Welcome, humans.

🔴 HAPPENING NOW: Neuron Live — Physical AI for Humanoid Robots

We’re going LIVE RIGHT NOW to talk all things physical AI and robotics with Nikita Rudin of Flexion Robotics!

Humanoid robotics challenges go beyond movement and servo motors; there are massive AI challenges behind getting intelligence into the physical world, where gravity is real, friction matters, and mistakes break hardware.

This week on Neuron Live, we're joined by Nikita Rudin, Cofounder & CEO of Flexion Robotics, to unpack what it actually takes to build intelligence for humanoid systems. From training control policies and perception models to bridging simulation and the real world, we'll explore the AI stack powering the next generation of embodied systems.

If large language models are the brain in the cloud, what does intelligence look like when it has to walk, grasp, and not fall over?

Oh, and best of all? We’ll be getting a LIVE DEMO on a REAL ROBOT… you won’t want to miss this one!

Click to watch live based on your preferred channel below:

• YouTube

• LinkedIn

• X (Twitter)

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IN CASE YOU MISSED IT…

He built GitHub Copilot at Microsoft. Then he left for Google, built an AI coding tool in his terminal, and his team now ships 100 to 150 features and bug fixes every single week—using AI to build itself.

In his first-ever in-depth interview about Gemini CLI, Google Principal Engineer Taylor Mullen came on the pod and revealed how he manages swarms of parallel AI agents, why the humble command-line terminal is having a full-on renaissance, and the viral “Ralph Wiggum” technique that recently made waves among devs on X and Reddit.

Here's our favorite parts:

• (2:14) The origin story: Taylor built Gemini CLI at a hackathon two years ago—but scrapped it because AI was too slow and expensive. Fast forward to today and it's the most popular open-source CLI on GitHub.

• (8:21) The "holy crap" moment: Taylor told Gemini CLI to clear his packed schedule, DM everyone affected, and reschedule—all while he was at the gym. Done in five minutes.

• (17:24) Live bug-fixing demo: Taylor pastes a real GitHub issue URL into his terminal without even reading the bug first—and watches the AI solve it in real-time.

• (18:47) Spawning CLIs that spawn CLIs: His team runs 7-10 parallel AI agents simultaneously—each one working on a different task, notifying the human only when it needs approval.

• (23:05) Conductor — "Planning dialed to 11": Google's new extension doesn't just plan your project. It asks clarifying questions, writes implementation specs, self-improves over time, and helps your whole team get smarter.

• (45:01) "10x is the new normal": Taylor's team has moved past the 10x engineer debate entirely. Everyone is 10x now. The question is how you get to 100x—and the answer is parallelism.

• (45:56) The Ralph Wiggum Technique: The viral prompting method sweeping developer Twitter. Feed the AI's output back into the same prompt, over and over, until the answer is polished. Taylor runs it 5 times. Every time.

• (31:54) Why it's open source: "With a tool this powerful, how else do you trust it?" Over a million users are helping build and audit Gemini CLI in the open—every single day.

Why watch this? Because Taylor's live demos at (17:24) and (23:05) will show you exactly how to use a “CLI” / command line interface terminal agent actually works, which will help demystify it for you whether you want to try Gemini CLI, Claude Code, Codex, or any other tools.

Watch and/or Listen now: YouTube | Spotify | Apple Podcasts

P.S. Taylor's team prefers Gemini 3 Flash over Pro for almost everything—and he's only fallen back to Pro 10 times in the last month. Find out why at (43:44).

Keep scrolling for what's new with Gemini CLI, details on our upcoming live stream with the CEO of a humanoid robotics company tomorrow, and some other recent episodes you’ll love.

ALso: Timed with our interview, Google just launched Conductor's Automated Reviews—a major new feature for Gemini CLI that automatically audits AI-generated code for security risks, style compliance, and accuracy against your original plans.

Why it matters: The biggest concern with AI-written code isn't speed—it's trust. This update makes Gemini CLI the first major terminal tool to close the loop: the agent writes code, tests it, and peer-reviews its own work—all before a human ever sees it.

What Automated Reviews actually check:

• Code quality: Flags race conditions, null pointer risks, and logic errors—not just syntax.

• Plan compliance: Verifies every phase of your roadmap was addressed. No skipped requirements.

• Security scanning: Catches hardcoded API keys, potential data leaks, and injection vulnerabilities.

• Test-suite validation: Runs your full test suite and folds coverage data into the review report.

• Style enforcement: Ensures all new code follows your project's guidelines automatically.

Every finding is categorized by severity (High / Medium / Low) with exact file paths—so you know exactly where to look and can start a fix track inside Conductor immediately.

Also new: Agent Skills—a modular skills library that extends Gemini CLI with task-specific expertise (security auditing, cloud deployments, codebase migrations, etc.) without cluttering the model's primary context window. 

Based on the Agent Skills open standard, think of it like plug-and-play superpowers. Gemini autonomously decides when to use a skill based on your request and pulls it in on demand.

Oh, and the whole thing (Gemini CLI) is free and open source. Just thought we should mention that somewhere.

P.S: If you’re just getting into coding with AI, Taylor mentioned Test-Driven Development as a technique you can use to code with agents; there’s actually a popular plugin called “Superpowers” you can install to help you with this.

We wrote more about it on the website here.

🔑 The bottom line: The race isn't about who can write code the fastest. It's about who can write code you don't have to fix. Gemini CLI is betting hard on "trust, but verify."

Try it free: geminicli.com | GitHub (open source) | Extensions blog | Launch announcement

One more before you go:

Last week, we spent 3 hours building AI agents live on camera. Microsoft's Bryan Goode demoed a tenant running 128,000 agents. Corey's OpenClaw agent literally haunted his house (his wife texted mid-stream in a panic because a voice was lecturing about tokenization from the living room). We built a landlord-tenant law scout in Claude Co-work in five minutes. GPT 5.3 Codex Spark dropped mid-stream. And yes, we made Cat Doom (our personal AI coding benchmark) with the Codex app…

The full breakdown—every tool, every timestamp, every tutorial—is in our deep-dive article. Or just watch the whole stream.

Last thing: if you haven’t subscribed yet, please do! All you have to do is click the image below, confirm, and you’ll be subscribed to the channel 😄 

We have a goal to hit 50K subscribers by the end of the year (if not 100K), and we’re only 35K away! If you like learning about AI, and already watch some of our videos, do us a favor and click here to subscribe today.

Stay curious,

The Neuron Team

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