Enterprise GenAI hires an agent

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Welcome to Runtime! Today: why agents are the new vehicle for enterprise AI ambitions, OpenAI secures the bag, and the latest moves in enterprise tech.

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Reasoning to believe

A computer is very good at executing a task when you tell it exactly what you want it to do and exactly how you want it done. Until now, when businesses needed to understand the more ambiguous needs of their customers they've turned to humans to get the job done, which is exactly the problem that the AI merchants of our time were determined to solve in September.

Nearly a dozen enterprise tech companies announced plans for AI agents last month, expanding two years of investments in generative AI technology in search of a winning formula. "We're going to do not only the largest deployment of agents, but the best possible agents you could possibly have," said Salesforce CEO Marc Benioff during a September press conference, as determined as ever to crank the hyperbole to 11.

No one really agrees on a strict definition of "agent," which of course allows the puffery to flow, but recent breakthroughs in large-language models have allowed companies to build enhanced versions of chatbots that can respond to natural-language queries with a plan of action.
Many of the agents introduced last month build on the "reasoning" capabilities of new LLMs like OpenAI's o1 models.
It's a term that is as annoyingly anthropomorphized as everything in this industry and describes how applications built around these models can take a new piece of information, evaluate that new data against a massive pool of old data while determining how it relates to a predetermined list of tasks it has been empowered to execute, and select the best path forward.
"Planning and reasoning is very hard," said Ashok Srivastava, chief data officer at Intuit. "It's hard for humans to do, it's much harder for machines to do."

Agents can be thought of as the second generation of the RPA movement, which promised to robotically automate the business processes all companies need to function on a day-to-day basis. A categorical example of RPA was the invoice-processing bot system, and this graphic produced by Menlo Ventures illustrates the number of steps involved in a typical workflow.

But RPA systems fell down when it came to handling unstructured data or poorly structured data, and developed a maintenance-heavy reputation as a result.
Generative AI, on the other hand, was designed to work with unstructured data, even if it needs tools like RAG to reduce the number of errors it tends to make processing that data.
"We started with scripted workflows, we have RPA workflows, we have conversational workflows," said Dorit Zilbershot, vice president of product management at ServiceNow. "It's just an evolution of the technology to now have an AI agent workflow."
AI researchers have been talking about agents for decades, but newer LLMs deliver on the six properties laid out by Shopify's Julia Winn that make up agents: they have perception, interactivity, persistence, reactivity, proactivity, and autonomy.

However, as the enterprise software industry tries to cram agents into anything and everything, it's not clear how many companies are ready to take advantage of the technology. Like any generative AI technology, unlocking whatever special outcome is promised by the tool requires sharing a ton of data with that tool in tool-friendly ways.

When Intuit started building an internal AI platform that allows its developers to create agents for internal and customer-facing use, "we made a huge investment in modernizing our data platform," Srivastava said.
That required breaking down the barriers between different types of data and creating a map of all that data that drew links between similar data types.
"Data hygiene is even more important today than it was in the past," Zilbershot said. "Everything can be knowledge for those AI agents, and so they're really able to leverage unofficial knowledge that exists in organizations and uncover existing patterns without a lot of investments from people."

Read the rest of the full story on Runtime here.

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Open for business

OpenAI just pulled off what Axios called the largest venture-capital deal in history, raising $6.6 billion to value the company at $157 billion. For comparison, ServiceNow was worth $183 billion at the close of Thursday's stock market and Palo Alto Networks was worth $109 billion, putting a company with pretty limited enterprise revenue up there with some of the giants of the present time.

OpenAI also secured a $4 billion line of credit on Thursday, which extends the total amount of money it can throw at advancing AI to over $10 billion. Microsoft and Nvidia participated in the $6.6 billion equity round, knowing they'll get a lot of that money back directly as revenue in a common practice that is starting to get really lame.

Despite all the executive turmoil OpenAI's rank-and-file has remained remarkably loyal over the last year, according to an analysis published Thursday by Bloomberg. But this is the point at which things start to get weird for any high-flying "startup;" living up to that valuation is going to require real enterprise products and real revenue.

Enterprise moves

Surabhi Gupta is the new CTO at Klaviyo, joining the marketing automation company after several years at Robinhood and Airbnb.

JP Vasseur is the new senior distinguished engineer and chief architect of AI and networking at Nvidia, following a legendary career at Cisco building its networking and AI strategy.

Angela Lim is the new chief growth officer at OXIO, adding more than two decades of experience working at AT&T to the telecom upstart.

Jordan Mauriello is the new chief strategy officer at Stratascale, joining the cybersecurity company after 10 years at Critical Start.

Steve Baird is the new executive vice president and chief revenue officer at Hyland, following several years in similar roles at SAP.

The Runtime roundup

The Department of Justice is expanding its probe into allegations of price-fixing by SAP and Carahsoft, seeking information on their business dealings with nearly 100 government agencies.

After soundly defeating a patent troll at trial, Cloudflare settled all outstanding claims by getting the troll "to dedicate its entire patent portfolio to the public."

Supermicro is working with Fujitsu on a server using Fujitsu's upcoming Arm server chip, which could test the market for on-premises Arm servers.

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