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AI + APIs — What 12 Experts Think The Future Holds
How AI and APIs are shaping the world as we know it, through the eyes of those building them.
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The Future of AI & APIs
The interplay of AI and APIs will dictate the future of technology. They are not only tools, but the very building blocks of the next generation of software.
With AI evolving so rapidly, APIs make connecting different applications and services easier than ever. APIs have become the connective tissue of the internet, enabling disparate systems to interact harmoniously. AI, on the other hand, is the brain that makes sense of a complex web of information.
In the years to come, AI and APIs will become the bedrock of our digital economy. As the pace of innovation accelerates, these technologies will enable startups to punch above their weight, challenging the dominance of established players.
The future will belong to those who can master these tools, not just because of the technological sophistication they represent but because of the fundamental shift from linear, procedural thinking to a more fluid, networked, and adaptive mindset.
APIs will simplify the process of creating complex solutions, allowing small teams to build on the shoulders of giants. AI, meanwhile, will unlock new levels of efficiency and personalization, transforming user experiences in ways we can hardly fathom today.
In this essay, we will highlight the thoughts and opinions of 12 experts on the opportunity that sits at the crossroads of AI and APIs.
Together, we’ll explore how AI and APIs are being used to:
Improve user experience.
Develop new products and services.
Disrupt legacy systems and processes.
We will also discuss the challenges that businesses face in implementing AI and so much more.
Let’s dive in.
“The combination of AI and APIs presents an exciting opportunity, with experts envisioning a landscape where AI's growth coincides with a surge in API development. The growing interest in AI translates into increased development of APIs. AI capabilities are becoming an integral part of products and services delivered through APIs, leading to a range of possibilities beyond technological advancements. The adoption of AI based tools has been quick and per 2023 Postman State of the API report Sixty percent of API professionals say they're using generative AI in their job.
The rising demand for AI-integrated solutions is expected to drive a corresponding need for roles such as API product managers, developer relations professionals, solution engineers, and AI/ML engineers. These experts will play a vital role in connecting sophisticated AI technologies with practical API implementation.
In this evolving scenario, the rise of AI is closely linked with the prominence of APIs as essential elements in the digital realm. As AI-powered offerings gain momentum, the importance of APIs as bridges for seamless integration and communication intensifies. The 2023 Postman State of the API report reinforces this trend, revealing that a significant number of respondents derive revenue from their APIs. This trend is particularly pronounced in sectors like finance and advertising, where API-generated revenue emerges as a key success metric. The burgeoning API economy is transforming APIs from mere technical components into revenue-generating products. This shift is reflected in the increased involvement of non-developer roles, such as chief technology officers, managers, and directors, who are now integral to API-related decision-making.
This confluence of AI and APIs offers a promising outlook where AI-powered advancements and API-driven solutions seamlessly integrate. As AI technologies become more accessible through APIs, the resulting demand for integrated solutions will lead to a need for skilled professionals capable of managing, developing, and implementing both AI and API technologies. This transformative trajectory will not only reshape our technological approach but also redefine organizational dynamics by elevating the role of APIs as revenue enablers and strategic assets in the digital landscape.”
“Things like Replit, Urbit, APIs, and generative AI are only going to accelerate the ease with which people can build something, and exacerbate the challenges for startups building undifferentiated products. Fleshing out where value accrues in this world probably deserves its own post.
This is classic Clayton Christensen stuff, namely The Law of Conservation of Attractive Profits: “The law states that when modularity and commoditization cause attractive profits to disappear at one stage in the value chain, the opportunity to earn attractive profits with proprietary products will usually emerge at an adjacent stage.”
I think the value from the app battle will emerge at two stages: below and above. Fierce competition at the app layer will create value that can be captured at the infrastructure layer (below) and interface layer (above).”
“APIs act as the enablers that allow companies to embed and harness the power of AI. Whether it’s allowing enterprises to unlock new insights, automate intricate tasks, improve customer service with NL, or utilize machine learning for tailored recommendations, APIs are democratizing access to AI for businesses of all sizes.
At Coast, we see this first hand. Businesses can demystify complex technologies by showcasing how powerful APIs can be integrated into existing workflows, driving faster and more consistent adoption. This synergy between AI and APIs not only nurtures innovation but also accelerates digital transformation, presenting businesses with an understanding and a gateway to leverage AI’s full potential.”
AI and APIs are a match made in heaven. These technologies are symbiotic and will be influencing a lot of growth. I see three key areas concerning the intersection between the two.
First, APIs are the conduit by which next-gen AI is being productized and integrated into all sorts of applications. For instance, anything creating a ChatGPT-like functionality will incorporate a large language model (LLM) through an API, such as the OpenAI Chat Completions API powered by GPT-3.5 or GPT-4. Integrating with APIs for generative AI means developers don't have to reinvent the wheel to access powerful off-the-shelf models.
