From Procrastination to Progress: How AI has helped me

By Lucas Fernandes Aguiar

April 13, 2025

For years, I was trapped in a cycle of ambitious beginnings and disappointing endings. My GitHub repository had become a digital graveyard of half-completed projects—enthusiastic starts abandoned at the first sign of a significant challenge. But over the past few months, something remarkable has happened: I’m actually finishing what I start, and the catalyst wasn’t a new productivity system or time management technique. It was AI.

A Little Background

Before diving into my productivity transformation, it helps to understand where I’m coming from. I’m a chemist by training, working in a government position while also collaborating on research projects at the local university. I don’t have a formal IT or software development background, but I’ve been increasingly drawn to data science projects that intersect with my professional work.

This non-traditional path meant that when I hit technical roadblocks in my coding projects, they often felt insurmountable. Without the foundation that computer science majors take for granted, each obstacle required significant effort to overcome—effort that my motivation couldn’t always sustain.

The Procrastination Trap

My story probably sounds familiar to many developers. I’d start each project with genuine enthusiasm and ambition, convinced that this time would be different. Two weeks later, I’d be staring at the same code I’d written during those first few productive days, feeling stuck and uninspired.

The pattern was predictable:

I’d hit a technical roadblock and spend hours “researching” solutions (mostly scrolling through Reddit)
Configuration became a convenient distraction—tweaking editor settings instead of writing actual code
Complex problems would send me spiraling into perfectionism, unable to commit to an approach
New project ideas would arrive just as existing ones became challenging, creating an endless cycle of abandoned work

What was particularly frustrating was that I’d tried all the standard productivity advice. I bounced between productivity systems like a pinball—GTD one month, bullet journaling the next, then whatever new app promised to finally “fix” me. I’d obsessively organized tasks in Todoist, broken projects into small chunks, used Pomodoro timers, and blocked distracting websites. I was spending more time managing my tasks than actually doing them.

Each new system would work for a week or two before I’d fall off the wagon. I was exhausted by this endless cycle of optimism followed by disappointment. These techniques would work for a while, but inevitably the projects would stall when I hit that critical point of resistance.

The Unexpected Solution

The shift in my productivity didn’t come from yet another task management system or productivity hack. It came from where I least expected it: artificial intelligence.

My journey began innocently enough—I was simply exploring AI-enhanced code editors like Cursor, Windsurf, and eventually Zed to see if they could help me code more efficiently. What I discovered instead was a fundamental transformation in how I approach work itself.

These tools did something no productivity system had managed before: they eliminated the friction points that typically triggered my procrastination. When I encountered a technical challenge that would previously send me spiraling into distraction, I now had an AI assistant that could offer immediate guidance, helping me maintain momentum rather than lose it.

The key wasn’t just having answers—it was preserving the psychological flow state that’s so crucial for creative work. The moment I realized I was finally completing projects that had been stuck at 60% for months, I knew something profound had changed in my relationship with work.

From “Someday” to “Done”: The Completion Revolution

The most concrete evidence of this transformation is simple but powerful: I’m actually finishing projects now. My “someday/maybe” folder is emptying as long-dormant ideas finally come to life.

A data analysis tool that had been stuck at 60% completion for nearly a year was finished in a single weekend. My personal website redesign, which had been in perpetual planning purgatory as I compared endless framework options, went from concept to deployment in two weeks. Those utility scripts I always meant to write “when I had time” now take minutes instead of hours to create.

The shift wasn’t about finding more time or discipline—it was about dramatically lowering the activation energy required to make progress. When the barrier to continuing work becomes smaller than the psychological cost of procrastination, the equation changes. Suddenly, it becomes easier to do the work than to avoid it.

What’s particularly satisfying is the compound effect of completion. Each finished project builds confidence that carries into the next one, creating a virtuous cycle that replaces the old procrastination loop.

Even my wife has noticed the difference, commenting on how much I’ve been learning lately and how some of these ideas could potentially turn into business opportunities. I’ve started automating parts of my work processes, which frees up even more time to explore new projects and ideas. This cascading effect of productivity has been perhaps the most unexpected benefit of the whole experience.

