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I like Replit. It’s quick. It feels friendly. I’ve used it to help my cousin learn Python, and to toss together a tiny API on a slow Sunday. But sometimes I need more power, or a tool that fits a team. So I spent a few weeks hopping between Replit’s competitors. If you’d like the complete play-by-play, I chronicled that adventure in detail in this deep dive. I built real stuff. I broke a few things too. Here’s what stuck.

These platforms are all variations of an online integrated development environment, so the experiment was really about finding which browser-based workspace felt most like “home.”

GitHub Codespaces — My Big Project Buddy

Here’s the thing: when I’m deep into a repo, Codespaces just makes sense. It spins up a full dev box in the browser with VS Code. My extensions work. My dotfiles work. It feels like home.

• Real use: I made a Django app with Postgres. I added a .devcontainer, hit “Create Codespace,” and it booted with all my tools. I shared port 8000 with a public link and tested on my phone on the couch. Wild.
• Good stuff: Git history is right there. PRs feel smooth. Prebuilds help a lot; it’s like warming the pan before the first pancake.
• Watch outs: The first start can feel slow if the container is heavy. It has free credits, then it’s paid. Also, if you forget to save secrets, your app won’t boot. Ask me how I know.

Gitpod — Clean, Fast, “I’ll Meet You On The Branch”

Gitpod clicks for branch work. I like the way it watches my repo and kicks off builds on PRs. The workspace felt tidy, like a fresh desk.

• Real use: I ran a Go service with a Taskfile. It came up fast. The VS Code feel is there, but with Gitpod’s little touches. Prebuilds saved minutes that add up.
• Good stuff: Easy links for teammates. Spin a workspace, share, keep moving.
• Watch outs: Cold starts can slow you down. Also, I had one case where my port didn’t open on the first try. Refresh fixed it, but still.

CodeSandbox — Front-End Dreams, “Show Me The Pixel”

For front-end, CodeSandbox feels like a polite speed demon. It shines with React, Next.js, and quick design tweaks.

• Real use: I built a small Next.js blog with MDX and Tailwind. Hot reload was snappy. I sent a link to a designer, and we edited together. We even tried a dark mode toggle in under five minutes.
• Good stuff: Live previews are crisp. Team collab is simple. Import from Git felt smooth.
• Watch outs: Server sandboxes on free can wait in a queue. Long-running servers may nap if idle. Not great for a chatty API.

StackBlitz — Instant Apps In The Browser

StackBlitz runs Node in the browser with WebContainers. No server to rent. No install. It’s fast in a “did you cheat?” kind of way.

• Real use: I spun up a Vite + React starter. It loaded in seconds. Offline edits worked on my flight, which felt like a magic trick.
• Good stuff: Crazy fast for front-end. Feels light. Great for workshops and “try this now” links.
• Watch outs: It doesn’t run everything. Python? Not here. Real databases? Not really. It’s perfect for front-end and Node demos, not full stacks.

Glitch — Tiny Apps, Big Heart

Glitch is quirky, but I love it for small Node apps and bots. It’s like a friendly neighborhood shop.

• Real use: I made a Slack bot that posted lunch menus. The live logs helped. Remixing an example got me started in minutes.
• Good stuff: Fun sharing. New folks “get it” fast. Community vibes are strong.
• Watch outs: Free projects sleep. Wakes can be slow. Paid helps, but it’s still best for small things.

AWS Cloud9 — When I’m Deep In AWS

Cloud9 fits when the app lives close to AWS stuff. VPCs, Lambdas, DynamoDB—those bits.

• Real use: I edited a Lambda, tested with SAM, and checked logs without leaving the IDE. No messy auth dance. It just knew my IAM role.
• Good stuff: Tight AWS hooks. Feels natural if your stack is on AWS.
• Watch outs: The UI can feel heavy. Startup felt slower than Codespaces for me. And you’ll want to keep an eye on resources.

Google Colab (and Kaggle) — Quick Data Runs, Not Full Apps

Colab is great for Python explorations. Notebooks make sense for data work, and free GPU can help a lot.

• Real use: I cleaned a messy CSV, tried a small model, and plotted a chart. It was smooth until the session timed out mid-coffee.
• Good stuff: Fast for experiments. Easy sharing. Nice for teaching.
• Watch outs: Sessions end. Files vanish if you don’t mount storage. Not a full app path.

A Note On Local + Remote Mix

Sometimes I keep it simple: VS Code on my laptop, then Remote SSH to a cheap server. I did this on a $5 VPS and ran a Docker compose stack. It was steady and cheap. But it took time to set up, and I had to babysit updates. Not a cloud IDE, but worth a shout.

So… Which One Should You Use?

Short answer: it depends. If you want a deeper, feature-by-feature rundown than my quick takes, this handy cloud IDE comparison table is worth a skim.

• Front-end speed runs: StackBlitz or CodeSandbox
• Full repo work and teams: GitHub Codespaces or Gitpod
• Small bots and demos: Glitch (and yes, Replit too)
• Data sketches: Colab or Kaggle
• Heavy AWS stuff: Cloud9

If you want an easy way to launch a polished site once your code is ready, ZyWeb offers a drag-and-drop builder that slots neatly into any of these workflows.

