Published on Aug 28th, 2025

The AI-Assisted Development Revolution

Published on August 28, 2025

Last week, I made a decision that would change everything about how I approach software development. I purchased a MacBook, and when it was delivered on Monday, I knew I was about to embark on something special. But this wasn't just about getting a new machine—it was about finally having the right tools to tackle what I've been avoiding for months: my massive stack of unfinished projects.

The Problem: The Unfinished Project Graveyard

Like many developers, I have a GitHub profile that tells a story of ambition, creativity, and... well, let's call it "optimistic planning." My repositories include:

• ClickRise - A ClickUp inspired project management platform (currently in active development)

• EducativeMachineLearning - Python exercises for ML engineering prep (module 1 complete)

• Fasolara - A solar company startup with full-stack implementation

• CodeniWork - A job applications tracking dashboard

• Bugginator - A bug tracking software (in active development)

• AWS Bootcamp CRUDDUR - Cloud infrastructure project provided by ExamPro

• Unity African Communities - A landing page for a Nonprofit organization (work in progress)

• Secret Chat and Whatsapp Clone - Next.js based messaging platforms based on MongoDB and PostgreSQL

• SmartNotes - An AI powered notetaking application used to power the chatbot functionality on SmartNotes and the tioye.dev dev portfolio

• Others - and dozens more on my GitHub

And that's just scratching the surface. Each project represents hours of planning, coding, and then... abandonment. Life gets busy, priorities shift, and suddenly you have a digital graveyard of half-built applications.

The Game Changer: AI Coding Assistants

What changed everything wasn't just the new MacBook—it was the realization that I now have access to something that didn't exist when I started most of these projects: AI coding assistants.

These aren't just code completion tools. They're full-fledged development partners that can:

• Understand complex codebases in seconds

• Debug issues that would take hours to solve manually

• Suggest architectural improvements

• Help refactor legacy code

• Generate comprehensive documentation

• Handle tedious boilerplate code

The Strategy: One Project Per Day (or Two)

With my new MacBook and AI assistants, I've adopted a simple but effective strategy: deploy one new app every day or every couple of days. Here's how it works:

Day 1: Assessment & Planning

• Review the unfinished project

• Identify the core functionality needed for MVP

• Plan the deployment strategy (usually Vercel for web apps)

Day 2: Development & AI Collaboration

• Use AI assistants to understand existing code

• Fix critical bugs and missing features

• Implement the minimum viable functionality

• Test core user flows

Day 3: Deployment & Polish

• Deploy to Vercel

• Fix any deployment issues

• Add final touches and documentation

• Move to the next project

The Results: From Graveyard to Portfolio

In just the past few weeks, I've managed to:

1. ClickRise - A fully functional project management platform with authentication, workspaces, projects, tasks, and team management

2. Machine Learning Prep - Comprehensive Python exercises and projects for ML engineering

3. Solar Startup Tools - Full-stack applications for solar company operations

4. E-commerce Dashboard - Functional admin interface for online stores

The AI Advantage: What Makes This Possible

Code Understanding

AI assistants can instantly analyze thousands of lines of code, understand the architecture, and identify what's missing. This saves hours of manual code review.

Bug Fixing

Instead of spending hours debugging, I can describe the issue to an AI assistant and get targeted solutions, often with explanations of why the bug occurred.

Feature Implementation

Need to add authentication? Database integration? API endpoints? AI assistants can generate the code, explain the implementation, and suggest best practices.

Documentation

One of the biggest time-sinks in finishing projects is documentation. AI assistants can generate comprehensive READMEs, API docs, and setup instructions.

The Learning Curve: Working WITH AI, Not Just Using It

The key insight I've discovered is that AI coding assistants aren't replacements for developers—they're amplifiers. You still need to:

• Understand the problem you're trying to solve

• Make architectural decisions about your application

• Review and validate the code that's generated

• Test and iterate on the solutions

But what used to take weeks now takes days. What used to take days now takes hours.

The Future: Sustainable Project Completion

This isn't just about finishing old projects—it's about changing how I approach software development entirely. Now when I start a new project, I:

1. Plan for completion from day one

2. Use AI assistants throughout the development process

3. Focus on core functionality rather than getting lost in edge cases

4. Deploy early and often to get real user feedback

The Portfolio Effect

What started as a cleanup operation has become a portfolio-building exercise. Each completed project now represents:

• A real, deployable application

• Demonstrable technical skills

• Problem-solving capabilities

• User experience design thinking

Lessons Learned

1. AI assistants are game-changers for solo developers

2. The right tools (like a new MacBook) can reignite passion

3. Unfinished projects are often just waiting for the right approach

4. Daily deployment creates momentum and accountability

5. Focus on MVP rather than perfection

What's Next

I'm not stopping at just cleaning up old projects. I'm using this momentum to:

• Build new applications that solve real problems

• Contribute to open-source projects

• Share knowledge about AI-assisted development

• Help other developers tackle their own project graveyards

The Bottom Line

My new MacBook arrived on Monday, and by Friday, I had deployed more applications than I had in the previous six months. The combination of better hardware and AI coding assistants has transformed how I approach software development.

If you have a stack of unfinished projects gathering digital dust, consider this your wake-up call. The tools are here, the time is now, and the results are incredible.

Your project graveyard doesn't have to stay a graveyard. It can become a thriving portfolio of deployed applications, each one a testament to your ability to ship real software.

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Ready to demolish your own stack of unfinished projects? Start with one. Use AI assistants. Deploy early. The results will surprise you.

Follow my journey on GitHub and check out my portfolio at tioye.dev.