Secondly, AI can be used within the development of APIs themselves. Some use cases include generating structures and schemas, code generation, testing for bugs and vulnerabilities, or linting API definitions against standard specifications. In this sense, AI can accelerate the design and maintenance of APIs.
Thirdly, generative AI can greatly help developer consumers integrate third-party APIs. For example, instead of browsing the documentation to find method names, parameters, and how to structure requests, AI could accept natural language prompts and generate requests in the programming language of choice. This would save time and reduce friction in the integration process.
However, accurate generation of glue code will hinge on up-to-date model training. As LLMs evolve, it also means that API owners must structure their developer portal resources to be effectively consumed and understood by public LLMs. This could emerge as a competitive edge for API providers and would also help improve accuracy and avoid hallucinations.
Overall, the surge of interest in AI will only benefit the adjacent API economy. However, development environments integrating LLMs should arm themselves with best security practices and review the new OWASP Top 10 for Large Language Model Applications as a starting point.
“The interaction between API producers and consumers is the critical interaction that has powered the SaaS revolution yet this workflow between the two has hardly changed in decades. There are two main ways i see LLMs creating step function changes in the ecosystem:
AI powered API lifecycle - The whole API lifecycle is fraught with friction and LLMs greatly improve developer efficiency. Whether its API design, documentation or maintenance for the producer or providing an assist for the API consumer with discovery, integration and testing LLMs can reduce the time to value and re-focus developer and company time on the core business problems rather than API problems.
AI as a primary consumer of APIs - We’re not far from applications that self discover and integrate to 3rd party services. Think Zapier or your favorite integration platform without needing to manage the data mapping yourself. Taking it a step further AI can figure out what APIs to call and use based on the task at hand. We already have agents that can be fed a set of “tools” to help answer a prompt. Imaging being able to pick any API out there for the task at hand.”
#6: Gil Feig — Co-Founder at Merge (byline from Merge Blueprint: Automating Integration Builds With AI)
Building Blueprint has accelerated our understanding of how LLMs can interpret code, such as API reference docs. We need our API-based integrations to be of the highest quality, so we started with a product that would be useful for our community while also helping us learn its long-term potential.
Don’t just build a wrapper on GPT. If you spend two weeks building something, anyone else can build it in two weeks.
It’s okay to take time here – just put one engineer on it and see what you can do. But don’t just build another thin wrapper on GPT if that won’t serve your customers and provide true value.”
"Modern software already runs on APIs. So if you believe AI is going to reinvent software (spoiler: it is), then you better believe the world of APIs matters.
Everything needs a good API. Software-to-software interaction is why APIs are so important already. The more functional or performant your APIs, the easier it is for a developer to integrate your data, service, app with theirs. Taking this one step further, if automonous software/agents are creating functions/services/apps. It will be critical that your API is easy to find, integrate with, and deliver if you want AI-assisted software to play well with your products (hint: you do).
API-first companies will continue to create major market value. OpenAI is a behemoth because builders want to build functionality, value, and entire companies on top of their incredible tech which are available as APIs. We have seen huge market value accrue to companies like Stripe and Google for the same reasons.
So it's worth asking - in a world where a SaaS app can be built via a few text prompts (i.e. building end user applications are easier then ever and there will be infinite SaaS) - where will the true market value accrue?
My answer: the building blocks and services that builders (human or AI) will rely on for core and advanced functionality."
“AI models are increasingly integrated into systems of engagement, primarily via APIs. This trend will significantly increase the number of APIs, and the dynamics of their usage will also evolve. I intend to delve deeper into this topic, but first, let's discuss the future of APIs.
This is not just a novel trend; it's a continuation of developments we've observed for a while now. Many large organizations, as well as web and mobile startups, face challenges due to the rapid advancements in their operational environments. They grapple with legacy systems, some of which are on-premise. Many are in the middle of cloud migration processes, and they often utilize third-party SaaS applications and API-based services. The sheer number of APIs integrated into their systems has reached a point where it's challenging to keep track.
A common term you might have come across is "API sprawl." This refers to the overwhelming number of APIs in use, to such an extent that organizations lose track of their deployments. Historically, the API management sector has provided tools to help organizations locate and implement these APIs. However, given the scale of API usage today, manual management is no longer feasible.
A concept gaining traction is dynamic discovery, which is essential for effective API governance. Being dynamic implies an automated method for discovering APIs. Some innovative techniques include scanning code repositories or using network sniffing to identify APIs. This capability is fundamental because it can be adapted to various situations. Companies like Akita, Optic, and Traceable AI have been at the forefront of dynamic API discovery.