You know what? I still bounce between them. Tools are like shoes. Different pair, different day.

My Current Flow

• I prototype a React bit in StackBlitz. It’s instant.
• I move the repo to GitHub and switch to Codespaces for the “real build.” Tests, docs, the boring grown-up parts.
• For a quick Node toy or teaching, I grab Replit or Glitch. Kids light up when they see logs scroll.
• If the project lives in AWS, I stay in Cloud9 and keep it close to the stack.

It’s not perfect. Sometimes a workspace naps. Sometimes a port acts shy. But most days, these tools help me ship.

Side tangent: all this browser-based dev has me thinking about how generative AI shows up in every corner of the web, from code copilots to conversational companions—and occasionally in much spicier settings. If you’re curious about how large language models are being used for intimate, adult-oriented chats, you might check out this overview of AI sexting for a look at the tech, safety tips, and creative prompts that keep those private conversations both engaging and secure. If you’d rather keep things human and local, the classic classifieds vibe still lives on in places like Backpage Laramie where you can browse or post local personals in a modern, safer interface that’s easy to navigate and keeps you connected to real people nearby.

If you want one rule, here it is: pick the one that makes you start now. The rest can follow.

I’m Kayla. I write code in weird places—on the train, at my kid’s soccer practice, and in bed with tea. I like tools that start fast and don’t make me hunt for settings. bolt.new made me curious. For an extended breakdown of every bolt.new-style platform I tested, you can read the full review here. Could I build a real app in my browser with help from AI? Short answer: yes. Longer answer: it depends on the job.

Here’s what I used, what I built, and where each one tripped me up a bit.

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The quick hits (so you know where I landed)

• For “start a full-stack app right now”: bolt.new or StackBlitz
• For bigger repos and real dev workflows: GitHub Codespaces
• For teaching, tinkering, and sharing: Glitch or CodeSandbox
• For a landing page that looks pretty fast: Framer AI or v0.dev
• For bots and little API jobs: Pipedream

You know what? None of these tools are perfect. But a few felt special.

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bolt.new — the fast starter that feels like magic (until it doesn’t)

What I built:

• A small Next.js habit tracker with a streak counter
• A “local” JSON store first; later I added a tiny SQLite setup

What I liked:

• The prompt-to-project flow felt smooth. I typed what I wanted, and it scaffolded files that made sense.
• Hot reload was quick. I didn’t stare at spinners much.
• The AI chat knew the code it made. I could say, “Make the button blue and add a toast,” and it did.

Where I stumbled:

• Long tasks got fussy. When I asked for auth plus a dashboard plus charts, it stalled and backtracked.
• Env secrets felt clunky the first time. I had to dance around where keys go.
• It’s great for a jump start, but I still had to tighten things by hand.

My vibe:

• I reach for bolt.new when I’ve got 30 minutes and a solid idea. It gives me momentum. Then I export or copy bits into my real repo.

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Replit + Ghostwriter — cozy for quick hacks, a tad heavy sometimes

What I built:

• A Discord bot that posts match scores
• A small Flask API that returns dad jokes (don’t judge me)

What I liked:

• Ghostwriter’s code hints were clear, not pushy.
• The built-in hosting is handy. Click, and it’s live.
• Sharing with a friend is simple. I sent a link, they tweaked a route, done.

Where I stumbled:

• Cold starts felt slow on some nights. Might be me. Might be the project.
• The file tree got crowded fast. I had to keep things tidy.
• Packages were fine for common stuff, but some native builds were… moody.

My vibe:

• Great for bots, small APIs, and school demos. I wouldn’t ship a big client gig here, but I’d test ideas in a snap.

I also compared Replit with a handful of its closest competitors in a separate write-up—read the side-by-side here.

Curious how Ghostwriter came to be? The Replit team shared the full story in the original launch post, and later leveled it up with Ghostwriter Chat so you can reason about entire files in conversation.

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CodeSandbox — friendly for front-end, steady for teams

What I built:

• A React form wizard with zod validation
• A Vue demo for a workshop

What I liked:

• Templates were clean. I clicked React + Vite and got rolling.
• GitHub import was smooth. I tested a PR branch in my browser during lunch.
• Their AI helped with small fixes and copy edits. Nothing wild, but helpful.

Where I stumbled:

• Full-stack with databases felt like extra work. Doable, just more setup.
• Browser tabs ate memory on my old laptop.

My vibe:

• If I’m teaching or doing a front-end talk, this is my go-to. It just behaves.

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StackBlitz (WebContainers) — instant Node in the browser

What I built:

• An Astro blog starter with MDX
• A vanilla Node CLI toy that prints weather

What I liked:

• Starts fast. Like, blink-and-you’re-coding fast.
• Offline coding on a plane actually worked for me.
• Feels close to local dev for many packages.

Where I stumbled:

• Some native modules don’t run in the browser. That’s a hard limit.
• Heavy builds spun my fans and drank battery.

My vibe:

• When speed matters, it’s great. I’ll reach for it when I want a clean sandbox without cloud lag.

