You’ve been wasting hours fixing what AI should’ve built right the first time.
Your code breaks halfway through.
Your automations forget the plan.
And your so-called “smart” agents lose context every twenty minutes.
That ends today with Gemini Conductor and GLM 4.7 AI.
Watch the video below:
👉 https://www.skool.com/ai-profit-lab-7462/about
The Real Problem Most Builders Face
Let’s be honest.
AI is incredible at writing text. It’s decent at writing code. But it’s terrible at staying consistent over time.
You ask it to build a backend flow.
Then a frontend.
Then a user login system.
And by the time you get to the third step, it’s forgotten what framework you were even using.
That’s the real bottleneck.
You’re not losing time because AI is slow.
You’re losing time because AI forgets.
Gemini Conductor and GLM 4.7 AI were built to fix that — not with more prompts or fancy GUIs, but with better thinking.
Meet GLM 4.7 AI — The Brain Behind It All
Zhipu AI (ZAI) dropped GLM 4.7 AI on December 22nd.
And it quietly outperformed models that cost seven times more.
GLM stands for General Language Model, but this isn’t just another text generator.
It’s an execution model — built specifically for agent workflows and multi-step reasoning.
Here’s what makes it a big deal:
- Interleaved thinking — It pauses mid-response to check logic before writing the next line.
- Preserved thinking — It remembers reasoning blocks across your entire conversation.
- Tunable thinking — You can adjust how “deep” it thinks for each task, balancing speed and accuracy.
That combination makes it feel like you’re coding alongside a senior engineer who never gets tired.
GLM 4.7 AI: Numbers That Actually Mean Something
You’ll hear people throw around benchmark scores all day.
But here’s why these numbers matter for real developers:
- SWBench Verified: 73.8% — a 5.8% jump from version 4.6.
- CodeBench V6: 84.9% — higher than Claude Sonnet 4.5.
- TerminalBench 2.0: 41% — that’s a 16.5% boost over its predecessor.
This isn’t marketing. These are verified tests across hundreds of coding tasks.
In practical terms?
It writes cleaner functions. It fixes its own syntax. It maintains variable naming consistency.
You spend less time debugging and more time building.
Vibe Coding: When AI Starts to Care About Design
Here’s where GLM 4.7 AI really surprises people.
It doesn’t just work — it looks good.
The new “Vibe Coding” feature focuses on UI quality. That means it can generate visually consistent, professional layouts with:
- Clean typography
- Modern color harmony
- Better component styling
- Usable layouts right out of the box
If you’ve ever had to fix ugly AI-generated web pages, you’ll appreciate this instantly.
The model now hits 91% presentation compatibility, up from 52%.
Translation: You can generate slides or interfaces that are basically ready to use.
It’s a small change with a massive impact on time saved.
GLM 4.7 AI Integrates with Everything You Already Use
Another reason developers are moving to GLM 4.7 AI fast?
It’s plug-and-play.
You can integrate it into:
- Claude Code
- Cursor
- RooCode
- KiloCode
- Cline
Setup takes about five minutes.
You just drop in your ZAI API key, point it to their endpoint, and you’re done.
Because it’s Anthropic-compatible, Claude Code actually thinks it’s talking to Claude — but it’s running GLM 4.7 behind the scenes.
That means better output without breaking your workflow.
And here’s the kicker: it costs one-seventh the price of Claude, with three times the usage quota.
If you run coding sessions all day, that’s a huge win.
Same performance. Lower cost. More output.
Now Let’s Talk About Gemini Conductor — The Memory That AI Never Had
You know that feeling when your AI loses context and you just give up?
You’re twenty prompts in.
You’ve explained your architecture five times.
And it’s still writing code that contradicts itself.
That’s where Gemini Conductor steps in.
Google released this as an extension for Gemini CLI, and it’s a total shift in how we work.
Instead of relying on chat history, Conductor creates permanent context files — your living documentation.
Every project becomes a set of markdown files in your repository:
- product.md — what you’re building
- stack.md — your tech stack and tools
- workflow.md — the process and rules your AI follows
These aren’t just notes. They’re your single source of truth.
How Gemini Conductor Keeps You in Sync
Here’s what makes this approach brilliant.
Everything Gemini Conductor does gets tracked in Git.
That means your context isn’t ephemeral — it’s versioned.
You can literally pause your AI mid-project, come back a week later, and pick up where you left off.
It’s like saving your brain state between sessions.
When you run commands like:
gemini conductor.new gemini conductor.implement
It helps you spec out tasks, plan the build, and then execute step-by-step — all while updating your repo automatically.
No more “what were we doing again?” moments.
You know exactly where things left off.
When You Combine GLM 4.7 AI and Gemini Conductor
This is where the magic happens.
Think of Conductor as your planner and GLM as your executor.
You use Conductor to build your roadmap — requirements, specs, architecture.
Then GLM 4.7 follows that roadmap with perfect reasoning and no memory loss.
Let’s say you’re adding user authentication.
