AI-Powered APIs and API-Enabled AI: A Symbiotic Evolution Driving Mutual Innovation

In today's digital landscape, APIs are the foundational building blocks of innovation. They connect services, share data, and enable new experiences. But as our API ecosystems grow to include thousands of endpoints, they present a new set of challenges that traditional development models are not equipped to handle. This is where AI comes in, not just as a consumer of APIs, but as a transformative force for making them better. The future of APIs and AI is not a one-way street; it's a symbiotic loop where each side continuously enhances the other.

AI for APIs: From Chaos to Clarity

The first part of this loop is the use of AI to streamline and improve the API landscape itself. Without AI, API discovery can be a cumbersome, keyword-based search through fragmented documentation, leading to a frustrating experience for developers. But AI changes the game entirely, taking a chaotic ecosystem and bringing order and clarity to it.

• Smarter API Discovery: We're moving beyond traditional keyword search to intelligent, intent-based discovery. By indexing API documentation with a semantic search engine and vector embeddings, an AI agent can understand a developer's true intent behind a natural language query. It can then retrieve the most relevant API documentation and provide an instant, natural language summary, drastically reducing the time spent searching. This feature is currently live and deployed for our API documentation on developer.cisco.com, as detailed in our blog post New AI-Driven Semantic Search and Summarization.
• Enhanced API Specifications: AI can act as a tireless assistant, continuously reviewing and refining API specifications to improve clarity and compliance. A critical part of this solution is the new OpenAPI Overlay Specification, which allows us to add rich context and metadata to existing specs without changing them. These agents are currently under active development and are being used internally by our tech writers and reviewers to ensure our documentation is always high-quality, up-to-date, and complete.
• Accelerated Developer Workflow: We are bringing this intelligence directly into the developer workflow. Our DevNet Devvie VSCode Copilot Extension uses a semantic search server to access the latest API documentation in real-time. This allows developers to write code, troubleshoot issues, and generate scripts directly within their IDE, knowing that the information is always current and reliable. This extension is currently in an internal pilot and build phase and is under evaluation for a broader release.

APIs for AI: The Brain to the World

Without APIs, an AI is essentially a brain in a jar-a powerful intelligence with no way to perceive or interact with the world. APIs are the crucial link that enables AI to move from theory to action, giving it both the senses to perceive its environment and the hands to act on it.

• Senses: APIs provide the "senses" for AI, allowing it to perceive the outside world and its state. Just as a human brain uses vision and hearing, an AI uses APIs like a Network Monitoring API or a State Fetching API to retrieve real-time data on the state of a system, a device, or an application.
• Actions: APIs also give AI a "hand to act on it." The AI can use APIs to perform tangible actions in the real world, such as updating a network configuration, provisioning a user, or executing a specific device command. This is what transforms AI from a reasoning engine into a powerful, autonomous agent.

The Challenge: A "Needle in a Haystack" Problem

With AI making APIs cleaner and easier to discover, a new and fundamental problem emerges: scale. When a large enterprise API ecosystem contains thousands of endpoints, and these are mapped directly to a massive number of MCP tools, the AI agent faces a critical performance bottleneck. While an AI agent might be excellent at finding the right tool from a small, curated list (e.g., fewer than 20 tools), its performance degrades rapidly when faced with a "haystack" of thousands of options.

This is a fundamental challenge for the standard AI agent tool selection model. The agent becomes overwhelmed, struggling to find the right tool among a chaotic number of choices, leading to poor performance and unreliable outcomes.

Solutions & Scaling

Now that we have established why APIs are critical for AI and the scaling problem that arises, we can discuss two primary solutions for making APIs truly scalable for AI agents.

• The Relevance Funnel: One highly effective solution is a multi-stage process that intelligently narrows the search space. This four-stage funnel starts by narrowing 100,000+ APIs to ~10 candidates using DevNet's semantic search and vector embeddings. An LLM then optimizes and enriches these candidates with essential business context. Finally, a confidence-based reranking system identifies the single best tool to execute, ensuring the AI agent always finds the right tool from even the largest ecosystems.

• The Arazzo Advantage: Another, more powerful solution is using Arazzo. Instead of exposing every single API endpoint as a tool, we define complex, multi-step workflows as a single, high-level tool. For example, a "User Provisioning" tool could contain a sequence of API calls that create a user, assign roles, and send a welcome email-all under a single Arazzo specification. This approach drastically reduces the number of tools the AI agent has to manage, solving the scaling problem and leading to high performance and precision.

Conclusion: The Symbiotic Loop

This is the final and most powerful part of the relationship. APIs give AI a "hand to act on the world" and a "body to sense it," providing the data and actions it needs to function. In return, AI enhances the very APIs that enable it, making them more discoverable, more complete, and more intuitive for developers.

This is a powerful feedback loop. As AI uses more APIs, it learns how to make them better, and better APIs make AI more capable. We are entering a new era of productivity and innovation, driven by this symbiotic relationship between APIs and AI.

This blog post is based on the session "AI-Powered APIs and API-Enabled AI: A Symbiotic Evolution Driving Mutual Innovation" which I presented at API World 2025 on Thursday, September 4th.