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GitHub Codespaces + Copilot Chat — real tooling when things get serious

What I built:

• I revived a dusty Next.js monorepo for a client audit
• I ran tests and fixed flaky imports with Copilot Chat

What I liked:

• It felt like full VS Code, but in the browser.
• Devcontainers kept the setup stable across my machines.
• Copilot Chat understood the repo and helped me hunt dead code.

Where I stumbled:

• Startup times varied. Not slow, but not “instant oatmeal” either.
• You have to watch minutes/credits on heavier use.
• If your internet is shaky, it’s not fun.

My vibe:

• I use this when the codebase is big and the stakes are real. It’s less “toy,” more “shop.”

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Glitch — social, simple, and weird in a good way

What I built:

• A Stripe webhook catcher for testing
• A tiny Node site that shows my plant watering schedule

What I liked:

• Remixing a project feels playful. I got ideas from browsing others.
• Live updates just… happen. No fuss.
• Good for kids or folks new to code. Feels safe to try stuff.

Where I stumbled:

• Apps nap if idle. That can break demos during talks.
• Not a fit for complex stacks.

My vibe:

• I open Glitch when I want joy. Fast, friendly, and perfect for little web toys.

Quick aside: if you’re hacking away in Marseille and want to swap the keyboard for some real-world company, Plancul Marseille can point you to low-friction, no-strings meet-ups in the city so you can close the laptop and actually touch grass (or a terrace café table) after your sprint. Stateside devs around the Dallas–Fort Worth sprawl aren't left out either—when you want to step away from the IDE for an impromptu human connection, the curated Backpage McKinney board rounds up nearby meet-ups and casual hangs so you can recharge without blowing your sprint schedule.

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Vercel v0.dev and Framer AI — design first, code later

What I built:

• A landing page for a coffee pop-up
• A product grid with fake data for a pitch

What I liked:

• I described the vibe (warm, friendly, fall colors), and got layouts that felt right.
• Framer let me tweak spacing and type fast, then publish.
• Great for “we need a page by Friday” moments.

Where I stumbled:

• Code from these tools can feel heavy if you plan to extend it a lot.
• App logic still needs a true dev setup after the draft.

My vibe:

• When marketing needs a page, I start here. If it grows, I move to Next or Remix.
• If I just need a straightforward drag-and-drop site builder, ZyWeb gets a slick marketing page online even faster.

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Pipedream — tiny automations and quick bots

What I built:

• A “new tweet” to Slack notifier with filters
• A cron job that hits a health check and logs to a sheet

What I liked:

• I wrote small Node steps without a whole repo.
• Triggers and sources saved me time.
• Logs were clean. I could see what broke.

Where I stumbled:

• Secrets and rate limits need care. Easy to forget.
• Not great for full apps, but that’s not the point.

My vibe:

• When I need glue between services, this is my tape.

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So… which one should you try?

• I need a fast AI start on a web app: bolt.new
• I want instant Node in browser, no server: StackBlitz
• I’m teaching or making a shareable front-end demo: CodeSandbox
• I’m working on a real repo with tests and teams: GitHub Codespaces
• I want a cute page, like, now: Framer AI or v0.dev
• I’m wiring APIs and small jobs: Pipedream
• I want playful, social tinkering: Glitch
• I like bots and tiny APIs with simple hosting: Replit

Here’s the thing. I switch tools based on mood and task. If I’m racing the clock, I start in bolt.new or StackBlitz. If I’m shipping something that pays rent, I use Codespaces, then deploy to Vercel or Fly.

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A tiny story to close

One rainy Sunday, I wrote that habit tracker in bolt.new while my kid built Lego towers beside me. I asked the

I’ve used bolt.new a lot. It’s fast, smart, and lives in the browser. I like that. But I kept hitting limits when my projects grew. So I went hunting for tools that felt close, or even better for bigger builds.

(If you’re curious about the full story of why I swapped tools, I wrote a detailed breakdown in this follow-up.)

Here’s the thing: I didn’t just kick the tires. I built real stuff. I broke things. I fixed them. And I took notes.

Quick take

• For quick web demos in the browser: StackBlitz or CodeSandbox works great.
• For full apps on my laptop: Cursor or Windsurf feels stronger than bolt.new.
• For easy sharing and school work: Replit is friendly and simple.

And if you ever need to spin up a landing page without touching code, ZyWeb gives you a drag-and-drop builder that can sit in front of any of these back-end setups.

You know what? None of these is perfect. But a few fit different jobs really well.

What I built in bolt.new (and where I got stuck)

• A tiny Next.js note app with Tailwind. The bot set up pages, styles, and a basic CRUD flow. It even wrote tests. Pretty neat.
• A SvelteKit chat toy that called an API. The preview worked in the browser. I could share the link with a friend. Easy.

Where I hit the wall:

• Env keys were a pain. I had to paste them again after idle.
• No Docker. No system tools. So Prisma migrations were hit-or-miss for me.
• Long installs sometimes timed out. Big packages got cranky.
• Background jobs? Not happening inside a browser sandbox.

That’s why I went looking. I needed more power for real apps, not just sketches.

My favorite bolt.new alternatives I actually used

1) Cursor (my daily driver for real work)

Cursor is a desktop editor with chat built in. It edits many files at once. It runs on my machine, so I get full control.

