superface.ai superface.ai