This ability to continuously and dynamically detect APIs is crucial. For efficient governance, companies must have an almost organic approach, seamlessly integrating into their ecosystem, sensing changes, and identifying new APIs. In this context, AI can be a game-changer. Due to the vast scope and complexity of the issue, automation is essential for discovery, anomaly detection, and assimilation of vast amounts of data. Thus, AI will play a pivotal role in addressing these challenges effectively.
Given the vast number of API assets organizations possess, AI will be indispensable in navigating and managing them efficiently.”
“On one side, we’re seeing more interfaces that have natural language as an entry. Instead of going in manually clicking a bunch of filters and doing a bunch of manual searching, [users are] able to talk to the app, to talk to the software, in natural language — ‘find me shoes that are green that are size 11 that have a Nike logo.’ I can just type that in and it works. We’re definitely seeing more of that.
We’re also seeing a rise of companies who use large language models. They use AI under the hood to craft a better product experience, but you might not realize it at first. It’s behind the scenes. It’s part of creating a better product experience. And I think this is it’s a rapidly growing part of companies infusing AI into their existing product offering.”
“Imagine a world where millions of professionals across thousands of industries use domain-specific versions of Copilot to soar faster and higher to new levels of productivity, accuracy, and creativity. A world where professionals across all industries can use general-purpose tools (like our portfolio company Adept's Action Transformer) to harness the power of every app, API, or software program ever written via interfaces that allow them to describe the tasks they want to accomplish in plain language.
In dystopian visions of the future, technology in general and AI in particular are often characterized as forces that will lead to an even more polarized world of haves and have-nots, with the bulk of humanity being disenfranchised, marginalized, and immiserated by machines.”
It’s an exciting time within the API and AI spaces. Embracing the potential seems like the most advantageous approach and has already happened within sectors like technology. Progression in AI is seen as a natural evolution of how we interface with (and programmatical direct) computers. This is already evident in the curriculum for computer science programs, which has a different focus compared to when I studied it at the earlier part of this century.
The general education sector is being challenged by the disruptive force of ChatGPT and other offerings. Moving forward with AI at our side, the shift will move from quoting knowledge to instead proving one’s understanding. Perhaps that will be validated by the AI tutor or at least the software systems being used by our educators!
Complexity never disappears in the art of delivering software. It just shifts around, and as consumer expectations continue to increase, we still must focus on the quality attributes of software. With the predicted acceleration in API growth, more AI contributing to even more API production and consumption, and the general trend for more companies depending on third-party APIs to deliver core capabilities, it’s never been more important to be critical of API quality.
#12: Abhinav Asthana — Co-founder & CEO at Postman (via Generative AI and the impact on APIs and software development)
“One area where I see a lot of potential is the simplification of complicated graphical user interfaces. For complex tasks, graphical user interfaces often become hard to use, and actions hide behind rows of buttons, menus, shortcuts, and procedures. They require years of training for people to become proficient, and even then, most people struggle with them. Generative AI trained on domain understanding has the potential to simplify those experiences.
These AI bots won’t be limited to chat, but will be deeply embedded in the existing workflows through which humans interact with computers. For instance, bots will begin helping with intensive UI and data tasks, interacting through voice, and of course, interacting through a chat mechanism. In this scenario, APIs become the “hands and legs that power the ‘thinking’ that the AI is doing.
Until now, we have primarily been designing APIs for applications that are used by humans, but designing APIs for machines will become an increasingly important area,. If you are the leader of an organization, what does this mean for you? Well, if your organization doesn’t have APIs or has poorly designed APIs, you are invisible to these bots.”
The ideas from our dozen experts reveal a clear narrative: the symbiosis of AI and APIs is not just a trend but a seismic shift that's set to redefine our future.
APIs, the unsung heroes of our interconnected world, are poised to play an even more pivotal role, enabling a level of integration and efficiency that will make today's tech look antiquated. AI, with its uncanny ability to learn, adapt and optimize, will become the status quo of competitive advantage.
The merging of these two forces will create a stomping ground for innovation, enabling startups to challenge incumbents not just based on novelty but on speed, agility, and adaptability.
In this new world, the dichotomy of 'big' versus 'small' will give way to 'fast' versus 'slow' & 'smart' versus 'dumb.'
We're looking at a future where the rules of the game are rewritten. It's a future where the underdog has a fighting chance and where good ideas have a better shot at seeing the light of day. It’s a future I’m excited for.
So here's to the dreamers, the doers, and the disruptors. The stage is set. Let's see what wonders you'll create at the intersection of AI and APIs.
Until our next adventure.
Special thanks to Mama Schroeder for editing this essay (any typos are on her 😊).
The views in this essay are my own personal opinions and don’t necessarily represent the views of my employer, those mentioned in this article, or anyone other than myself.
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