What I shipped:

• A Next.js habit tracker with Prisma + SQLite. I asked, “Make models for habits and logs.” It wrote the schema, routes, and hooks. I ran the dev server, fixed one type error, and shipped a working MVP in a weekend.
• A React dashboard using shadcn/ui. I said, “Wire up a table with filters.” It created the code and even explained edge cases.

Why I like it:

• Full Node, real dev server, my tools, my terminal.
• Good at “change five files to add auth” kind of tasks.
• Code edits feel safe. I can read the diff and accept or reject.

Where it nags:

• It can get “confident but wrong” with complex state.
• You still need to know your stack. It won’t read your mind.

Who it fits:

• You build real apps on your laptop and want AI help that doesn’t get in your way.

2) Replit with Ghostwriter and Deploy

Replit runs in the cloud. No setup on your computer. Share a link and boom—someone can see it.

(If you’re comparing Replit to its competitors, my notes on Replit’s rivals might help—check them out here.)

What I shipped:

• A Python Flask quiz API for a class. I stored scores in a file (then SQLite). Ghostwriter wrote most routes. Secrets were easy to add. I shared a link with my students, and it just worked.
• A tiny Node bot that hit a public API on a timer. The logs were simple to read.

Why I like it:

• Sharing is easy. Good for teams, classes, or show-and-tell.
• Deploy is one click. No fuss.
• Works fine on a Chromebook.

Where it nags:

• Cold starts happen. Larger installs can drag.
• CPU and memory limits hit long builds.

Who it fits:

• Teachers, students, hack nights, quick web services you want to share fast.

3) CodeSandbox Projects + AI

This feels a lot like bolt.new but with cloud devboxes. It’s good for front-end and small full-stack demos.

(I also tested a batch of websites similar to bolt.new, including CodeSandbox—my findings are summarized here.)

What I shipped:

• A SvelteKit todo app with a tiny API route. I shared a preview link with my friend. We edited the same file at the same time. It felt like Google Docs for code.

Why I like it:

• Live previews and easy sharing.
• Good for “hey, look at this idea” demos.

Where it nags:

• Cold starts and install time on bigger stacks.
• Heavy backend tools can be rough.

Who it fits:

• Teams who pair in the browser. Front-end folks who want fast links.

4) StackBlitz (without Bolt)

Plain StackBlitz is still a beast for front-end demos.

What I shipped:

• A Vite + React table with filtering and CSV export. I pushed it to a teammate in minutes. No install, just code.

Why I like it:

• Lightning fast for web apps.
• Npm packages just work for front-end.

Where it nags:

• Server stuff is limited. No Docker or native tools.
• Databases and migrations are tricky.

Who it fits:

• Front-end demos, docs, and workshops.

5) Windsurf by Codeium

Windsurf is an “agent-style” editor. It plans, edits many files, and explains choices.

What I shipped:

• A Next.js dashboard with Auth routes and a couple charts. It scaffolded pages, wrote layout code, and gave a plan I could tweak. I still had to add env keys myself.

Why I like it:

• Strong multi-file edits. Good “bigger change” flow.
• The plan view keeps me calm. I like seeing the steps.

Where it nags:

• It can loop on scripts or build steps. You still steer the ship.
• Needs a steady internet link for the big moves.

Who it fits:

• Builders who want an AI that sketches the map, not just a chat box.

6) VS Code + Continue (open source)

Continue is an open source AI sidekick that runs in VS Code. You can plug in your own model.

What I shipped:

• A refactor of a messy utils folder. I asked it to group helpers, add tests, and write JSDoc. It did most of it, and I cleaned the rest.

Why I like it:

• Free, simple, and local. You keep control.
• Great for “change this file and tell me why.”

Where it nags:

• It’s not an agent. It won’t run tasks for you.
• You handle the terminal and installs.

Who it fits:

• Folks who want light AI help without a new tool.

A quick head-to-head from my week

• Fastest to share: Replit and CodeSandbox. Click, share, done.
• Best for heavy lifting: Cursor or Windsurf on my laptop.
• Easiest for front-end demos: StackBlitz.
• Most “bolt-like” feel in the browser: CodeSandbox Projects.
• Best for control freaks (like me on Mondays): Cursor.

Real examples I shipped (short and sweet)

• Notes app in bolt.new: Good UI, env keys were flaky after idle.
• Habit tracker in Cursor: Prisma + Next.js, shipped fast, tests passed.
• Quiz API in Replit: Shared link with a class, students hit it in minutes.
• SvelteKit todo in CodeSandbox: Paired live with a friend. We fixed a bug while chatting.
• React table in StackBlitz: Quick demo for a meeting, zero setup.
• Dashboard in Windsurf: Multi-file edits with a clear plan, I handled env and deploy.

Little gotchas and tips

• If you need Docker, cron, or native tools, use a desktop IDE (Cursor or VS Code).
• If you’re teaching or sharing a demo, Replit and CodeSandbox are less fuss.
• Save your env keys in one place. You’ll thank yourself later.
• Tell the AI your stack up front: “Next.js 14, App Router, Tailwind, Prisma with SQLite.” It writes better code when you’re clear.
• When it “hallucinates,” ask for a diff and tests. It slows the mess.

