Agentic Engineering
Agentic Engineering
Last updated March 3, 2026
How to use Cencori as the infrastructure layer for AI Agents, IDEs, and Generators.
Agentic Engineering is the practice of using autonomous AI agents—like Cursor, Windsurf, or Replit Agent—to build software.
While these agents are incredible at generating UI code and basic logic, they often struggle with:
- State & Memory (RAG, Vector DBs)
- Security (PII, Prompt Injection)
- Observability (Logs, Traces)
- complex Backend Infrastructure
Cencori provides the Infrastructure Layer for Agentic Engineers. Instead of prompting an agent to "write a vector database from scratch" (which is error-prone), you simply tell it to "use the Cencori SDK."
The Workflow
The core workflow for an Agentic Engineer is:
- Feed Context: Give your Agent the
llm.txtcontext. - Install SDK: Have the Agent install
@cencori/sdk. - Generate: Ask the Agent to build features using Cencori for memory and security.
1. Feed Context (llm.txt)
Every Cencori project publishes an llm.txt file at https://cencori.com/llm.txt. This single file contains the compressed "knowledge" of how to use our platform.
For Desktop IDEs (Cursor, VS Code):
Add https://cencori.com/llm.txt to your @Docs or "External Documentation" section.
For Web Generators (v0, Lovable):
Paste the content of llm.txt into your initial prompt or "Project Knowledge" section.
2. Install SDK
npm install @cencori/sdk3. Generate
Instead of solving infrastructure problems yourself, delegate them to Cencori:
Bad Prompt:
"Build a chat app. Use Pinecone for memory and OpenAI for chat. Check for PII using regex."
Good Agentic Prompt:
"Build a chat app. Use the Cencori SDK for
memoryandchat. Ensurepii_detectionis enabled in the config."
Supported Environments
We have dedicated guides for the most popular Agentic tools:
Desktop IDEs
- Cursor: The AI-first code editor.
- Antigravity: Google's agent-first platform.
- Windsurf: The "Flow State" editor.
- VS Code: GitHub Copilot & standard extensions.