DEV Community: OdaloV

Digital Hoarding

OdaloV — Sat, 11 Apr 2026 15:52:47 +0000

A personal journey through 4GB of laptop clutter and over 800 phone screenshots I'll never look at again

The discovery

During some late-night reading, I stumbled across a 2025 paper by Liu & Liu in Frontiers in Psychology on something called digital hoarding.
I'd never heard the term before.
But as I kept reading, I felt Called out.

They defined it as: "The compulsive accumulation of digital files to the point of distress and disorganization."
And I thought to myself ,that's not only a research subject. that's my laptop,and probably my phone too.

On my laptop:

~/Downloads – 47 PDFs, 12 driver installers, 3 tutorials I never finished. Oldest: 2019
~/Desktop – Screenshots of error messages I Googled and fixed. Oldest: 2021
~/code/experiments – 23 half-built projects, 18 with broken dependencies. Oldest: 2020
~/Documents/old-work – Repos from two jobs ago. Two jobs ago! Oldest: 2018

On my phone:

Screenshots folder – 1,112 images. Error messages, tweets, "read later" articles, memes.
Photos (duplicates) – The same picture saved 3-4 times.
Old app caches – 2.1 GB from apps I haven't opened in months.
Voice notes – 47 recordings. "Reminder to self" from 2022 to 2026.
WhatsApp images – From groups I left in 2023.

I was a digital hoarder with a terminal and a smartphone addiction.

What Liu & Liu taught me

The paper described digital hoarding as a "double-edged sword."
On one edge: It feels responsible. "I might need this someday." "Better to save it than lose it."
On the other edge: It's actively hurting me — on every device I own.
They listed consequences that hit too close to home:

Cognitive load – Every extra file is a tiny decision I don't make
Decision fatigue – Which of these 14 project folders is the real one?
Anxiety – "What if I delete something important?"
Battery drain – Your phone constantly indexing thousands of unused files

And the part that really got me: "A protective behavior that eventually becomes a burden."

The hidden cost never measured

Before cleanup:

Storage used: 10 GB
Boot time: 48 seconds
Search time: 6-8 seconds
Battery life: ~6 hours
Backup time: 45 minutes

After deleting 500+ old files and 2,000+ screenshots:

Storage used: 8 GB (down 2 GB)
Boot time: 31 seconds (down 35%)
Search time: 1-2 seconds (down 75%)
Battery life: ~8 hours (up 33%)
Backup time: 12 minutes (down 73%)

No hardware upgrade. No factory reset. Just… deleting things.

The developer-specific hoarding patterns

Liu & Liu didn't study developers specifically. But I noticed patterns unique to our craft — and how they spill onto our phones.

1: The tutorial graveyard

We start a tutorial. Clone the repo. Follow along for 30 minutes. Get distracted. Never finish.
But we keep the folder. Just in case.
My count: 23 unfinished tutorial projects. 18 using packages that are now deprecated.

2: The error screenshot museum

Something breaks. We screenshot the error on our laptop. Then we Google it. Fix it. Feel proud.
But we never delete some of the screenshots.
My count: 110 laptop screenshots + 1,110 phone screenshots. I will never look at 99% of them again.

3: I'll refactor this someday

Old projects. Old code. Old mistakes. We keep them like trophies.
My count: 4GB of code I haven't touched in over two years.

4: The screenshot spiral

See something interesting? Screenshot. Want to remember a tweet? Screenshot. Need to save a receipt? Screenshot.
Then never organize them. Never look at them. Never delete them.
My count: 1,112 screenshots. I remember taking maybe 200 of them.

5: The "I'll clean this later" cache (phone)

Apps cache images, videos, and files. We ignore it. It grows. We run out of storage.
My count: 2 GB of "System Data" — a black hole of forgotten files.

Liu & Liu ended their paper with a question:

"How do we design systems that support selective retention rather than indiscriminate accumulation?"
I don't have an answer. But for me,I'll start small. One old file. One screenshot. One deleted folder at a time.

Progressive Web Apps (PWAs): The Best of Both Worlds

OdaloV — Sun, 01 Mar 2026 12:38:02 +0000

What is PWA?

Progressive Web Apps are regular websites built with standard web technologies such as HTML, CSS and JavaScript, that progressively enhance to deliver an app-like experience. They work in any browser but can be installed on your device like a native app. Think of them as websites that put on an app costume.

