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Coding Agents: zed.dev

Custom Agentic IDE with Beautiful UI/UX, Browser Use & Intuitive Flows

Papajams

I Built Three Apps Solo in Weeks.


Two years ago, I had this idea amongst many others, but was stuck in a familiar loop: overly ambitious prototypes leading to abandoned repos. Integrating machine learning? Needed an expert. Blockchain micropayments? Complexity rabbit hole. Real-time computer vision and audio processing? WTF.

Fast forward to 2025 and—i'm shipping. No team. No burnouts. No funding.

The shift? AI-integrated tooling. I no longer have to choose between ambition and scope. With tools like Zed, I can build full-stack systems with the potential to bring my vision to reality.

This isn’t a productivity hack. It’s a structural shift in how software is made.


Exponential Developer

Traditional development follows a linear growth model: more features = more time = more people. But exponential developers operate differently. With AI-native development environments, they:

  • Offload complexity to AI agents

  • Rapidly prototype across technical domains

  • Maintain architectural integrity without mental overhead

What used to take a team of five over six months can now be done by one person in a few weeks.


The Forces Behind the Shift

The rise of the exponential developer sits at the intersection of:

  • Wright’s Law: Efficiency improves with cumulative experience

  • Moore’s Law: Computing power doubles roughly every two years

  • Kurzweil’s Law of Accelerating Returns: Technological change is exponential, not linear

We’ve hit an inflection: where AI doesn’t just assist code completion—it drives full system architecture.


Case Study #1: MegaVibe – Live Performance Economy

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Zed's UI/UX modifications span animations, feature cards & much more

Idea: A platform where artists monetize performance energy through real-time tips, verified by location.

Architecture:

  • Mantle blockchain micropayments

  • GPS-verified proof-of-presence protocol

  • WebRTC live streaming

  • Decentralized tipping infra

Old Way:

  • 4-5 developers across frontend, blockchain, backend, and DevOps

  • 8-12 months development

  • $500K+ budget

What I Did Instead: With Zed, I:

  • Deployed smart contracts in days, guided by AI-generated Solidity patterns

  • Built GPS proof-of-presence logic with AI code review support

  • Integrated WebRTC livestreaming using AI-guided React flows

  • Delivered the MVP in 1 week: https://megavibe.vercel.app

Results:

  • Deployed a fully working decentralized tipping platform

  • Shipped live to users for under $500 in infra/tooling costs (testing in beta at next event)


Case Study #2: ImperfectCoach – Multi-Model AI Orchestration Fitness Platform

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Goal: Real-time AI coaching with LLM orchestration and user motion tracking

Stack:

  • OpenAI, Gemini, Claude via serverless LLM router

  • Real-time motion tracking with MediaPipe

  • Blockchain-based identity verification

  • Supabase DB + AWS Lamda

Traditional Build Requirements:

  • AI/ML expert, blockchain dev, backend architect, UI/UX engineer

  • 6-9 month timeline

My Reality:

  • Zed’s multibuffer editing enabled orchestration of multiple LLMs

  • AI agent helped debug API response issues across providers

  • Created the full system from scratch in under 4 weeks: https://imperfectcoach.netlify.app

Key Unlocks:

  • Zero external research required for AI model integration

  • Real-time code insights into system dependencies

  • Single codebase orchestration with full architectural visibility

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AWS + Supabase Backend Support

There is ZERO chance I would ever have been able to navigate the complexity of AWS console + Supabase simultanously to deliver on this. Its performant and useful, super proud its out. For a limited time its free for users to try out, kindly share feedback and tweet about us: https://x.com/ifdotfun


Case Study #3: ImperfectBreath – Computer Vision Wellness Platform

Vision: Personalized breath coaching using computer vision and real-time audio processing

Technical Stack:

  • Computer vision for posture analysis

  • Real-time audio analysis for breath pattern detection

  • AI-generated coaching feedback

  • WebRTC for live coaching

Challenges:

  • Real-time ML pipelines

  • Cross-modal data synchronization

  • Frontend motion design

My Approach:

  • Built CV pipeline in 48 hours with AI assistance

  • Designed ML-based feedback loop without ML expertise

  • Streamlined complex UI animation using AI-injected CSS/JS logic

Output:

  • A functional, responsive platform demo in a week

  • Ready for real user feedback and live testing

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ZED ui/ux is beautiful, as is its efficacy!

Economics of Exponential Development

Factor

Traditional Team

Exponential Dev (Me)

Timeline

8-12 months

3-4 weeks

Team Size

4-6 people

1

Cost

$500K+

<$20K

Tooling

VS Code + plugins

Zed (AI-native)

Debugging Time

40+ hrs/week

~10 hrs/week (AI-aided)

These are not minor improvements. They're a restructuring of the cost-function of software development.


What Makes Zed the Right Tool

When I first came across it I was hesitant to download a dedicated IDE - why not just use an extension in VS CODE?! Turns out by vertically integrating their stack they can really optimise the user experience.

Key Differentiators:

  • <1s startup time

  • Native multiplayer coding

  • Context-aware AI via Agent Panel

  • Low memory + power usage

  • Full-codebase understanding

Table: Zed vs Others

Metric

Zed

VS Code

JetBrains

Startup Time

<1 second

3-5 sec

5-10 sec

RAM Usage

~150MB

~500MB

~700MB

Collaboration

Built-in

Plugins

Complex

AI Context

Full

Partial

Plugin

Source Model

Open (GPLv3)

Closed

Closed


Takeaways

  1. AI as a Teammate: Not a helper. I ask it hard questions. We design systems together.

  2. Architectural Thinking Wins: Coding is easier now. The hard part is systems thinking.

  3. Start Small, Iterate Fast: I don't aim for perfect. No problem is now unsolvable.

  4. Imagination Is the New Bottleneck: Not tech skills.


From Idea to Execution

The hardest part of building used to be execution. Now, it’s ideation and discernment. If you’re a developer who’s been burned by the complexity of full-stack ambitions, I’m here to tell you: it’s time to build again.

The tools have changed.

The game has changed.

And you? You just might just be a more exponential developer than I am, if you try!

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All projects referenced in this article are live open-source repositories available on GitHub:

Supporting writers is beyond the call of duty, reading this far is its own form of glory, appreciate you.

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Coding Agents: zed.dev