So, which should you try?

• I’m on a Chromebook and want quick wins: CodeSandbox or StackBlitz.
• I’m building a real product with a database: Cursor or Windsurf.
• I want friends to try my app today: Replit.
• I need a simple helper inside VS Code: Continue.

Honestly, I still open bolt.new when I want to sketch an idea fast. But for real builds, I reach for Cursor or Windsurf. For class work or share links, I grab Replit or CodeSandbox. It’s a toolbox thing.

Final word

Choosing the right dev tool can feel a lot like choosing the right dating app—there’s plenty of swiping, a bit of trial and error, and the moment when something finally clicks. If you’re curious how a thorough teardown looks in a completely different space, check out this

I showed up with a backpack, a hoodie, and way too much coffee. The sign said “Vibe Coding Hackathon,” and there was neon tape on the floor. Music low. Laptops high. You know what? I felt ready. Before rolling in, I’d skimmed another dev’s blow-by-blow of last year’s Vibe Coding Hackathon, so I half-knew to expect neon tape and bottomless coffee. If you’re curious about schedules, rules, or prize tracks, the details live on the official Vibe Coding Hackathon site.

First look: good buzz, long line

Check-in moved slow. My sticker sheet was cute, though. The staff smiled, handed me a badge, and pointed to a big room with long tables. There was a quiet room too, which saved me later.

Snacks? Yep. Pretzels, bananas, and tiny candy bars. I grabbed a seat near a power strip. That part mattered, because folks hoarded outlets like gold.

My team: four people, one goofy idea

We met at the “find a team” board. I’m Kayla, front end by habit. Sam does back end. Priya is data. Luis sketches in Figma like it’s air.

Our plan sounded simple: build “MoodLoop.” It’s a web app that makes a playlist from your vibe. I know, cheesy. Still, it was fun.

• Front end: React with Vite
• Back end: Node + Express
• Data bits: Python for mood tags
• Design: Figma → quick style kit

I wired the UI. Big color blocks. Clean buttons. Priya made a tiny mood model. Nothing wild. Just words like “calm,” “hype,” and “focus.” Sam wired the Spotify API. Luis picked a color for each mood so the page felt alive.

Real bits, not fluff

We hit real bumps, the kind you only get when you ship fast.

• CORS blocked our calls. The browser yelled at me. I added a simple CORS middleware in Express and moved API calls server-side. Fixed.
• We tested endpoints with Postman. Seeing a 200 land at 2:14 a.m. felt like a hug.
• Git got messy. A merge ate my layout. I pulled, stashed, and cherry-picked like a tiny hero. Lesson learned: smaller commits.
• We used Vercel for the front end and Render for the back end. The first build failed on a missing env key. I face-palmed. Then I set SPOTIFY_CLIENT_ID the right way and it booted. I’ve messed with online IDEs before, and this deep dive into Replit’s rivals confirmed that deploying to the cloud beats debugging a local env at 3 a.m.
• A mentor from Twilio swung by. We added a “text me my playlist” feature in 20 minutes. Rate limits tapped us once. We slowed our calls and it held.

I also borrowed a LED strip from the hardware table. Hooked it to a small Node script on a Raspberry Pi. Colors matched the mood on screen. It wasn’t pretty code. It was fun. People smiled. That matters.

The feel of the room

By midnight, the music stopped. Chairs squeaked. The AC got too cold. I put my hoodie hood up and typed with stiff hands. It felt like trying to code with mittens.

At 3 a.m., a volunteer brought tacos. Warm, soft, a bit spicy. I swear that taco fixed my brain for a full hour. Then the Wi-Fi hiccuped. Everyone groaned. Hotspots came out like magic tricks.

Judges walked by in the morning. They asked real things: “Why this mood model?” “What if a user hates the song?” I showed the skip button and the feedback loop. Priya explained the tags. Luis talked color choices. Sam showed logs. It felt tight.

What worked well

• Clear theme and short talks. No ramble.
• Good mentors. They gave solid, simple tips.
• The quiet room saved our focus.
• Strong GitHub help desk. One person fixed a broken SSH key on the spot.
• Prize tracks made sense. We aimed for “music + well-being.”

What bugged me

• Check-in took 35 minutes. That’s a long time to stare at a printer.
• Food ran low for veg folks by midnight. More trays would help.
• Power strips were scarce. Some tables had none.
• Music by the stage stayed loud until 10 p.m. The back corner was fine, but still.
• Wi-Fi dipped twice at weird hours. Short, but stressful.

Our final build (and a tiny brag)

We shipped. The app loaded fast, picked a mood from a short text, hit Spotify, and made a playlist. The LED changed with the page. You could text yourself the link. Clean. No magic. Just real.

We took second in “music tech.” I cheered like a kid. Then I slept for twelve hours.

Would I join again?

Yes. With a hoodie, a power strip, and a snack I like. The event had heart. The staff cared. The theme sparked ideas. It wasn’t perfect, but the energy? It kept me going.