Core Technologies

HTTPS - Secure connection required for all modern web capabilities.
Web App Manifest - A JSON file defining your app's name, icons, colors, and launch behavior.
Service Workers - Background scripts that enable offline functionality, caching, and push notifications.

Why PWAs Matter

For Users

Install with one click - No app stores, no approvals, no fees.
Works offline - Access content even without internet.
Lightweight
Cross-platform - Same app works on any device with a browser.

For Developers

Single codebase - One app for all platforms instead of separate iOS/Android builds.
Lower costs - PWA development ranges from $15,000-$150,000 versus $50,000+ per native platform.
No app store gatekeepers - Deploy updates instantly without waiting for approval.
SEO-friendly - PWAs are indexable by search engines unlike native apps.

Real-World Example

Microsoft:

Microsoft took a data-driven approach to PWAs, automatically identifying 1.5 million progressive web apps for inclusion in the Windows Store. This discovery opened up a massive ecosystem of applications that could run natively on Windows without any additional development work.

The impact was twofold:

Users gained access to millions of apps without waiting for developers to build Windows-specific versions
Developers saw their apps appear in the Windows Store automatically—no extra effort required

Microsoft's embrace of PWAs validated that the technology wasn't just for small projects—it was a legitimate distribution channel for the world's largest operating system.

When to Choose PWA

PWAs are ideal for :

E-commerce - Higher conversions, better mobile experience.

Content-driven apps - News, blogs, media.

Businesses with limited budget - One app for all platforms.

Emerging markets - Works on slow connections.

The web is evolving, and PWAs are leading the charge toward a future where the line between websites and apps disappears entirely.

Agentic-AI :Simple tools to autonomous partners

OdaloV — Mon, 02 Feb 2026 09:26:32 +0000

If you have been following AI development,then you've seen the shift, from ChatGPT answering questions to Devin writing entire codebases. From simple chatbots to systems that plan, execute, and adapt.

What Makes an AI Agentic?

Agentic AI is about ,agency,the capacity to act independently toward goals. While a traditional AI model generates text based on patterns, an AI agent:

Sets and pursues goals
Breaks problems into steps
Uses tools to interact with the world
Learns from feedback
Adapts its approach when stuck

It's like moving from a calculator;executes commands, to a mathematician;solves problems using tools and reasoning.

The Fundamental Loop: Perception → Reasoning → Action

The simplest theoretical model of an AI agent is the Perception-Reasoning-Action cycle:
In practice with LLMs, this becomes the ReAct pattern (Reason + Act):

    python

    # How an AI agent thinks and acts
    def agent_loop(objective, tools, memory):
    while not objective.achieved():
    # 1. PERCEPTION: Look around
    observation = perceive_environment()

    # 2. REASONING: Think about next step
    thought = llm_reason(objective, observation, memory)

    # 3. ACTION: Do something with tools
    action = choose_action(thought, tools)
    result = execute_action(action)

    # 4. UPDATE: Learn and continue
    memory.update(thought, action, result)

return "Task completed"

Breaking It Down with Fast Food

Let's say you're craving KFC and tell an AI agent: "Get me KFC for dinner"

Old-School AI (Traditional Chatbot)

Would give you instructions:

Go to the KFC website or use Glovo

Agentic AI (Autonomous Assistant)

Actually does it for you. Here's how it thinks:

Agent's Thought Process:

PERCEIVES:

Checks your current location

Remembers you ordered KFC last Tuesday

Notes you usually ask for extra ketchup
REASONS :

They want KFC. Let me check where they are

Found 3 KFCs nearby. Which one has the shortest wait time?

They like the Zinger Burger based on last order.

Should check for any discounts or offers
ACTS :

Searches for nearby KFC locations

Checks opening hours and current wait times

Compares prices and specials

Places the order via API

Tracks the delivery in real-time
UPDATES :

Noted: they want extra ketchup. Remember for next time.

The bottom line: The agent doesn't just talk about KFC ,it gets you the actual chicken.

Why This Matters
Agentic AI represents a fundamental shift:

You give goals, not step-by-step instructions

AI handles complex multi-step processes

Systems improve through experience

One agent replaces what used to take multiple tools