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Why Your AI Tool Needs Salesforce Context

Generic AI tools see files. They don't see governor limits, org-specific patterns, or the order of execution. Here's why that matters — and what you can do about it.

NG

Nishant Goswami

Your AI coding assistant is brilliant at general programming. Give it a Python script, a React component, or a Go service, and it will generate solid code, suggest improvements, and catch bugs.

But ask it to write an Apex trigger, and things get interesting.

The Problem: AI Without Context

When a general-purpose AI writes Salesforce code, it's working from a general understanding of programming — not from Salesforce platform knowledge. This leads to predictable problems:

Governor limit violations. The AI writes a SOQL query inside a for-loop because it doesn't understand that Salesforce limits you to 100 SOQL queries per transaction. In any other language, querying inside a loop is just a performance concern. In Salesforce, it's a runtime exception.

Incorrect patterns. The AI generates a trigger that directly queries or modifies records without using trigger context variables. It doesn't understand Trigger.new, Trigger.oldMap, or the execution order that governs when each runs.

Missing best practices. The AI doesn't know about the "one trigger per object" pattern, or why you should use handler classes, or that @future methods can't call other @future methods. These aren't in the language spec — they're tribal knowledge.

The Scalpel vs. The Hammer

Think of a general-purpose AI as a hammer. It's useful for a wide range of tasks, but it treats everything like a nail. Every Apex class looks like a Java class. Every SOQL query looks like SQL.

What Salesforce developers need is a scalpel — a tool that understands the specific constraints, patterns, and best practices of the Salesforce platform. Not just "how to write code," but "how to write code that works on Salesforce."

What Salesforce Context Actually Means

Real Salesforce context isn't just documentation. It's a layered system of knowledge:

  1. Platform documentation. The official Salesforce docs — API references, object schemas, method signatures.

  2. Governor limits and constraints. The 200 DML operations per transaction. The 50,000 rows per SOQL query. The 10-second CPU time limit. These aren't suggestions — they're hard limits that will crash your code.

  3. Best practices. Bulkification. One trigger per object with handler classes. Using Database.insert with allOrNone: false for partial processing. The patterns that experienced developers follow.

  4. Tribal knowledge. The 46 rules that come from years of production deployments. The gotchas that aren't in any documentation. The anti-patterns that new developers discover the hard way.

What You Can Do Today

Kognyt MCP is an MCP server that gives AI assistants this Salesforce context. It works with Claude Code, Cursor, VS Code Copilot, and other MCP-compatible clients.

Install it in one command:

npx -y @kognyt/salesforce-mcp

No sign-up. No API key. No configuration. Your AI assistant immediately gains access to Salesforce platform knowledge — governor limits, documentation, release intelligence, and more.

The free tier includes 3 tools with 100 requests per day. Pro unlocks all 10 tools including tribal knowledge, SOQL optimization, code pattern analysis, and the full Apex class library reference.

Where To Go Next

Kognyt MCP gives your AI platform knowledge — what Salesforce is and how it works. But it doesn't know about your specific org.

Kognyt for VS Code is the live next step: it connects to your Salesforce org and gives your AI Org Context for your schema, your code, your profiles, and your permissions.

If you want the desktop workspace, join the Kognyt IDE waitlist. If you want connected-org work today, explore Kognyt for VS Code.