APIs for AI: Have we failed?

Slide 1

Slide 1 text

Zdeněk “Z” Němec, superface.ai, October ’24 APIs for AI: Have we failed? superface.ai

Slide 2

Slide 2 text

Shall we stop building APIs? I am here to tell you that we should probably stop building APIs unless we change how we do it. superface.ai

Slide 3

Slide 3 text

Zdeněk “Z” Němec • designed an API description language • pioneered API-design & API-first • built APIs with the largest enterprises • building API infrastructure for AI agents • building AI agents Founder and CTO of Superface.ai • DSL director Apiary.io → Oracle • Founder of Good API consulting • Enterprise API strategy and execution superface.ai

Slide 4

Slide 4 text

LLM-powered Agents superface.ai

Slide 5

Slide 5 text

LLM-powered Agents • An agent is a software that acts on behalf of user or another program • LLM-powered agents can independently • perform tasks • make decisions • interact with other systems • Agent needs tools to be able to do meaningful things superface.ai

Slide 6

Slide 6 text

Tools LLM-powered agents • Agents are only as good as the tools they have • computation • databases • API calls • LLM works more like a human • It’s able to fi gure out what endpoints to call from API documentation • Agents are more resilient to API changes LLM-powered Agent Memory Planning Tools APIs superface.ai

Slide 7

Slide 7 text

You would think the APIs are the best things for agents superface.ai

Slide 8

Slide 8 text

In many situations it is easier, faster and cheaper to access data and perform actions via UI over API. Often, it is the only way. superface.ai

Slide 9

Slide 9 text

LinkedIn A minute vs. several weeks • LinkedIn API exists • It is not easily accessible to developers • The functionality is limited • Using 3rd party scraping service • Connect my agent to LinkedIn in one minute superface.ai

Slide 10

Slide 10 text

Instagram Two minutes vs. several weeks • API exists but it is not accessible • Some of our most popular articles are regarding getting the access to API • Using Apify web actor we are able to read data from Instagram in two minutes superface.ai

Slide 11

Slide 11 text

Accessing a Salesforce instance of a biggest HW maker Deal or no deal • Entering data into CRM • The case was saving 38hrs / week • Agent did not get the API access to the CRM • Entering the data using web actor (scraper) works superface.ai

Slide 12

Slide 12 text

There are many more similar stories • No access to API for agent developers • Legacy APIs (WS/RPC) • API can do only fraction of what UI can • Overcomplicated APIs superface.ai

Slide 13

Slide 13 text

Jesse Lyu, Founder and CEO @rabbit “We don’t like to work with APIs because you are betting everyone will give you an API which is not the case. It’s easier for OpenAI to get an API built or open for them, it’s hard for startups to convince the API providers.” https://www.youtube.com/watch?v=X-MNgciL5hw superface.ai

Slide 14

Slide 14 text

Problems with APIs and AI APIs are slowing down AI agents • API does not exist • You won’t get access • The functionality is not there • It’s impossible to convince companies to built functionality for you • Companies have no incentive to do it • → API Economy superface.ai

Slide 15

Slide 15 text

API Economy Business drivers for building APIs Innovation & e ffi Value add Partners Stickiness Direct monetization superface.ai

Slide 16

Slide 16 text

API Economy Business drivers for building APIs Innovation ffi Value add Partners Stickiness Direct monetization the case for AI superface.ai

Slide 17

Slide 17 text

API Economy Business drivers for building APIs Innovation ffi Value add Partners Stickiness Direct monetization what are agents challenging: commoditizing your SaaS apps superface.ai

Slide 18

Slide 18 text

API Economy Business drivers for building APIs Innovation ffi Value add Partners Stickiness Direct monetization what are agents challenging: commoditizing your SaaS apps B2B agents

Slide 19

Slide 19 text

API Economy Business drivers for building APIs Innovation ffi Value add Partners Stickiness Direct what are agents challenging: commoditizing your SaaS apps B2B agents agents purchasing capabilities

Slide 20

Slide 20 text

API Economy Business drivers for building APIs Innovation ffi Value Partners Stickiness Direct what are agents challenging: commoditizing your SaaS apps B2B agents agents purchasing capabilities agents adding value on top of API

Slide 21

Slide 21 text

Attention economy AI challenging the stickiness • Salesforce launched its "End of Software" campaign in 2000 • 25 years since the inception of SaaS / Cloud • Most users don’t like to work with CRM (and software ) • No.1 use-case for Superface agent is dealing with CRM • But companies want us to stick in front of the screen, with their UI superface.ai

Slide 22

Slide 22 text

“Governance” problem AI challenging the value add • Limited data integration • Power plant operators have to observe the dashboards and react when something happens • A “scraping” solution was developed because of the lack of data integration • A camera observing the dashboard with image recognition alerts the workers when a reaction is needed superface.ai

