The rapid evolution of artificial intelligence is compelling businesses to create and introduce new offerings faster than ever or face the risk of being outpaced by more agile rivals.
Salesforce believes it has discovered a method that enables it to adapt even amidst the uncertainty of AI’s future direction. The behemoth in customer management software is sourcing input for its AI strategy in real time.
Salesforce is by no means the only firm to actively collaborate with its clients for insights on its products. However, what sets it apart is the company’s vast scale, the speed of new product launches or updates, and the detailed nature of these collaborations. These exchanges occur far more frequently than annual or quarterly meetings; some customers are engaging with Salesforce as regularly as once a week.
“The 18,000 customers are a significant reservoir of insights and critical information necessary for achieving customer success,” stated Jayesh Govindarajan, executive vice president at Salesforce AI, during a recent discussion with TechCrunch. “The stack we’ve developed has resonated with these clients. Over time, we will enhance our context, and as it improves, and LLMs advance, agent systems will perform increasingly autonomous functions. That’s an ongoing path of innovation to which we will commit resources.”
Salesforce was among the pioneers to roll out AI agent management software in late 2024, even before agentic AI began to capture media attention the subsequent year. Since then, the company has intensified its efforts and is persistently launching new products for voice AI and Slack at a brisk pace.
The rapid pace of product introductions is credited to Salesforce’s clientele. According to the company, by allowing its customers to guide the process, it can create an AI product roadmap that swiftly adapts to the evolving landscape of AI technology.
As large language models emerged, businesses eagerly sought to leverage the technology but lacked the necessary final applications to fully utilize LLMs, explained Muralidhar Krishnaprasad, president and chief technology officer of Salesforce engineering, in a conversation with TechCrunch.
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The necessity for that final technology is what prompted Salesforce to unveil its agent management platform, Agentforce, according to Govindarajan.
From this point, the firm embraced a grassroots strategy directed by themes — such as agent context, observability, and deterministic controls, among others — rather than specific product timelines. This method involves direct feedback from rotating customer groups to design products under the assumption that other businesses will encounter similar requirements.
Customers in control
“The advancements we’ve made come directly from collaborating with a vast array of these customers and categorizing the challenges they face in the marketplace,” Govindarajan shared. “Then we analyze that and determine which issues can be addressed at the LLM level and which cannot. For the latter, we need to develop a sort of agentic operating system components around the LLMs to be able to achieve that.”
Close collaboration with customers’ engineering teams enables Salesforce to address issues swiftly before the technology surpasses them.
“We can’t afford to wait three or six months for feedback and then take another six months to address it,” Krishnaprasad stated. “We are actively responding, week by week, month by month. This has been a significant change. Now we deploy code quickly and have various checkpoints to test new features and gather early feedback prior to wider release. These are all adaptations we’ve had to make to respond to the rapid shifts in this landscape.”
Engine, a travel management platform, is one of the companies engaged in Salesforce’s customer feedback loop. This relationship is not casual; the operations team at Engine meets with Salesforce weekly, as reported by Engine founder and CEO Elia Wallen.
Through this collaboration, Engine gains early access to AI tools ahead of their public launch. Wallen highlighted that this access helps Engine maintain its competitive edge and derive greater value from these tools than it could otherwise achieve.
The benefits are mutual.
Wallen noted that feedback from Engine has been integrated into Salesforce’s tools. For instance, Wallen once directed an AI voice agent to reserve a hotel in Chicago but found the interaction felt somewhat artificial and reported this to Salesforce. Subsequently, adjustments were made, and the company’s A/B tests began yielding improved results.
“If someone is genuinely willing to assist in curating and developing solutions we require, they can understand our challenges better and find effective ways to address them,” Wallen said. “For us, it’s excellent to be included in such processes because we can shape the product.”
This strategy also enables the company to implement solutions and workflows crafted by users across its larger client base.
The federal credit union PenFed has managed to streamline its technology stack by closely collaborating with Salesforce, according to Shree Reddy, the company’s chief innovation officer and executive vice president, who spoke with TechCrunch.
“We dedicate our time and effort to platforms that are more strategic, and we naturally invest significantly in this partnership,” Reddy commented about Salesforce. “This investment has produced favorable outcomes in terms of strengthening that collaboration, with mutual impacts that yield enhanced value for both parties.”
Reddy shared that PenFed developed an IT service management (ITSM) workflow independently using existing tools and agents in Agentforce that worked effectively for the organization. Salesforce recognized this success and expanded the tool for use across its platform for other businesses as well.
A potential drawback of this approach is its reliance on the traditional notion that the customer is always right. Salesforce is hopeful, despite numerous businesses still determining the role of AI in their operations and many not having realized value from the technology. Consequently, these businesses might not offer the best insights for long-term product development.
Additionally, a willingness to test and explore technology in beta today may not necessarily predict long-term usage patterns or future software agreements either.
Maximize internal usage
The company adopts this grassroots philosophy internally as well. Govindarajan mentioned that Salesforce employees are the primary users of its AI offerings.
Moreover, the company redirected its workforce and resources at the onset of the AI surge. Following the release of ChatGPT, Salesforce reallocated teams and resources to establish a new AI division — a strategy the company has successfully implemented during previous innovation phases, according to Krishnaprasad.
“As technology evolves, we can never predict what will emerge a month later,” he noted. “We will adjust accordingly. That’s what we did throughout the past year. If you consider, agents weren’t even on the radar just a year and a half ago. We needed to respond to all the developments and adjust to our customers’ needs.”