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AI Coding

Analysis | Diagrams | Innovators

What is the best architecture for AI Coding and Agent Development?

Clarity of intents and purpose is now the most important capability for driving valuable outcomes. Code is only as good as it remains, understandable, maintainable and free of technical debt.

Subject Expertise

IDE Toolkit

What are the best tools and practices for evolving solutions with a clean architecture?

IDENotes
VS CodeLegacy
AiderMost innovative? Python
Bolt NewWeb Green Fields
ClineVS Plugin
Convex ChefIntegrated Backend
CopilotOutpaced
CursorAll Purpose
DevinEnterprise
FirebaseGoogle
ReplitWeb Green Fields
v0Vercel, UI/UX Design
qodoEnterprise
windsurfFork of VS Code, Codium
coderabbit.aiDev Ops

MCP Servers

context7

See MCP Server configuration.

Benchmarks

SWE Benchmark is a tool for evaluating the performance of AI coding agents.

See best practices for using coding agents

Use Cases

Use JTBD Analysis to build software to expand potential to deepen insights to build closer connections.

tip

Software is a Commodity, Culture is your only Competitive Advantage

  • Save money on software with features you don't use or need
  • Maximize Advantage of Trade Secrets and IP
  • Take control of your data footprint
  • Optimize integration and data flows
  • Control your own destiny

Prototyping Ideas

  • Quickly building proof-of-concept applications
  • Iterating on designs through conversation with AI

Automating Tasks

  • Writing exploratory code to try out structures
  • Simplifying and trimming down large codebases
  • Automating monotonous tasks and one-off scripts
  • Converting programs to more efficient languages for performance improvements
  • Building entire web applications with unfamiliar technologies

Code Optimization and Refactoring

  • Identifying opportunities to improve code efficiency
  • Suggesting refactoring to simplify complex codebases

Documentation and Logic Explanations

  • Generating code documentation
  • Explaining complex code or algorithms

Context