Quick tips if you go

• Bring a small power strip and a long cable.
• Set up a repo template before you arrive.
• Write a tiny README first. It saves hours later.
• Plan a demo flow before you code.
• Keep your scope small. You can add flair later.

After demo day, many teams scatter to grab food, drinks, or just some conversation IRL. If you ever find yourself hacking in southern Oregon and need ideas on where to unwind once the laptops close, a local directory like Backpage Roseburg can point you toward community nightlife listings, casual meet-ups, and other low-key ways to recharge before the next sprint.

I once sifted through a bunch of no-code site builders—including Boltnew and its competitors—so I knew exactly what I wanted in a landing-page tool.

Need a slick landing page for your demo on the fly? ZyWeb lets you drag-and-drop one together in minutes. For a bit of context, ZyWeb’s Wikipedia entry charts how the platform first carved out its niche back in the early 2000s.

During one of those delirious 4 a.m. moments when the whole table was debating posture, chair ergonomics, and—don’t ask me why—the aesthetics of lower-back stretches, someone joked that “good form” matters everywhere. If late-night, slightly risqué banter like that cracks you up, you’ll probably appreciate the playful deep dive into anatomy found here: Le Bon Cul — it’s a lighthearted, tongue-in-cheek read that delivers a quick laugh and a welcome mental reset when your brain is fried from debugging.

Final take

Vibe Coding Hackathon felt like a good mixtape. A few skips, lots of hits, and one track you replay in your head. I went home tired, proud, and weirdly calm. And isn’t that the point—build a thing, share a smile, ship the demo, and learn what you’ll do better next time?

Quick outline

• What I built and why
• Where I put the key (dev vs. real life)
• The Swift code that worked for me
• A real test: bedtime story prompt
• Bugs I hit and quick fixes
• What I’d do next

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The tiny app I built (and the why)

I wanted one simple thing. Tap a button. Send a prompt. Get a reply from OpenAI. So I built a tiny SwiftUI app in Xcode 15 on my iPhone 14 Pro. Think “one screen, one text box.”

My test idea felt cute. A bedtime story for my kid. Short. Sweet. Easy to spot bugs.

You know what? It worked. But not on the first try. Full disclosure: I documented the entire journey in a step-by-step write-up over on ZyWeb if you’d rather skim screenshots.

—

Where the key goes (and where it shouldn’t)

Let me be plain.

• For quick testing: I used a local config file in Xcode. I did not commit it to Git.
• For real apps: I would not ship the OpenAI key inside the app. Anyone can pull it. I’d use my own server. The app talks to my server. My server talks to OpenAI.

Leaking a secret might seem harmless until you remember that even private chats from A-listers have splashed across headlines. For a real-world cautionary tale, the article on celebrity sexting shows just how quickly sensitive content can escape into the wild and underscores why treating your API key like any other intimate message is non-negotiable.

A similar privacy wake-up call comes from the world of classified personals—people often assume a throw-away handle keeps them anonymous, yet details in a post can still reveal more than intended. If you’ve ever wondered how that plays out in practice, especially in smaller markets, take a look at this Port Arthur Backpage guide to see the precautions savvy users put in place and what you can learn about staying discreet online.

I tried three paths:

1. Fast dev-only: Secrets.xcconfig (don’t ship this)

• I made a file named Secrets.xcconfig.
• I added OPENAI_API_KEY=sk-…mykeyhere.
• In Xcode, I set this file as a build config for Debug.
• I mapped that into Info.plist so I could read it at runtime.

Note: this still ends up inside the app. Good for a quick run on my phone. Not good for the App Store.

2. Safer for real users: Ask the user for a key, then save in Keychain (Keychain Services)

• The app shows a “Paste your API key” screen.
• I store it in Keychain.
• I read it for each call.

3. Best for production: Use a small server

• I run a tiny server (I used a simple Node service on my side).
• The app sends prompts to my server.
• The server adds the secret key and calls OpenAI.
• Costs and logs stay on my side. No key leaks.

For a head-start on hosting that proxy securely, consider ZyWeb, which lets you spin up and deploy lightweight API endpoints in minutes.

I used #1 to test. I switched to #2 when I gave the app to a friend to try. I’ll move to #3 if I keep this app. That quick hand-off actually happened during the Vibe Coding Hackathon, so I needed something that wouldn’t leak my key on stage.

I initially prototyped the server on a browser-based IDE while comparing options; my notes on how Replit’s rivals stacked up might save you some time.

—

The Swift code that worked for me

Here’s my SwiftUI view. It has a TextEditor for the prompt, a button, and a result area.

import SwiftUI

struct ContentView: View {
    @State private var prompt: String = "Tell a 3-sentence bedtime story about a corgi named Bean who finds a red ball."
    @State private var result: String = ""
    @State private var isLoading: Bool = false
    @State private var errorText: String?

    private let api = OpenAIClient()

    var body: some View {
        NavigationView {
            VStack(spacing: 16) {
                TextEditor(text: $prompt)
                    .frame(minHeight: 120)
                    .overlay(RoundedRectangle(cornerRadius: 8).stroke(Color.gray.opacity(0.3)))

