A Guide to Using AI for Salesforce Development Issues

AI is quickly becoming an absolute must for any DevOps developer worth their salt. From larger to more minor development issues, the right software used in the right way can make all the difference.

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When fixing Salesforce development issues, AI will have a truly transformational impact. In this blog, we’ll walk you through some of the critical need-to-knows when utilizing AI in Salesforce at maximum efficiency.  

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Let’s get to it.

What are the development challenges in Salesforce?

Salesforce is undoubtedly a robust, well-designed platform. Even so, it’s not without its complexities. Updates are regularly rolled out, which makes keeping your testing methodologies up to scratch tricky. Manual work fixing issues is also a huge time-drainer when testing and executing rapid deployment strategies, and it leaves you with worse results in the long run. On top of all that, manual testing doesn’t fit well with scalability as Salesforce applications continue to evolve. 

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Let’s examine some of the challenges that highlight the need for specialized tools and methodologies tailored to the Salesforce environment to improve the development experience, streamline workflows, and enhance the overall quality and efficiency of Salesforce application development.

1. A lack of additional help

Salesforce offers extensive support for companies of all sizes, providing a vibrant ecosystem of documentation, tools, and community support. However, while Salesforce rightly offers substantial resources for users, tools like CopadoGPT can be handy when deadlines are tight. 

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An AI assistant tool such as CopadoGPT helps you find answers to your development issues like *that*. The tool is a bottomless well of knowledge that can be drawn from 24/7 and even helps you prepare simplified test planning frameworks for the future. Trust us: it will immediately enhance and streamline your troubleshooting and development process through extensive, AI-driven insights and automation.

2. Time spent on manual testing

Manual testing isn’t just laborious; it’s also time-consuming, inefficient, and ineffective. It’s been a vital part of DevOps strategy for years, but that’s changing quickly. Draining resources in this way only leads to poorer-quality development in the long run, and team leaders have noticed this. In this realm, AI is firing on all cylinders.  

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Unfortunately, many Salesforce development teams rely on a mix of manual steps and only light automation. This approach can lead to infrequent and error-prone deployments, making it challenging to maintain high standards of quality and reliability in the development process. With an AI assistant, you can enable your team to enhance testing efficiency and help uncover those development issues quicker, all while achieving more impressive results. That’s less time spent testing and more time spent on crucial problems. 

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On top of time refinement, AI will also improve accuracy and drastically reduce the likelihood of human errors. Copado's Robotic Testing, which offers features like natural language processing and parallel test execution, is the perfect example. The benefits don’t end there either; Robotic Testing provides lower maintenance, enhanced quality, and automation for business testing and all other aspects of Salesforce. We could go on…

3. Slow deployments

The smooth running of a DevOps pipeline, more generally, is a significant cog in any well-oiled DevOps machine. A split between development and testing (extremely common within DevOps teams) can lead to broader, disparate issues, including slow release times and low-quality results. On top of this, Salesforce imposes specific limits on the types of changes that can be deployed, and tracking these changes presents a whole host of challenges. This can lead to situations where developers need to manually log into the Salesforce organization to complete deployments, increasing the risk of errors and inconsistencies.

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The challenges don’t stop there, either. Traditional development tools and CI/CD pipelines are not always compatible with Salesforce, requiring the use of specialized tools like change sets and the Ant Migration Tool. The lack of examples and established practices for building comprehensive CI/CD pipelines in Salesforce further complicates this issue.

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Our AI-powered Salesforce Continuous Integration and Continuous Deployment (CI/CD) product integrates development and testing in a single pipeline. The result? Advanced branch management, automated deployments, instant rollbacks, quicker feedback loops, and fewer manual tasks. AI, in this form, will also predict and resolve conflicts well before they impact the main branch. Thanks to this, you can ensure smoother deployments all round, with much less downtime. Ultimately, a well-integrated CI/CD for Salesforce system delivers continuous innovation.

4. Scalability, release, and customization issues

One thing’s for sure: your organization and Salesforce are constantly changing. When businesses grow, their operational requirements do, too. This leads to broader development issues further down the road, which can quickly snowball. Frequent updates and robust customization capabilities are another headache for developers. Regular releases from Salesforce can muddle up your ability to maintain and test complex customizations, especially when trying to ensure that all custom components and integrations continue to function correctly after updates.

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With AI, scaling can be much more accommodating, giving your organization the ability to scale upwards without quality going in the other direction. AI tools are now particularly adept at adapting to changing environments and requirements. A prime example is the ability AI has to analyze trends and usage patterns to make predictions for future needs. The technology can then present infrastructure adjustments before any performance bottlenecks occur.

