I Used Ai to Code a Very Simple Game - Is This The Future?

With Cursor it was pretty simple but very helpful to have a smart Ai bot to chat with

iRobot much?

Did you ever see the movie Hackers (1995) with Angelina Jolie? That’s kind of how I feel right now installing random stuff using my computer Terminal based on what some random Ai startup is telling me to do - watching random characters, words and I dont even know what type out and move across my screen as things get installed and configured…

If you’ve been on Twitter or read the tech news over the last week, the biggest thing right now is Ai coding assistants, specifically Cursor. There are many out there like Microsoft CoPilot, but Ive never used it and honestly dont even know where to start, which is why Cursor was so easy. I literally downloaded it, prompted their chatbot with ideas, it printed the code, which confused me and made no sense, so I asked more questions until eventually I learned and figured it out. It’s very apologetic and empathetic too lol.

I haven’t really coded (if you can even call it that) since I failed AP Comp Sci in high school (2005 yes I’m old) and more seriously with my first startup out of my dorm-room building personal websites for friends to get jobs using Dreamweaver, CSS and HTML. The most basic coding possible really, but it worked as a start to something larger (startup got acquired!), which is exactly where we are again now 20years later. The problem is kind of that 99% of things will be crap but that’s OK because iteration is the new innovation.

So for those looking to tinker with ideas, test out concepts, or even develop early-stage prototypes, Cursor provides the perfect environment. It strips away many of the complexities associated with traditional coding environments (which I dont know much about), making it accessible to a broader audience, including those who may not have formal training in software development like me.

However, while Cursor is excellent for getting ideas off the ground, it's important to recognize its limitations and why it wont replace experienced developers just yet. Building real, scalable platforms or companies requires more than just a basic understanding of coding. Deep technical knowledge of systems architecture, scaling strategies, and integrations is essential to create robust, secure, and scalable applications. The simplicity of Cursor, while beneficial for initial ideation, can mask the complexities that arise when trying to take an app from a prototype to a production-level platform.

Hence my really bad and impossible game below I made in a few hours because I had to do lots of Ai prompting, learning Github repositories then how to host/launch it using Netlify.

I also was hanging with a VC friend last week who was talking about their do diligence process and how they rate startups. So I prompted a few times, make a few edits, changes etc and created a simple rating system for 3 partners to give feedback on a potential startup they’re looking at. This literally took 20 minutes to do right in front of them and while it’s very simple, just the process of a non-technical person watching it happen in real time, definitely blew their mind while I played it cool, literally making it up as I went along.

The AI Landscape: Current Platforms and Future Prospects

The broader AI landscape though is evolving at a break-neck pace, with platforms like Cursor leading the charge in democratizing access to seemingly complex Ai thanks to the help of actually smart chatbots. These tools are lowering barriers to entry, enabling more people to engage in coding, data analysis, and even machine learning. The AI ecosystem is now more diverse than ever, with applications ranging from natural language processing (NLP) to computer vision, robotics, and beyond available to basically anyone.

Benefits for Hobbyists and Prototyping:

  1. Lowered barrier to entry for coding

  2. Accelerated ideation and prototyping

  3. Assistance with syntax and common coding patterns

  4. Valuable learning tool for beginners

Limitations for Production-Ready Applications:

  1. May not adhere to best practices or company-specific coding standards

  2. Limited understanding of complex system architectures

  3. Potential security vulnerabilities if not properly vetted

  4. Lack of deep domain knowledge for specialized industries

The Broader AI Ecosystem is Massive

AI-assisted coding is just one facet of the rapidly evolving AI landscape though. Let's explore other key areas where AI will make a significant impact:

1. Natural Language Processing

  • Large Language Models

  • Chatbots and virtual assistants

  • Speech recognition and synthesis

  • Machine translation

2. Computer Vision

  • Image and video recognition

  • Object detection and tracking

  • Facial recognition

  • Augmented and virtual reality

3. Robotics and Automation

  • Industrial automation

  • Autonomous vehicles

  • Drones and unmanned systems

  • Robotic process automation

4. Machine Learning Platforms

  • TensorFlow

  • PyTorch

  • Amazon SageMaker

  • Google Cloud AI Platform

5. AI in Business Intelligence

  • Predictive analytics

  • Customer segmentation

  • Fraud detection

  • Recommendation systems

What else…?

Future Applications of AI

As AI continues to advance, we can expect to see innovative applications across various industries - there is still so much green space opportunity as it will take years to reach, teach, convince and integrate.

Healthcare

  • Personalized medicine

  • Drug discovery

  • Medical imaging analysis

  • Predictive diagnostics

Education

  • Adaptive learning systems

  • Automated grading and feedback

  • Personalized curriculum development

Environmental Sustainability

  • Climate modeling and prediction

  • Optimizing renewable energy systems

  • Smart grid management

  • Wildlife conservation

Finance

  • Algorithmic trading

  • Risk assessment

  • Personalized financial planning

  • Fraud detection and prevention

Agriculture

  • Precision farming

  • Crop yield prediction

  • Automated pest and disease detection

Creative Industries

  • AI-generated art, music, and literature

  • Virtual influencers and digital humans

  • Personalized content creation

Cybersecurity

  • Threat detection and prevention

  • Automated incident response

  • Behavioral analysis for anomaly detection

What else…?

Investing in Broad and General VS Niche and Specific?

As AI continues to advance literally everyday, we can expect to see more sophisticated tools that bridge the gap between simple prototyping and production-ready applications. However, the need for deep technical understanding, especially in areas like system architecture, scalability, and integration, will remain crucial for building robust, enterprise-level solutions.

As an early stage investor investing in the broad LLMs and hardware is basically out of reach because most of those startups begin with $10M+ raises at $50M+ valuations which sadly doesn’t work for Emerging Managers economics. That means we need to find niche and specific startups/founders with a moat in industries where their expertise and network are their unfair advantage initially.

😂 MEME of The Week 😂 

Always have an ask!

  1. How often do you use Ai?

  2. Have you tried to code using Ai yet?

  3. Send me your best early stage startups to invest in!

  4. Your trusted guide for health www.roon.com

FIND ME: 𝕏 @Trace_Cohen / in LinkedIn

Reply

or to participate.