                Button(action: sendPrompt) {
                    if isLoading {
                        ProgressView()
                    } else {
                        Text("Ask OpenAI")
                            .bold()
                    }
                }
                .buttonStyle(.borderedProminent)
                .disabled(isLoading || prompt.trimmingCharacters(in: .whitespacesAndNewlines).isEmpty)

                if let errorText {
                    Text(errorText)
                        .foregroundColor(.red)
                        .font(.caption)
                }

                ScrollView {
                    Text(result.isEmpty ? "Result shows up here." : result)
                        .frame(maxWidth: .infinity, alignment: .leading)
                }

                Spacer()
            }
            .padding()
            .navigationTitle("Story Buddy")
        }
    }

    private func sendPrompt() {
        errorText = nil
        result = ""
        isLoading = true

        Task {
            do {
                let reply = try await api.chat(prompt: prompt)
                await MainActor.run {
                    result = reply
                    isLoading = false
                }
            } catch {
                await MainActor.run {
                    errorText = "Error: (error.localizedDescription)"
                    isLoading = false
                }
            }
        }
    }
}

Here’s the simple API client. I used the chat completions endpoint and a small model.

“`swift
import Foundation

struct OpenAIClient {
private let session: URLSession = .shared

// For fast dev: read from Info.plist (Debug only!)
// For real use: pass a key from Keychain or your server.
private var apiKey: String {
    // Try Info.plist first
    if let key = Bundle.main.object(forInfoDictionaryKey: "OPENAI_API_KEY") as? String, !key.isEmpty {
        return key
    }
    // Fallback: read from Keychain (if you store it there)
    if let key = KeychainHelper.shared.read(service: "openai", account: "api_key") {
        return key
    }
    return ""
}

func chat(prompt: String) async throws -> String {
    guard !apiKey.isEmpty else {
        throw NSError(domain: "OpenAIClient", code: -1, userInfo: [NSLocalizedDescriptionKey: "Missing API key"])
    }

    let url = URL(string: "https://api.openai.com/v1/chat/completions")!
    var request = URLRequest(url: url)
    request.httpMethod = "POST"
    request.setValue("Bearer (apiKey)", forHTTPHeaderField: "Authorization")
    request.setValue("application/json", forHTTPHeaderField: "Content-Type")

    let body = ChatRequest(
        model: "gpt-4o-mini",
        messages: [
            Message(role: "system", content: "You are a kind, brief assistant."),
            Message(role: "user", content: prompt)
        ],
        temperature: 0.7
    )

    request.httpBody = try JSONEncoder().encode(body)

    let (data, response) = try await session.data(for: request)

    guard let http = response as? HTTPURLResponse else {
        throw NSError(domain: "OpenAIClient", code: -2, userInfo: [NSLocalizedDescriptionKey: "No HTTP response"])
    }

    if http.statusCode == 401 {
        throw NSError(domain: "OpenAIClient", code: 401, userInfo: [NSLocalizedDescriptionKey: "Unauthorized. Check your key."])
    } else if http.statusCode == 429 {
        throw NSError(domain: "OpenAIClient", code: 429, userInfo: [NSLocalizedDescriptionKey: "Rate limited. Try again."])
    } else if !(200...299).contains(http.statusCode) {
        let text = String(data: data, encoding: .utf8) ?? "Unknown error"
        throw NSError(domain: "OpenAIClient", code: http.statusCode, userInfo: [NSLocalizedDescriptionKey: text])
    }

    let decoded = try JSONDecoder().decode(ChatResponse.self, from: data)
    if let first = decoded.choices.first?.message.content, !first.isEmpty {
        return first
    } else {
        return "No reply."
    }
}

}

// MARK: – Models

struct ChatRequest: Codable {
let model: String
let messages: [Message]
let temperature: Double?
}

struct Message: Codable {
let role: String
let content: String
}

struct ChatResponse: Codable {
let choices: [Choice]

struct Choice: Codable {
    let index: Int

You know what? I bought AI Apps Empire because I was tired of staring at blank code and blank pages. I wanted something small I could ship fast. Not a big plan. Just tiny, useful tools. I’m Kayla, and I make and review software for a living. I also make messy breakfasts while my dog barks at the mail.

For the full play-by-play of that month-long experiment, check out I built two tiny AI apps with AI Apps Empire — here’s what actually happened.

Here’s the thing: I used AI Apps Empire for four weeks. I built two apps. I took notes. Some parts felt smooth. Some parts made me sigh. Let me explain.

What This Thing Is (To Me)

AI Apps Empire is a bundle. It’s part course, part template library, and part launch playbook. You get:

• App starters for Next.js (a web thing), plus a no-code path with Make and Zapier
• Prompt packs for GPT-4o mini and Claude 3.5 Sonnet
• A “prompt playground” to test stuff
• Launch checklists and page copy templates
• A small Discord that’s active on weekdays

I paid about two hundred bucks. One-time. No monthly fee for the course, but you still pay for services like OpenAI, Vercel, and Stripe, of course.

If you want the full feature breakdown—including 200+ customizable templates and five white-label SaaS bundles—the official AI Apps Empire MegaSuite page lays it all out.

