A Story of Human-AI Collaboration
January 2026
When agents improvise instead of following instructions
A user was writing a recipe to automate code reviews...
"Your recipe has errors on lines 4 and 7. Here's how to fix them..."
Report the problem, let user fix it
"I'll fetch the PR details for you and analyze the code..."
Agent read the recipe and executed the steps itself
The agent tried to be helpful by doing what the recipe described, instead of running the recipe through the proper system.
The CLI tool existed, but users wanted a human way to say:
"Run this recipe, but that's all - don't do it yourself"
Amplifier suggests the "mode" approach
All tools are blocked unless explicitly allowed. No file edits, no bash, no web access.
The recipes tool is marked as safe - the agent can execute, resume, and manage recipes.
Sharing the solution with the team
Team saw immediate value in restricted execution modes
"Can I share this mode with others?"
Amplifier as architectural advisor - not just executing commands, but providing guidance on system design and organization.
A bug lurks in the mode system
Mode system couldn't discover modes from other bundles
The recipes tool was being blocked despite being marked safe
The hooks-mode code expected tools to be nested under tool_policies,
but the mode file had it at the top level.
During a meeting, with minimal attention
The user described the bug briefly and let Amplifier work autonomously:
Complex debugging and fix
with minimal human attention
Safe testing for dangerous changes
The fix involved changes to core mode/hook code - the very system that controls tool access. Testing this in production was risky.
Changes tested in an isolated container, separate from the main environment
Confirmed the fix worked before committing to the real codebase
Caught potential issues that could break other modes
Amplifier as architectural advisor, not just code executor
Complex debugging with just a few user prompts
Modes can be shared in bundles - community benefit
Shadow environments for testing changes to core systems
This wasn't a planned feature. It emerged from a real user frustration, evolved through collaboration, and improved the system for everyone.
From frustration to shared solution in a single conversation,
with autonomous bug fixing during a meeting.
Data as of: February 20, 2026
Feature status: Active
Research performed:
Gaps: Exact commit dates, PR numbers, and line counts not available from local research. Story is based on qualitative user experience narrative.
Primary contributors: samschillace (mode design and bug fixing)
Available in the recipes bundle