LinkedIn or LinkeDone?

Kevin G — Fri, 17 Apr 2026 20:05:42 +0000

Nine months of silence is a long time to spend shouting into a void.

Since last July, I have been a full-time participant in the current job market. My background isn’t thin: it’s a ten-year portfolio of coding that includes six years of self-taught grit, 2.5 years of professional full-stack experience across multiple companies, and the ongoing management of a live production site. I’ve even sat in the lead chair for a startup, handling everything from embedded software to team management and architecture decisions.

Yet, despite a decade of technical work, a small portfolio, and consistent applications for roles I have already performed, the result is a perfect zero. Not a single interview request in 270 days.

The Audit

When logic fails, you start running experiments. To see if the issue was my approach or the platform itself, I treated my search like a technical audit:

The Rebuild: I scrapped my CV and built new versions from the ground up, matching the specific vernacular of each job description.

The Stress Test: I even tested the "validity" of the listings by slightly embellishing qualifications to create a near-perfect match for the algorithms.

The response remained unchanged: absolute silence. It is a strange reality when a candidate with high-stakes production experience cannot even trigger a screening call.

A Professional Marketplace?

It forces a necessary question: Is LinkedIn still a job board, or has it transitioned into just another social media platform for sharing opinions, accolades, and memes?

The math doesn't seem to add up. It leads one to wonder if many of these "openings" are actually legitimate opportunities. Are we looking at ghost roles—corporate theater used to project an image of growth and strength while hiring is effectively frozen?

The Documented Reality

This isn’t a hot take; it’s a record of a broken feedback loop. When 270 days of consistent effort from an experienced developer yields zero engagement, the system has drifted far from its original purpose.

I am documenting this simply to ask: is this the new standard? If the primary goal of connecting talent with work is no longer being met, is it time to consider a major migration toward something that actually works?

Has anyone else met this level of silence?

I spent a year building a PWA to track 150 cafe workspaces. Did AI actually help, or did it just give me a "Tinder for Coffee"?

Kevin G — Wed, 28 Jan 2026 15:47:31 +0000

The Premise I’m a remote worker.

I spent the last year working from 150+ cafes in Denver because I was tired of "Google Maps Roulette"—where a 5-star review means great lattes, but zero outlets and a "no laptops" policy.

To solve this, I built

caferoamer.com

a Vanilla JS/PHP/MySQL PWA. Along the way, I leaned on AI to "speed things up." Looking back at the repo, I’m not actually sure if it saved me time or just gave me new ways to procrastinate.

The "Cool(ish)" UI Trap One afternoon, I decided the site needed a "discovery mode." Instead of a boring list, I thought: “What if it was like Tinder, but for cafes?”

With an AI coding assistant, I knocked out the basic swiping logic in minutes. It felt like magic. But then came the "jank":

Handling touch-start vs. mouse-down events across different mobile browsers.

Getting the "swipe-away" animation to feel fluid and not like a PowerPoint transition.

Managing the state so that a "swiped" cafe didn't immediately reappear in the main feed.

I spent three days polishing a feature that took 30 minutes to draft. It’s "cool," but does anyone actually want to swipe right on a coffee shop? Probably not. AI lowered the barrier to entry for a "fun" feature, which lured me into a week of UI polishing I never planned for.

When AI Became a Time-Sink: I used AI to help build my "Accidental Backend"—a custom firewall, an email server from scratch, and a sophisticated weighted-randomization algorithm for the feed.

The AI was great at generating the "boilerplate" for things like:

PHP rate-limiting logic.
SQL cleanup queries for my 150+ messy field notes.
PWA manifest configurations.

But the friction started when the "boring" stack (Vanilla PHP) met "complex" AI-generated logic. Because the AI didn't have the full context of my custom-built, dependency-free architecture, it kept suggesting solutions that required libraries I didn't want to use. I spent a significant amount of time "un-hallucinating" the code back into raw PHP.

The Verdict: Net Gain or Net Loss? If I'm being honest:

The Wins: AI was a beast at data transformation. Moving my "old person" screenshots and messy notes into a structured MySQL schema was 10x faster.

The Losses: It encouraged "Feature Creep." Because I could generate a merchant-claiming dashboard or a payment-integrated ad engine in an afternoon, I did.

I built a solution for a 1,000-city platform before I even had 50 users in Denver.

The Real Validation now that the "AI-fueled" build phase is over, I’m back to the hard part: human validation. I’m looking for 500 beta users to tell me if the "vibe" metrics I collected (like lighting and food variety) are actually useful, or if I should have spent less time on the "Tinder-swipe" UI and more time on the basics.

To my fellow devs:

Have you found that AI actually shortens your time-to-launch, or does it just make it easier to build "janky" features you don't actually need?

Leave a comment on what you'd like to see in the evolving remote worker ecosystem over the next 10 years.

DEV Community: Kevin G