MCP & CONNECTED WORKFLOWS
Your bug report is in one tool. The fix is in another.
Connect issue context and project tools through MCP. Follow a LoopCode workflow with scoped access, source checks, test evidence, and a reviewed handoff.
THE LOOPCODE JOURNAL
AI coding, with the details.
Practical notes on working with AI coding agents. Written by Heksync, the maker of LoopCode, with runnable examples, explicit boundaries, and checks you can reproduce.
By Heksync product team · Updated
FROM THE LOOPCODE JOURNAL
Start with a practical workflow.
Working examples, clearer boundaries, and checks you can reproduce.
CODE INTELLIGENCE & REFACTORING
Six matching words. Only two belong in this rename.
See why symbol-aware refactoring differs from text replacement. Use LoopCode's language-server tools, inspect external contracts, and verify the final change.
BROWSER AGENTS & PRODUCT VERIFICATION
The screen says ‘Saved.’ Did anything actually save?
A screenshot is not proof that data was saved. Use LoopCode's browser workflow to check requests, persisted state, failure behavior, and a reproducible handoff.
ENGINEERING WORKFLOWS
From a feature ticket to code you can review.
Use an AI coding agent on an existing backend project: scope a feature, test input boundaries, inspect the patch, and review evidence before shipping.
DATA & DEVELOPER CONTROL
A local AI coding agent can still send code to a hosted model.
Understand local execution versus hosted inference, which code enters model context, and how to check file rules, shell access, and MCP permissions.
TERMINAL & AUTOMATION
Let an AI agent explain a failing build. Keep the build red.
Add bounded AI failure triage to CI without hiding failed tests. Use a read-only LoopCode run, preserve exit codes, and protect tokens and test logs.
From Heksync, the maker of LoopCode. These are first-party engineering articles, not independent product rankings. The examples are illustrations; the articles explain which checks we ran and which remain project-specific.