If you look at Twitter/X right now, you see the same demo over and over again. Someone types a prompt into a chat box, and poof—a clone of Flappy Bird appears. Or a landing page. Or a To-Do app.
They call it "Vibe Coding." It feels like magic.
But if you are a Product Manager or an Engineer working on a real product—one with users, legacy code, and a design system—you know the truth.
Vibe coding doesn't work for production.
The moment you try to take that AI-generated code and paste it into your actual repository, the magic dies. The styling doesn't match your theme. It imports libraries you don't use. It hallucinates variables that don't exist.
The Fragmented Era of AI
We are currently stuck in the "Fragmented Era" of AI. You have an AI for your docs, an AI for your design, and an AI for your code—but none of them talk to each other, and crucially, none of them know your codebase.
"The Fragmented Stack vs. The Integrated Engine. When tools don't talk to each other, humans become the copy-paste bridge."
The "Context" Counter-Argument
Now, a developer reading this might say: "Wait, my IDE (VS Code, Cursor, Windsurf) already reads my code."
And you are right. Those are incredible power tools for engineers who already know the architecture. They are fantastic at autocomplete and answering technical questions.
But Product Development is a team sport.
The problem isn't just "can the tool read the code?" The problem is "who can use the tool?"
Right now, if a Product Manager or Designer wants to iterate on a feature, they are locked out. They have to write a spec ticket, hand it off, and wait. Or they try to "vibe code" in a separate window, generating a generic prototype that the developer has to rebuild from scratch anyway.
We built Codiris Import to bridge this gap
We wanted to give the context of the codebase to the people defining the product, not just the people maintaining it.
The Cost of Context Switching
The modern product team is expected to move at breakneck speed. But our tools are slowing us down.
We are forced to be the "Context Bridge."
You copy a snippet from VS Code, paste it into ChatGPT, explain the context, get a result, paste it back, realize it broke the layout, and repeat.
This isn't just annoying; it is expensive.
Research from the University of California, Irvine famously tracked the cost of these interruptions. They found that once a developer or PM is pulled out of their flow (context switched), it takes an average of 23 minutes and 15 seconds to get back to deep focus.
If you are "Vibe Coding" by jumping between three different AI tools to build one feature, you aren't accelerating. You are fragmenting your focus.
Real leverage doesn't come from an AI that can write code. It comes from an AI that can read your code.
The "Import" Philosophy
We need to stop treating AI like a slot machine where we pull the lever and hope for a jackpot. We need to treat it like a new team member.
When you hire a new developer, you don't ask them to write a feature on Day 1 without looking at the codebase. You tell them: "Clone the repo. Read the documentation. See how we handle state management. Look at our component library."
Context is King.
If an AI doesn't know your specific constraints—your linting rules, your file structure, your CSS framework—it is producing "slop." It might work in isolation, but it is technical debt the moment it hits your branch.
Let me show you how this works in practice
It is easy to nod along to these concepts in the abstract. But let's look at what actually happens when we try to push a feature into a living, breathing codebase.
My co-worker was developing ConnectIn, an app designed to help users find the right professional connections. The codebase already existed. It had a specific directory structure, a chosen styling library, and established patterns.
We needed to add a new feature, not because we thought it was cool, but because User Research told us we had a problem.
Users were finding the right people, but they weren't reaching out. They told us:
- "I don't know what to say."
- "I'm intimidated by their title."
- "I'm scared of being ignored."
The friction wasn't search; it was social anxiety.
We decided to build an AI-powered "Icebreaker" button—one click to analyze the profile and generate a personalized, low-pressure intro message.
The 5-Step Process
Step 1: Sync the Reality (Importing the Repo)
I didn't start with a prompt. I started by connecting Codiris to our GitHub repository. Codiris didn't just read the text files; it analyzed the structure and dependencies. It understood: "Oh, they are using TypeScript. They use Tailwind for styling. Here is where the reusable UI components live."
Step 2: The "Junior Dev" Prompt
Because Codiris now understood the context, I didn't need to write a ten-paragraph prompt explaining our tech stack. I simply wrote: "Add a button that generates an icebreaker message. Use the properties profile.bio and profile.title to generate a relevant opening line."
Step 3: Architecture, then Code
Codiris didn't just spit out code. It thought through the implementation first (Plan Mode). It identified what it needed to do, where to add the button, and how to match existing styles. It wasn't guessing; it was planning a surgical insertion into the existing logic.
Step 4: The Build
When I looked at the preview, the new "Icebreaker" button didn't look like a generic HTML element. It looked exactly like ConnectIn. It used the correct border radius, the correct brand colors, and the correct Tailwind utility classes. It reused the code we had already written months ago.
Step 5: The PR, Not the Paste
Finally, I didn't have to copy-paste snippets into VS Code. Because Codiris is synced with the repo, I simply clicked "Create Pull Request." Codiris pushed a clean branch to GitHub. The diff was readable. The imports were correct. It was ready for review.
The Shift from Creation to Curation
This is the future of product development.
We don't need tools that help us generate more code from scratch. We have enough code. We need tools that help us evolve and maintain the complex systems we have already built.
Codiris Import allows Product Managers and Designers to make meaningful contributions to the codebase without breaking the build. It allows Developers to offload the boilerplate tasks to an AI that actually knows where the bathroom is.
Stop pasting context. Start importing it.
Import your Repo Today
Stop vibe coding. Start building with the context your AI actually needs.
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— Bruno, Humiris AI