Slide 23

Slide 23 text

There is one more problem with AI and APIs… superface.ai

Slide 24

Slide 24 text

LLM performs miserably finishing the complex tasks with complex APIs superface.ai

Slide 25

Slide 25 text

Agents are the future of API consumption superface.ai

Slide 26

Slide 26 text

The way agents have to interact and do business with APIs is broken superface.ai

Slide 27

Slide 27 text

If you can’t use APIs… superface.ai

Slide 28

Slide 28 text

LAM: Large action models superface.ai

Slide 29

Slide 29 text

• Instead of tools, LAMs use web and screen actors to interact with systems on your behalf • Similar to robotic process automation, but • more capable (reasoning, semantics inference) • in fi nitely more reliable (no hard-coded UI) • usable by end-users (users can add actions) • LAM interprets user commands and execute tasks LAM: Large Action Model Neuro-symbolic engine with actors superface.ai

Slide 30

Slide 30 text

Rabbit.tech How LAM works • Record users performing actions e.g. “using Uber Eats to order meatballs” • Record enough people over time • LAM understands and knows what am I doing, where am I clicking • Then, the action is invoked using voice via R1 device • Rabbit’s neuro-symbolic LAMs executes the action https://www.rabbit.tech/research

Slide 31

Slide 31 text

Open Interpreter “LAM” approach • Runs directly on your computer • Controls your computer and applications • Can be used with voice device communicator • Uses your identity since it runs on your behalf • You can “teach” it your work fl ows using voice https://github.com/OpenInterpreter/open-interpreter superface.ai

Slide 32

Slide 32 text

• Companies are scared of loosing attention • APIs do not exist • APIs are limited • APIs have a poor design LAMs running the actions reliably, without the need for APIs -vs- this wasn’t feasible before LLMs superface.ai

Slide 33

Slide 33 text

“Engineering of APIs is an unnecessary complication if all the data and actions can be achieved using the UI.” superface.ai

Slide 34

Slide 34 text

superface.ai We could be doing so much more useful work with agents but we are not because of the obstacles.

Slide 35

Slide 35 text

Have we failed with APIs? superface.ai

Slide 36

Slide 36 text

We need APIs more than ever! superface.ai

Slide 37

Slide 37 text

Get APIs right or people will either use LAM or walk away. ( and agents ) superface.ai

Slide 38

Slide 38 text

APIs are built for the old world • Agents are your new best friends • As API provider / product owner go out and look • The API consumption will be 80% agents and 20% humans • Do everything to support LLM-powered agents • API- fi rst • API-design for AI • Streamline API access • Drive the business incentives superface.ai

Slide 39

Slide 39 text

superface.ai The way humans and software are interacting has changed.

Slide 40

Slide 40 text

Attention economy will shift. • my agent does not care about your commercial • is my agent your daily active user? • what is your KPI? superface.ai

Slide 41

Slide 41 text

We won’t be manually integrating your API. We won’t be sitting in front of your UI. superface.ai

Slide 42

Slide 42 text

Thank you! Let’s talk Zdenek “Z” Nemec   Twitter/X: @zdne LinkedIn: https://www.linkedin.com/in/zdne/ superface.ai superface.ai

Slide 43

Slide 43 text

No content

Slide 44

Slide 44 text

LLM function calling And API design • Mechanism that LLM uses to recognize a and call a function (tool) • Ideally, we would give an API to LLM and it would fi gure it out • The more atomic and “normalized” the API is the harder it is to use • Complex tasks and atomic (high granularity) APIs makes it di ffi cult for LLMs LLM detects function requirements Structured function input Execution of the function Returning the result API call LLM function calling repeat multiple times superface.ai

Slide 45

Slide 45 text

UI vs. API APIs and Web • Hypertext (HTML) is a representation of resources • Originally a resource could have multiple representations (e.g. HTML and JSON) • APIs parted away from the original REST API concept • We are stuck with Web and APIs providing di ff erent capabilities • What is available via API is now a product (and business) decision Contact resource superface.ai

Slide 46

Slide 46 text

CAPTCHA and other anti-scraping • LLM is actually helping me to beat the anti-robot protection • anti-scraping race is something you don’t have to do if you have a solid API program superface.ai

Slide 47

Slide 47 text

https://www.reddit.com/r/Rabbitr1/comments/1fu5gst/ is_lam_still_a_thing_true_innovation_or_a_lie/ “Go to target.com and order 2 boxes of Fancy Feast canned cat food for me" 1. Opens the webpage 2. Searches for products 3. Adds them to the cart 4. Enters the order interface At the fi nal checkout interface, my input is required to con fi rm the order

Slide 48

Slide 48 text

Practically speaking How to minimize the need for LAM • API- fi rst • Provide the same data and actions as UI* • API product management • API design for AI: bundle atomic calls for complex task • Streamline access delegation • Make APIs access accessible • Security team should be helping secure the access not ensuring they are covered superface.ai