Journey Through Code Generation Tools: Exploring Replit’s Agents

As a curious product designer, I love exploring new technologies, especially when they promise to change how we build products. But my journey isn’t just about finding the perfect tool to solve a problem — it’s more about learning along the way, trying out different design patterns, and discovering which workflows help deliver the highest quality code with the least friction.

AI-powered code generation tools promise to automate tedious tasks, catch bugs before they happen, and even write entire sections of code based on natural language input. It’s an exciting space, but with so many tools to choose from, it’s hard to know where to start. My journey led me to Replit’s AI Agents, one of the more popular options out there but also one that has some quirks. Let’s review it together.

The Design Adventure Begins: Why Replit?

I approached Replit with excitement because the promise is huge: a seamless IDE experience where AI helps you debug, write code, and speed up your workflow. On paper, it sounds like a developer’s dream, but dreams don’t always translate perfectly into reality.

Replit’s AI agents tool is positioned within a competitive market of AI coding assistants. While it shows promise in enhancing developer productivity and has garnered community interest, its long-term success will hinge on addressing user concerns and demonstrating clear value over time.

Success Metrics

• Adoption and Usage: Replit’s AI tools are gaining traction among developers, similar to GitHub Copilot, which has reportedly made over a million developers 26–55% faster in their coding tasks, depending on the source (sources: DX@linkedin, chatGPTPro@reddit, SaaS@reddit). While specific user numbers for Replit’s AI agents aren’t disclosed, the growing popularity of AI coding tools suggests a positive trend.
• Marketplace Ratings: While specific ratings for Replit’s AI agents weren’t available, user feedback on platforms like Reddit indicates a mix of enthusiasm and skepticism about AI tools in general. Many users appreciate the productivity gains but express concerns about limitations and real-world applicability (source: Salesforce@reddit).
• Revenue Metrics: Similar to GitHub Copilot, which generates $100 million in annual recurring revenue, Replit’s financial performance remains largely undisclosed. However, and the overall market for AI coding assistants is projected to grow as more developers adopt these tools (Source: chatGPTPro@reddit).
• User Feedback: Discussions among developers reveal that while many find AI tools beneficial for speeding up coding tasks, there are concerns about their effectiveness in complex scenarios. This could impact long-term adoption rates if users feel the tools do not meet their expectations (Sources: LocalLama@reddit, ).

🤩 What’s Great

An Extraordinary IDE UX

Replit’s IDE stands out right from the start. The layout is intuitive, with the Explorer always on the left and Chat on the right. This setup allows you to see your project files and communicate with the AI at the same time. No constant tab switching, no context loss. It’s simple, and simplicity often breeds efficiency.

Key UX Patterns that Shine:

• Minimal Chat Dependency: Unlike other tools that make you rely on chat responses for code snippets and instructions, Replit AI keeps the chat strictly for communication, not execution. This cuts down on reading long responses or copying and pasting code manually.
• Integrated Diff Views: The chat isn’t just for talking — it also functions as a to-do list. You can click on file lists directly from chat, view diffs, and even roll back changes easily, all within the chat window. This feels like a fusion of communication and version control in one.
• Auto-Managed Agent State: Rolling back code feels natural. It’s almost like using git reset without the overhead of managing branches or commands. The agents handle state management on their own, making it easy to experiment without fear of breaking something permanently.

🫥 Where Replit Falls Short

Control Issues

While Replit’s user interface is slick, the behavior of the AI Agents can be a bit unpredictable. For example, the agents are given too much autonomy at times, which can lead to unintended consequences.

Key Friction Points:

• Over-Control by Agents: Once agents kick off their tasks, they’ll start making changes to multiple files across iterations. This isn’t always helpful in complex projects where more granular control is necessary. It’s great for small side projects, but if you’re working on something complex and multi-layered, the lack of oversight can quickly become a headache.
• Rigid Paths to Completion: The agents are too fixated on completing tasks based on the initial spec, even if it leads to persistent errors. While this may be desirable in some workflows, there are times when the agent doesn’t know when to stop. You’re left trying to convince it that the job isn’t quite finished yet.

😶‍🌫️ What’s Missing

Flexibility with External Dependencies

One of the bigger limitations is that Replit’s agents can’t reason about outside project dependencies. For instance, they can’t debug non-responsive endpoints or validate external service states. This means you’ll need a solid grasp of your project’s architecture and be ready to intervene when things go beyond Replit’s scope or when the agent is lost.

My UX Wishlist for Replit Agents

1. More Control Over Iterations: Developers should be able to control exactly which files agents can edit or limit their scope to avoid unwanted changes across multiple files.
2. Dependency Awareness: It would be a game changer if Replit agents could interact with external services and diagnose their state, ie. make an API call to validate the state of endpoints and mock the contract data.
3. Less Mouse, More Keyboard: Right now, the workflow is still very mouse-dependent, with too many clicks interrupting the coding flow. This is especially true when agents are running — you can’t edit files while they’re working, which breaks the flow.

Reviewing Replit

A Scorecard for AI Code Generation Tools

Now, let’s create a benchmark to assess how Replit AI stacks up based on the metrics that matter to developers. Here’s how I evaluate each aspect, and I’ll give you a score out of 10. Feel free to share your thoughts on how you’d rate it!

✨ Usability: 8/10

The user interface is intuitive, especially the integration between chat and file explorer. But the AI’s over-control and the rigid completion path can be frustrating.

🏃‍♂️‍➡️ Performance: 7/10

Performance is stellar for smaller projects. But when it comes to larger, multi-file projects, the agents' unpredictable actions can slow down the process.

🏎 Speed: 7/10

It’s fast, but it threw me out of the flow as I was waiting for the final output. On top of that, the mouse-oriented workflow and inability to edit while agents are working introduce unnecessary delays.

💆‍♀️ Intuitiveness: 8/10

While the layout is clean, controlling the agents can sometimes feel counterintuitive, especially when they start changing files you didn’t intend them to.

🎡 Workflow Length (Clicks): 3/10

The experience could be more keyboard-friendly. Right now, there are too many clicks involved.

🛸 Innovation: 9/10

Replit is ahead of the curve in terms of agent integration. The way it handles chat and file interactions is forward-thinking, but it still needs to balance control and transparency better.

📡 Technical Relevance: 4/10

As AI-powered code generation tools go, Replit feels modern and integrated well with developer workflows. However, external dependencies remain a blind spot, and generating tests didn’t work as expected; tests failed, and the agent was lost after many iterations.

🎯 Flexibility & Control: 5/10

More granular control over agent behavior would be beneficial. Replit’s current setup feels a bit rigid for complex use cases.

🤹 Agent Autonomy: 7/10

Autonomy is both a blessing and a curse. While it’s helpful for automating mundane tasks, it can lead to unwanted side effects. For example, the agent gets stuck when generating tests.

Final score: 6.4

Replit AI: Final Thoughts

Replit’s AI agents are a fascinating glimpse into the future of coding with AI assistance. There’s a lot to love about their direction, but like any tool, it has its quirks. For smaller projects, it’s fantastic—quick, intuitive, and highly usable. However, for more complex, multi-layered projects, flexibility and control still need to be balanced.

The real magic in this journey isn’t just about automating code — it’s about learning which tools, design patterns, and workflows best support quality code generation without sacrificing developer control. And that’s a journey we’ll continue with each new tool we explore.

What score would you give Replit based on your experiences? Let me know so I can craft the next review with your input in mind!