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April 30, 2026Artificial intelligence advances at breakneck speed. Companies that don’t keep pace risk losing ground to faster competitors. Salesforce thinks it has found a solution: let customers guide its AI roadmap in real time.
The customer management software giant isn’t just gathering occasional feedback. It’s meeting with some customers weekly to shape product development. This approach helps Salesforce react quickly to AI’s rapid evolution while building tools that actually solve real business problems.
Why customer-led development matters now
Salesforce revealed its strategy in a recent interview with TechCrunch. The company works with 18,000 customers who provide constant feedback on AI products and features.
“The 18,000 customers are a wellspring of information and a wealth of information that is really needed to get to customer success,” said Jayesh Govindarajan, executive vice president at Salesforce AI.
This matters because enterprises wanted to use large language models when they first appeared, but lacked the infrastructure to implement them effectively. Salesforce filled that gap with tools like Agentforce, its AI agent management platform launched in late 2024.
How the feedback loop works
Salesforce organizes feedback around key themes rather than specific product timelines:
- Agent context and performance
- System observability
- Deterministic controls
- Real-world problem classification
“The innovation that we’ve brought, they are direct result of us working with a vast number of these customers and then classifying the problems they see in the real world,” Govindarajan explained.
The company can’t wait months for traditional feedback cycles. “We can’t wait three months or six months to get feedback, and then go figure out another six months of work,” said Muralidhar Krishnaprasad, Salesforce’s president and CTO of engineering.
Real examples from customer partnerships
Engine, a travel management platform, meets weekly with Salesforce’s operations team. The company gets early access to AI tools before public release, helping it stay competitive.
Engine founder Elia Wallen shared specific feedback that led to product changes. When he tested an AI voice agent for hotel booking, he found the interaction unnatural. After sharing this feedback, Salesforce updated the agent and saw improved A/B test results.
“If somebody is willing to actually help curate and build products that we need, they can help us better and really understand our problem and how they can solve it,” Wallen said.
Federal credit union PenFed developed its own IT service management workflow using Salesforce tools. The company’s success prompted Salesforce to roll out similar capabilities across its broader platform.
The risks of customer-driven strategy
This approach has potential downsides. It assumes customers know what they need from AI technology that’s still evolving rapidly. Many enterprises are still figuring out AI’s role in their business operations.
Companies willing to test beta features today might not become long-term users or renew software contracts. Customer feedback could lead to short-term solutions rather than strategic long-term development.
Internal adoption drives external success
Salesforce also uses its own AI tools extensively. Company employees are the biggest users of its AI products, providing internal feedback alongside customer input.
The company reorganized teams and resources when ChatGPT launched, creating dedicated AI teams. This mirrors strategies Salesforce has used during previous technology waves.
“As the technology changes, we never know what’s going to come out a month from now,” Krishnaprasad said. “We will adapt to it. And that’s what we did all of last year.”




