User story to deployable Salesforce code in 2 hours, down from 8, with Gemini
A Gemini-powered solution that turns user stories into Apex and LWC code, test cases, and test scripts, with an engineer validating every output.
Outcome
Release cycles about 35% faster, developer productivity up 30 to 40%, debugging time down more than 20%, and development costs cut 50% by automating test case and test script generation.
Global technology leader, developing and deploying Salesforce features and customizations
Engagement
Rapid prototyping of Salesforce-specific use cases, then a Salesforce-centric code, test case, and test script generation solution
Scope
Apex classes, Lightning Web Components, triggers, SOQL queries, schema, and metadata, within Salesforce governor limits
Maps to below services
AI & ML Engineering
Where it started
Salesforce projects averaging three to six months, with half or more of developer time spent on repetitive work.
Business problem
Developing and deploying new Salesforce features and customizations took three to six months per project on average. Developers spent significant time on repetitive coding, and turning user stories into test cases took 50 to 60% of their time.
Technical barriers
Keeping code consistent, documented, and testable across projects was getting harder, and debugging took about 15% more time as a result.
Agivant's role
Rapid prototyping, Salesforce-aware prompt engineering, and code, test case, and test script generation with human validation
What Agivant built
Agivant prototyped Salesforce-specific use cases, then built a Salesforce-centric coding, test case, and test script generation solution powered by Gemini. It generates high-quality Apex and LWC code directly from user stories and automatically creates comprehensive, accurate test cases. It works from a deep understanding of Salesforce specifics, including Apex, LWC, SOQL, and governor limits, and uses advanced prompting for precise and compliant output. Value in days and weeks.
User story to code
Generates high-quality Apex and LWC code directly from user stories, significantly reducing development time.
Test case generation
Automatically creates comprehensive and accurate test cases, improving test coverage.
Test script creation
Produces test scripts alongside the code, speeding up the QA process.
Code context awareness
Reads active Apex classes, Lightning Web Components, triggers, and metadata as input.
Schema and limits awareness
Works from SOQL queries, the Salesforce schema of objects and fields, and governor limits.
Chain-of-thought for Salesforce logic
Keeps generated output compliant with Salesforce best practices.
Prompt-chaining for complex tasks
Breaks complex requirements into linked prompts for precise output.
Human feedback loop
The model proposes a solution, an engineer validates or corrects the reasoning, and then the final code is generated.
How it is built
Models
Platform
Languages
Prompting
Controls
Gemini 2.0 Flash, 2.5 Flash, 2.5 Pro
Salesforce CRM
Apex, Lightning Web Components, SOQL
Chain-of-thought, prompt-chaining
Engineer validation before final code generation
Before
Three to six months per project, 50 to 60% of developer time on repetitive coding and test cases, and about 15% extra time on debugging.
After
User stories turned into validated Apex, LWC, test cases, and test scripts with Gemini, and an engineer confirming the reasoning.
Proof in production
An admin writes a user story, such as a contact search LWC that respects sharing rules, or error handling for DML operations in a batch Apex job. Gemini reads the Salesforce context, reasons through the logic step by step, and proposes the code with its test cases and scripts. An engineer validates the reasoning, and a user story that took 8 hours to turn into Apex is ready in 2.
Measured results
Faster Salesforce releases at half the development cost, with an engineer validating every output.
8 hrs to 2
User story to Apex
~35% faster
Release cycle
30 to 40%
Developer productivity gain
50% down
Development cost, by automating test cases and scripts
>20% down
Debugging time
90%
Test-case automation within two weeks
The repeatable pattern
Reusable asset
The Salesforce-aware prompting pattern, with org context, chain-of-thought, and human validation, now feeds Agivant's CPQ Lens accelerator. Every build amplifies the next.
Challenges overcome
Getting generated code to follow Salesforce best practices and governor limits on every output, which is why chain-of-thought prompting and engineer validation sit inside the workflow.
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