Breaking Through “The Wall”

Every creative project has what I’ve come to call “The Wall”—that critical juncture where initial enthusiasm fades, technical challenges multiply, and the temptation to abandon ship becomes nearly irresistible. It’s the point where most of my projects used to die.

With AI assistance, I’ve developed specific strategies to push through these barriers:

Perspective Shifting: When I feel stuck on a particular approach, I prompt the AI to suggest alternative implementations, breaking me out of tunnel vision
Progressive Breakdown: For intimidating components, the AI helps decompose them into smaller, more manageable steps that maintain a sense of progress
Momentum Building: When motivation wanes, I use AI to help me generate quick wins—small, satisfying completions that rebuild my enthusiasm for the larger project
Immediate Unblocking: Instead of scheduling research for later (which often meant never), I get immediate guidance that keeps me in flow

The psychological impact of removing these friction points has been profound. The AI doesn’t just solve technical problems—it preserves the mental state that makes productive work possible in the first place.

Beyond Coding: A Complete Workflow Transformation

Before diving into AI-enhanced tools, I was a dedicated user of traditional productivity systems. Todoist was my daily companion – meticulously organizing my day into blocks, setting priorities, and checking off tasks. I had my morning routines, my pomodoro timers, and my carefully scheduled deep work sessions. While this approach worked to some extent, it often felt mechanical and constraining. I’d complete tasks but still didn’t feel genuinely productive or creative.

An unexpected benefit of embracing AI tools has been a complete transformation of my productivity philosophy and workflow.

From Task Management to Exploration

Instead of rigidly blocking my day for “must-do” tasks, I now approach work with more fluidity and exploration. The AI assistants have given me permission to follow my curiosity while still making progress. Here’s how my workflow has evolved:

Morning Brainstorming: I start my day with a conversation with Claude about what I want to accomplish, letting the AI help organize my thoughts rather than checking a predetermined task list
Project Mapping: For complex projects, I use AI to create visual maps of components and dependencies, giving me multiple entry points depending on my energy level
Flexible Focus Sessions: Rather than forcing myself to work on specific tasks at specific times, I allow myself to choose what I’m genuinely interested in exploring that day
Obstacle Removal: When I hit a barrier, instead of scheduling it for “later research,” I immediately engage the AI to help me work through it while my interest is still high

Cross-Domain Applications

What’s been particularly exciting is how these benefits have extended beyond my coding projects to my primary work as a chemist. I’ve started using AI tools to:

Analyze research papers more efficiently and extract key insights
Generate hypotheses for laboratory tests
Create better data visualization of experimental results
Automate repetitive aspects of my government work
Develop scientific documentation and reports with greater clarity

This cross-pollination of productivity techniques has created a flywheel effect where improvements in one domain accelerate progress in others.

Taming the Shiny Object Syndrome

One of my biggest productivity killers has always been the constant influx of new ideas. Just as I’d get traction on a project, a new concept would capture my imagination, and the existing work would be abandoned.

AI has helped me transform this tendency from a liability into an asset:

When a new idea strikes, I quickly capture it through a structured conversation with an AI assistant
Together, we evaluate its feasibility, scope, and potential connections to existing projects
I create a quick proof-of-concept to satisfy my immediate curiosity
The assistant helps me document the concept thoroughly enough that I can return to it later
Most importantly, I can then redirect my focus back to my primary project, knowing the new idea has been properly preserved

This approach acknowledges the creative value of new ideas while preventing them from constantly derailing ongoing work—turning what was once my biggest distraction into a structured process for building a rich backlog of future possibilities.

I should note that while I’m completing more projects than ever before, I’m also generating ideas at a faster rate—which means my backlog continues to grow despite my increased productivity. I’ve made peace with this reality by acknowledging that not every idea deserves to be completed. I’m conscious that many items in my backlog will only be executed if they remain important and relevant in the future. This perspective removes the pressure to “do it all” and allows me to focus on what matters most in the present while maintaining a curated library of possibilities for later exploration.

