Launching today
Enia Code
Proactive AI that refines code & learns your standards
112 followers
Proactive AI that refines code & learns your standards
112 followers
Most AI coding tools wait for you to ask. Enia Code doesn’t. Enia is a proactive AI coding agent that detects bugs, performance issues, architectural inconsistencies, and refactoring opportunities — as you write code. No prompting. No context re-explaining. No workflow disruption.
Enia Code
I’m a developer and CEO, and this product started from my own frustration. Over the years, I’ve used countless coding tools that only react after something breaks — after the bug appears, after performance drops, after architecture gets messy. But real development doesn’t work like that. When we code, we’re constantly thinking ahead. We anticipate problems. We refactor before things collapse. I kept asking: why can’t our tools think that way too? That question led us to build Enia Code.
There are already many AI coding tools — copilots, editors, chat-based assistants. Most of them wait for prompts. Enia is different. It’s proactive. It detects bugs, performance risks, architectural inconsistencies, and refactoring opportunities as you write. No constant prompting. No re-explaining context. No switching tabs. It works quietly inside your IDE, adapting to your coding habits and team standards over time. The goal isn’t to replace developers — it’s to protect their flow.
We believe coding tools are evolving from reactive copilots to proactive agents. The next step isn’t just faster autocomplete — it’s intelligent systems that anticipate, learn, and grow with your project. Software complexity is increasing, solo developers are building bigger systems than ever, and “flow” is becoming the most valuable resource. The future of AI coding isn’t about answering questions — it’s about preventing the need to ask them in the first place.
If you have any thoughts, ideas, or feedback, I’d truly love to hear them — feel free to drop a comment and let’s discuss.
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Happycapy
@jessica_miller_7 Interesting direction. Proactive coding agents feel like the next step beyond prompt based coding tools. Curious how it decides what to fix or suggest in real time.
@jessica_miller_7 proactive is what I need. but what model can i use here? can i use skills
PopPop AI Vocal Remover
I’ve been building SaaS tools for the past few years, and one thing that always slows me down is discovering architectural problems way too late. Refactoring a working system is painful. The idea of a tool that signals these issues earlier sounds really valuable. Curious whether Enia detects these patterns based on past projects or just the current repo context.
Enia Code
@charlenechen_123 That’s actually the exact frustration that pushed us to build Enia in the first place. We ran into the same thing a few times — everything looks fine while you’re building, and then a few months later you realize the architecture is fighting you...
Right now most of the signals come from the current repo context (structure, dependencies, patterns in the codebase, etc.), so it’s looking at how the system is evolving while you’re actively working in it.
We’re also exploring how to incorporate longer-term signals from project history over time, but getting the “current repo awareness” right was the first step.
Curious — what kind of architectural problems tend to show up late for you? Dependency cycles, scaling bottlenecks, or something else?
Happycapy
I work on a small startup team where we ship features quickly, and technical debt inevitably creeps in. Having something that proactively points out potential architectural drift could actually save us a lot of cleanup later. Wondering how customizable the rules are for different teams:)
Enia Code
@lyss_luo That’s a very real scenario, Lyss. Fast-moving teams tend to accumulate technical debt before anyone notices 😅Right now the system focuses on detecting structural patterns automatically, but making rules more customizable for different teams and workflows is definitely something we’re exploring.
Gro
Would love to see some examples of issues Enia caught proactively. Real-world scenarios would help illustrate the value.
Enia Code
@leo_aj Thanks Leo! That’s a great suggestion — we’re actually putting together a few real-world examples and will share them soon. Appreciate the feedback.
Mom Clock
Looks sweet!
I wonder how proactive it will be, especially when I am working on a large project.
Enia Code
@justin2025 Thanks Justin! Great question, especially for larger projects where issues tend to surface much later.
When you’re coding, Enia can surface potential risks directly in the IDE as small prompt bars.
It analyzes the current context and flags patterns that might become problematic as the project grows. And it’s not intrusive — you can choose to review the suggestion, ignore it, or adjust the code based on the feedback.
Most AI coding tools are reactive. This feels more like an observer system that monitors the project evolution. That's a pretty interesting design direction.
Enia Code
@ibitekukie Thanks for sharing this perspective!
AdFox (formerly GoodsFox)
The plugin approach is smart. One challenge with new dev tools is adoption friction. If it integrates directly into existing IDE workflows, that's a big plus.
Enia Code
@janicelewis00 Great point, Janice. Adoption friction is definitely one of the hardest parts for dev tools.
That’s exactly why we focused on integrating directly into existing IDE workflows so developers can use it without changing how they already work. In practice we’ve noticed that even small workflow disruptions can make people abandon a tool, no matter how useful it is.
The idea is to keep everything lightweight and contextual — surfacing signals while you’re coding, rather than requiring a separate tool or process.