Software developers are under more pressure than ever — juggling complex codebases, repetitive tasks, and the constant need to innovate. These challenges create bottlenecks, slowing down progress and increasing burnout. To address these challenges and unlock developer potential, companies are turning to a new generation of AI developer tools.  

Research backs this trend, with 96% of software developers believing AI will improve the developer experience and four in five expecting AI agents to become essential tools in app development.

Salesforce has built several AI-powered tools to boost developer productivity. For example, its internal tool CodeGenie is transforming how software engineers work at the company. Similar to Agentforce for Developers, which helps external Salesforce developers write code, CodeGenie is trained on Salesforce codebases to help developers at Salesforce. More than that, it’s helping the company improve its AI products, deepen its understanding of this emerging technology, and share insights with the broader community. 

Here’s a closer look at how Salesforce is putting CodeGenie to work — and what its developers have learned along the way. 

CodeGenie: Paving the way for developer agents

CodeGenie is designed to boost developer productivity within Salesforce. Built in-house by Salesforce AI Research and fine-tuned using proprietary Salesforce repositories, CodeGenie supports Salesforce’s developers at every stage of the software development lifecycle, from writing and reviewing code to answering developers’ questions in real time. The results have been remarkable:

• 7 million+ lines of code accepted by developers at Salesforce.
• 500,000+ developer questions answered through AI chat.
• 30,000+ hours saved per month.
• Seamless integration across IDEs, GitHub, Portals, CLI, and Slack.

This reflects Salesforce’s broader engineering strategy, where AI-driven insights power efficiency and innovation. The Engineering 360 dashboard, for example, unifies engineering data to help teams make more informeddata-driven decisions. Capable of managing up to 90 billion records with rapid response times, it scales seamlessly alongside Salesforce’s growing engineering organization. AI tools like CodeGenie further enhance this ecosystem by streamlining development workflows and maximizing developer productivity.

CodeGenie helps handle repetitive work, giving me more time to focus on solving complex problems and building great software.”

NaveenKumar Namachivayam, Senior Software Engineer at Salesforce

“CodeGenie helps handle repetitive work, giving me more time to focus on solving complex problems and building great software,” said NaveenKumar Namachivayam, Senior Software Engineer at Salesforce. “It speeds up my workflow and seamlessly integrates into my development process. It’s like having an extra set of hands, making coding faster, smarter, and more efficient.” 

Insights from Salesforce’s Own AI aAdoption

Salesforce’s developers’ use of these tools goes beyond internal experimentation to, it’s a real-world demonstration of how AI enhances productivity and collaboration. Early adoption has surfaced key lessons:

• Working with AI as a true collaborator: – AI tools act as intelligent partners, boosting productivity by assisting with complex coding and enhancing effectiveness withby providing real-time support for developer questions.
• Ensuring seamless integration: — AI must fit naturally into existing workflows to be truly effective. CodeGenie, foras one example,  integrates effortlessly across IDEs, GitHub, CLI, and Slack, accelerating adoption with minimal latency.
• Eliminating busywork sparks innovation: — By handling time-consuming tasks like coding, debugging, and test generation, AI-powered tools free developers to focus on high-value problem-solving and creative solutions.

These lessons don’t just not only inform developers’ work at Salesforce —, the results and feedback from CodeGenie feed directly into improvements for the company’s external product offerings. For example, CodeGenie’s logistic regression model – which determines when and what code completions to display for developers – served as a valuable pilot for Salesforce’s Agentforce for Developers. Developers at Salesforce tested and evaluated the tool internally before ultimately deploying the feature in Agentforce for Developers, where it now enhances the coding experience for Agentforce for Developers users.  

By refining and iterating AI in-house, Salesforce is addressing common developer pain points like navigating complex codebases and troubleshooting before it ever brings these capabilities to the market. This not only improves internal efficiency but also provides a blueprint for transforming software development at scale.

Learn more:

• Read how Agentforce resolved 80% of visitor issues on the Salesforce Help site
• Learn more about how CodeGenie is enhancing developer productivity
• Dive deeper into Salesforce’s latest developer research
• Explore Agentforce for Developers

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