The Liberation from Traditional Productivity

Surprisingly, by releasing myself from the rigid structures of traditional productivity tools, I’ve never felt more productive. I’ve discovered that:

My natural curiosity is actually a productivity driver when properly channeled
The “must-have” task blocks often created resistance and anxiety that led to procrastination
Following interest leads to higher quality work and more creative solutions
Quick AI assistance removes the friction points that would previously derail my momentum
Projects actually get completed instead of being perfectly planned but never finished

The key has been leveraging AI tools not just for technical assistance, but as thought partners that help maintain flow and remove barriers to progress. By embracing this more organic approach to productivity, I’ve found myself consistently making more meaningful progress than I ever did with traditional time-blocking and task management systems.

Finding What Works For You

After trying various approaches, I’ve settled on a combination of tools that work for my brain and workflow patterns. The specific tools aren’t as important as finding what reduces friction and maintains your momentum. For me, it’s about having the right support available exactly when I need it, whether that’s through a code editor’s built-in AI or through companion applications that integrate with my workflow.

What’s more fascinating is how these tools have sparked ideas for potential side businesses. As I’ve automated more of my work processes and developed new skills, I’ve begun to identify opportunities where these solutions might help others facing similar challenges. My wife has noticed this transformation, commenting on both the quantity of what I’m learning and the practical applications that could potentially turn into business ventures. This entrepreneurial angle has added another layer of motivation to my productivity system.

The Psychology Behind the Transformation

Reflecting on this journey has helped me understand what was really happening. The fundamental shift wasn’t about the technology itself—it was about how these tools addressed the psychological barriers that trigger procrastination.

Here are the key principles I’ve extracted that might help others, regardless of their specific tools:

Eliminate Decision Fatigue: Procrastination often begins with ambiguity. When there are too many possible approaches or too many small decisions to make, willpower depletes rapidly. AI assistance dramatically reduces these decision points by providing clear, contextual guidance.
Lower the Activation Energy: The energy required to start or resume work is often the biggest barrier. Finding tools that make those first steps frictionless—whether through scaffolding, templates, or guided assistance—can be the difference between action and avoidance.
Preserve Mental Context: One of the most underappreciated aspects of productivity is context preservation. The cognitive cost of rebuilding mental context after an interruption is enormous. Tools that keep you in flow by providing immediate assistance without requiring context switching fundamentally change the economics of attention.
Embrace Imperfection: Perfectionism is procrastination’s silent partner. Having an AI suggest “good enough” solutions helps overcome the paralysis of trying to find the perfect approach. You can always refine later, but you need something tangible first.
Build Success Spirals: Small wins create psychological momentum. By lowering the barrier to these small completions, AI tools help create what psychologists call “success spirals”—virtuous cycles where each small accomplishment builds confidence for the next challenge.

A New Framework for Evaluating Tools

My experience has led me to develop a different framework for evaluating productivity tools—one focused on psychological friction rather than features. When considering a new tool, I now ask:

Does it reduce friction at the specific points where I tend to get stuck?
Will it help me maintain mental context or force costly context switching?
Does it lower the activation energy required to start or resume work?
Can it help me push through the challenging middle phases of projects?
Does it integrate naturally with my thinking process or force me to adapt to its logic?

These questions reflect a fundamental shift in perspective: the best tool isn’t the one with the most features or the slickest interface—it’s the one that works with your specific psychological patterns rather than against them.

Future Outlook

The landscape of development tools continues to evolve rapidly, and I’m excited to see how AI integration becomes increasingly sophisticated. But the most important realization has been that the right tools aren’t just about coding efficiency – they’re about psychological barriers and how to overcome them.

With the right setup, I’ve managed to transform my relationship with unfinished projects, turning what was once a source of guilt into a genuine sense of progress.

Has anyone else found AI tools helpful for overcoming procrastination? I’d love to hear about your experiences!

You can reach out to contact me about this and other topics at my email [email protected]