If you have spent any time watching AI coding agents work, you know the pattern: the agent writes code at blistering speed, you glance at it, and you silently hope nothing blows up in production. Google just released a feature that tackles that exact anxiety head-on.
On February 13, the Conductor extension for Gemini CLI received a major update: Automated Reviews. Instead of trusting that your AI-generated code is correct, Conductor now runs a structured validation step that checks quality, security, plan compliance, and test results before anything gets merged. For teams leaning into AI-assisted development, this is the governance layer that has been conspicuously missing.
What Is Conductor?
Conductor launched in December 2025 as a Gemini CLI extension designed to bring persistent context to AI-driven development. The core idea is simple but powerful: instead of feeding project details into ephemeral chat sessions that forget everything the moment you close the terminal, Conductor stores your project plans, specifications, and guidelines in version-controlled markdown files.
Think of it as giving your AI coding agent a project brief it can reference at any time. Your plan.md describes what needs to be built. Your spec.md defines the requirements. Your guideline files set coding standards. The AI reads these files, builds to spec, and now -- with Automated Reviews -- validates its own work against your documented expectations.
How Automated Reviews Work
After your coding agent finishes a task, you trigger a review with a single command:
conductor review --report review.md
Conductor then generates a comprehensive post-implementation report covering five key areas:
Deep code review. This goes well beyond linting. Conductor performs static and logic analysis, flagging race conditions in async code, null pointer risks, and logic errors that could cause runtime exceptions. It catches the kinds of bugs that often slip through quick human reviews.
Plan compliance checks. The system cross-references newly generated code against your plan.md and spec.md to verify that every requirement was addressed. If the agent skipped a feature or deviated from the roadmap, the review flags it.
Guideline enforcement. Your coding standards and custom governance rules get validated automatically. Style inconsistencies, naming convention violations, and architectural drift all surface in the report.
Test-suite validation. Rather than trusting that tests pass in some vague future CI run, Conductor integrates your entire test suite into the review workflow. It runs unit and integration tests, then rolls coverage data into the final report.
Security scanning. Every review includes a security pass that catches hardcoded API keys, potential PII leaks, and unsafe input handling that could expose your application to injection attacks.
Findings are prioritized by severity -- High, Medium, and Low -- so you know exactly where to focus. You can then start a new Conductor track to address the issues, keeping the fix-and-verify cycle tight.
Why This Matters Right Now
The timing of this release is not accidental. We are in the middle of an agentic AI explosion where autonomous coding tools are reshaping how software gets built. Claude Code, Cursor, GitHub Copilot Workspace, and Gemini CLI itself have all pushed the envelope on what AI can produce without human intervention.
But speed without safety is a liability. The industry has a name for the fast-and-loose approach to AI-assisted development: "vibe coding." You describe what you want, the agent builds it, and you ship it based on a gut feeling that it works. For prototypes and side projects, vibe coding is great. For anything touching customer data, financial transactions, or production infrastructure, it is a risk your business cannot afford.
Conductor's Automated Reviews represent a shift from AI-generated code to AI-governed engineering. The agent still does the heavy lifting, but now there is a structured checkpoint ensuring the output meets your standards before it reaches your users.
What This Means for Small and Mid-Size Businesses
If you are a smaller team that has been cautious about adopting AI coding tools, this is exactly the kind of development that should change your calculus. The main objection we hear from SMBs considering AI-assisted development is not about capability -- it is about trust. Can you trust AI-generated code in production?
With automated validation built into the workflow, the answer is getting closer to yes. Here is what changes practically:
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Smaller teams get enterprise-grade reviews. A two-person dev shop using Conductor gets the same depth of code review that a large engineering org gets from senior staff engineers and dedicated security teams.
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Compliance becomes continuous. If your industry requires audit trails or adherence to specific coding standards, Conductor generates documentation of compliance automatically with each review cycle.
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Junior developers level up faster. When an AI agent writes code and an automated review explains exactly what is wrong with it, that is a learning loop that accelerates skill development.
How It Fits Into the Bigger Picture
Google is not the only player investing in AI code quality. OpenAI recently introduced elevated risk labels and lockdown mode for agentic workflows. The broader trend is clear: the industry is moving past the "generate everything fast" phase and into the "generate everything fast and verify it automatically" phase.
For businesses evaluating their AI development strategy, the takeaway is straightforward: look for tools that include validation and governance in the workflow, not as an afterthought. The agentic AI shift is accelerating, and the winners will be teams that combine autonomous speed with automated oversight.
Getting Started
Conductor is open source and installs with a single command:
gemini extensions install https://github.com/gemini-cli-extensions/conductor
If you are already using Gemini CLI, adding Conductor to your workflow takes minutes. If you are evaluating AI-assisted development tools for the first time, Conductor paired with Gemini CLI gives you a complete plan-build-verify pipeline with no proprietary lock-in.
The age of unsupervised AI code generation was always going to be temporary. Google just fired the starting gun on what comes next: verified, governed, production-ready AI engineering.
Need help integrating AI-assisted development tools into your workflow? BaristaLabs specializes in helping businesses adopt AI practically and safely. Get in touch to talk about what makes sense for your team.