- Conductor helps define the OAuth flow, session management, and password reset logic.
- You approve the markdown spec.
- GLM 4.7 picks it up, writes the code, tests it, and tracks its reasoning.
You get code that follows a plan — not random lines generated from half-remembered context.
Real-World Results with Gemini Conductor and GLM 4.7 AI
Early developers using this combo have already seen massive efficiency gains.
One dev integrated authentication into a full-stack app using a stack they barely knew — and still shipped in record time.
Why?
Because the planning phase forced the AI to stop, think, and spec before building.
That meant fewer re-writes, fewer errors, and full documentation.
Every decision was traceable. Every test had context.
The workflow didn’t just make the AI better — it made the developer better.
The Real Advantage: Context as an Asset
For years, context has been a limitation.
Now, it’s leverage.
GLM 4.7 AI handles the reasoning.
Gemini Conductor preserves the memory.
Together, they give you a system that actually learns from your own work.
You can scale complex builds, automate processes, or hand off projects without losing critical knowledge.
Imagine onboarding new team members. They don’t have to guess what the AI did.
They just read the markdown files.
That’s professional-grade automation — not hobby-grade prompting.
How to Get Started
You can set this up in under 20 minutes.
- Install Gemini CLI and the Conductor extension.
- Clone your repo and run
conductor.setup. - Add your ZAI API key for GLM 4.7.
- Connect your agent (Claude Code, Cursor, or RooCode).
- Start a new project using
conductor.new.
That’s it.
From that point forward, every project has structured documentation, preserved reasoning, and traceable progress.
You’ll never lose context again.
Running GLM 4.7 AI Locally
Here’s something most people don’t know — GLM 4.7 AI can run locally.
ZAI released the weights publicly on Hugging Face and ModelScope.
You can deploy it using VLLM or SGLAN on your own hardware.
That means:
- No API costs
- No rate limits
- Complete data privacy
You control everything.
And when combined with Conductor, your AI workflow becomes fully local, auditable, and private.
These Tools Won’t Fix Bad Requirements — They’ll Expose Them
Here’s the truth: AI can’t fix unclear thinking.
If your project is vague, your output will be too.
But Gemini Conductor and GLM 4.7 AI force clarity.
Conductor catches problems early — when they’re cheap to fix.
GLM executes precisely — when it’s time to build.
The result?
Fewer late-stage bugs.
Cleaner architecture.
Faster launches.
Instead of re-writing broken code, you iterate on structured plans.
That’s how professionals build.
The Community That Makes It Click
When I started using these tools, I was overwhelmed.
So I joined a group called AI Profit Boardroom — 1,800 builders all sharing workflows and what actually works.
No hype. No spam. Just real practitioners comparing results.
That community taught me which AI automations are worth the effort and which ones waste time.
If you want to shortcut the learning curve, join communities like that. You’ll see how others use Gemini Conductor and GLM 4.7 AI in production, not just demos.
Going Deeper: AI Success Lab
If you want the full system, SOPs, and over 100 real AI use cases, check out the AI Success Lab.
It’s where 38,000+ people are learning to build real workflows, not just play with prompts.
You’ll get:
- Practical AI automation templates
- Project documentation systems
- Weekly updates on new tools like GLM and Gemini
Join for free here → https://aisuccesslabjuliangoldie.com/
Why This Moment Matters
We’re entering a new era of AI development — one where planning and execution merge.
Most tools handle only one side:
ChatGPT gives you text.
Claude gives you reasoning.
Gemini gives you access.
But Gemini Conductor and GLM 4.7 AI give you something else entirely:
A workflow that thinks, plans, and remembers.
You’re no longer coding in isolation.
You’re orchestrating intelligence.
FAQs
Q: Is GLM 4.7 AI better than Claude for coding?
Yes. It matches Claude Sonnet 4.5 in performance benchmarks but costs a fraction of the price.
Q: Can I use Gemini Conductor without Gemini Advanced?
Yes. It works through the Gemini CLI in preview mode.
Q: Do I need coding experience to use these tools?
Basic knowledge helps, but the setup is simple enough for non-coders building automation workflows.
Q: Can GLM 4.7 handle front-end design?
Absolutely. That’s what Vibe Coding was built for — producing real, visually consistent UI components.
Q: Is my data safe?
Yes. GLM 4.7 can run locally for total privacy, and Gemini Conductor stores only markdown documentation in your repo.
Final Thoughts
Gemini Conductor and GLM 4.7 AI aren’t just upgrades.
They’re a framework for how intelligent systems should work.
One plans, one executes, both remember.
You can use them separately — but together, they redefine what “smart” actually means in coding and automation.
Start with one.
If you’re building code — go with GLM 4.7.
If you’re managing workflows — start with Conductor.
Then combine them.
Because the real power isn’t in what these tools do.
It’s in what you can build when your tools finally remember what you told them.
Use Gemini Conductor and GLM 4.7 AI today.
Plan smarter. Build faster. Ship without breaking.
That’s the new standard for AI development.