5. A lack of shared knowledge and learning

As Socrates said, “The only true wisdom is in knowing you know nothing.” Even the smartest DevOps employee understands that there’s always something new to learn. 

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Salesforce development requires a unique set of skills that combines both declarative (admin-level) and programmatic abilities. The platform's unique nature means that traditional development skills and tools are often not directly transferable to Salesforce projects, which can slow down the adoption of best practices like continuous integration and delivery. 

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In addition to this, and unlike traditional software development, Salesforce doesn’t allow for a local development instance. Developers must work directly within the Salesforce cloud environment, which can limit testing and development flexibility. This central cloud-based model requires developers to deploy functionality updates directly to a specific Salesforce instance, complicating the development process.

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With that said, the ability to learn and gain knowledge must be a high priority for any team searching for DevOps success. That’s precisely why tools such as CopadoGPT are so vital. Our tool not only provides answers to complex questions but also facilitates shared learning and knowledge among your team. It has the ability to guide users through complex Salesforce configurations or automate routine tasks, allowing team members to focus on more strategic initiatives. Every day is a school day, and you and your team will be smarter for it.

The solution? AI-powered DevOps

Embracing AI, from AI-powered Robotic Testing to CopadoGPT, will empower each and every team member in the development cycle, bringing with it a huge range of benefits at every stage. Our AI-powered Robotic Testing is the perfect example, supplying simplified scripts, handy insights, and test automation without the headaches. 

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By leveraging AI in the following ways, Salesforce development teams can also address the common challenge of slow deployments, ensuring that they can deliver updates and new features more rapidly and reliably using CI/CD pipelines.

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Automated testing: AI-powered tools can automate the testing process, which is a critical component of deployments. By using AI to conduct regression, performance, and integration testing, teams can quickly identify and resolve issues before they impact the production environment.

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Predictive Analytics: AI can analyze historical deployment data to predict potential issues and bottlenecks in the deployment pipeline. By understanding trends and patterns, AI can provide suggestions for optimizing the deployment process, such as the best times to deploy, potential risk areas, and more. This proactive approach helps in planning and executing deployments more efficiently.

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Advanced Branch Management: AI can assist in managing complex branching strategies in version control systems, ensuring that the integration of new features and updates is smooth and conflict-free. AI tools can automatically merge branches and resolve conflicts, which minimizes delays and manual interventions required during the deployment process.

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Change Impact Analysis: AI can perform impact analysis to determine the effects of proposed changes on the existing Salesforce environment. This helps in understanding the implications of changes and planning deployments that minimize disruption to the system. By predicting the impact of changes, AI enables more strategic deployment planning.

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Deployment Automation: AI enhances deployment automation by learning from past deployments and continuously improving the deployment scripts and processes. This includes selecting the optimal components for deployment, scheduling deployments to reduce downtime, and automating rollback procedures if issues are detected.

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Real-time Monitoring and Adjustments: During the deployment process, AI can monitor the application's performance and stability in real-time. If an issue is detected, AI can trigger automatic rollbacks or adjustments to ensure the system remains stable and available, thus reducing downtime and manual monitoring efforts.

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By leveraging AI in these ways, Salesforce development teams can address the common challenge of slow deployments. This not only improves the development lifecycle but also enhances overall agility and responsiveness.

Resolving development issues with CopadoGPT

Automation enables you to unlock smooth, fuss-free DevOps, but AI can be used in different ways too. Our AI DevOps advisor CopadoGPT helps you find all the right answers to your questions and is geared towards empowering your team by unlocking real-time answers and suggestions. Here are just a few of the ways it can help resolve your development issues:

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• Find answers to your problems on conflict resolution, metadata or general development issues.
• With additional tailored recommendations based on your specific team role, Copado onboarding will be quicker, smoother, and more straightforward.
• Create step-by-step instructions in order to fix your Salesforce problems.
• A vast knowledge base helps you enhance your knowledge of Salesforce development.
• Stay prepared with simplified test planning that provides a structured framework shaped for your project.

Interested in implementing CopadoGPT? Find out more here and get exclusive access.

Elevate your DevOps strategies with AI today

AI is a game-changer. When implemented correctly, it will transform how your team executes projects, big and small. Copado’s own GPT chatbot and Salesforce DevOps solution are another example of how you can supercharge human potential by fixing development issues and creating test automation scripts. 

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Enabling your team with an AI-powered DevOps solution will not only save you heaps of time but also deliver tremendous results. So… what are you waiting for?

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