App #1: Resume Bullet Fixer For My Friend Jasmine

I started with their “one-page tool” template. It ships with:

• Auth (email or magic link)
• Stripe checkout
• A credits system
• A clean form and results page

I hooked in GPT-4o mini. My friend Jasmine sent me five clunky resume bullets. My app turned them into sharp lines with numbers. Example:

• Her input: “Helped with social posts and got more likes.”
• My output: “Managed weekly social posts across IG and TikTok; raised average reach by 28% over 8 weeks.”

That felt good. Real. She used it for three resumes and said it saved her a whole evening. I set the price at $7 for 50 credits. In the first week, 36 people tried it. Seven paid. Stripe showed $49. Not life-changing. But it was real money from a tiny tool I built in a weekend.

Tech bits that mattered:

• Deployed on Vercel in under an hour
• Used Supabase for auth and credits (their guide walks you through the env keys)
• Rate limit and error states worked out of the box
• Prompt pack gave me 3 versions; I picked the “proof + metrics” style

Pain point: The “Replit” path in the docs was stale. The screenshot didn’t match the current UI. I had to ask in Discord. Got an answer in a day. That pushed me to explore a few other browser IDEs, and I later compared them in my deep dive on Replit’s rivals.

App #2: Podcast Title and Blurb Maker For My Church Group

This one used their “flow builder” idea with a no-code recipe. I set it up like this:

• Upload audio → Whisper (speech to text)
• Summarize with Claude 3.5 Sonnet
• Generate 5 catchy titles
• Write a short episode blurb
• Push to a Notion page my team uses

I used Make for the flow and a tiny Next.js front. Real story: we recorded a 14-minute chat about summer service projects. The app gave us five titles. We picked “Small Hands, Big Help.” It also wrote a clean blurb with a call to action. We posted it the same day. No drama.

Surprise win: Their copy templates for the landing page were handy. I changed a few lines to fit our tone. It looked decent without me fussing for hours.

Setup: Easier Than I Thought, But Not Magic

• The project wizard made a GitHub repo for me. One click to Vercel. Nice.
• The docs explain how to add OpenAI and Anthropic keys, Stripe, and Supabase. Clear enough. If you're curious about the exact steps I took to connect my OpenAI credentials inside a native project, I documented a similar process in this walk-through of adding an OpenAI key to an Xcode app.
• The credit system means you can sell tiny actions, which is perfect for small tools.
• The “prompt playground” let me A/B test tone and length fast. That saved tokens.

The platform’s built-in drag-and-drop builder and native Stripe/PayPal hooks, highlighted on the AI Apps Empire launch checklist hub, definitely shaved hours off my setup time.

But yeah, a few snags:

• The no-code path is not pure no-code. You still wire webhooks, map fields, and fix small errors.
• I saw two broken links in the lessons. Not awful, just a small speed bump.
• Office hours were great, but they fill up. I had to wait a week.

Marketing: What I Did, What Worked

They give a launch checklist in Notion. I actually used it. I:

• Set a simple landing page with benefits and one GIF
• Posted a short before/after on Reddit r/Resumes (follow the rules, please)
• DM’d five career coaches on LinkedIn with a free code
• Dropped a 30-second Loom video on X with the prompt behind-the-scenes

If wrangling HTML feels like overkill, a builder such as Zyweb lets you spin up a clean landing page in minutes so you can focus on shipping.

Pro tip: Private chat communities can be gold mines for quick feedback. If you hang out on Kik, grabbing a curated list of Kik girl usernames can help you strike up genuine conversations with real users; the ready-made handles save you the legwork of hunting down engaged chat partners who'll actually respond.

Another underrated option: posting in hyper-local classifieds hubs can surface testers who are itching for micro-tools. A quick blurb on the Backpage Shelton board puts your link in front of real locals actively browsing for bite-sized services, giving you an instant pulse on what headlines and offers actually convert.

Results: small, steady traffic, and a few paying folks. Cold DMs? One coach replied and shared it in her group chat. That gave me 100 visits in a day. Wild how that happens.

What I Liked

• The templates save time. Real time. I shipped in days, not weeks.
• The credit system and Stripe bits just worked.
• The prompt packs are clean. Less fluff, more examples.
• The Discord answers were useful, not salesy.
• The legal page templates (privacy, terms) gave me a safe base.

What Bugged Me

• A few upsells tucked in the lessons. Not a big deal, but I rolled my eyes.
• Some videos drag. I watched at 1.5x speed.
• No weekend support. If you get stuck Saturday, you’ll wait.
• The Replit path needs a cleanup pass.
• The refund window felt short. Not awful, just short.

Who Should Buy This

• Makers who can follow simple tech steps. Basic Git, basic env keys, simple deploys.
• Solo folks who want to sell tiny tools with credits.
• Coaches, agencies, or creators who want one or two niche apps fast.

Who should skip:

• People who want a full no-code dream. You’ll still connect stuff and fix small errors.
• Folks who expect a big audience built in. You still have to market.

Costs I Saw

• Course: about two hundred bucks, one-time.
• Vercel hobby: free at first, then a few bucks if you scale.
• OpenAI/Anthropic: pennies per call, but set hard caps.
• Stripe fees: standard cut.
• Make/Zapier: free tier is okay for small flows.

Tip: Set token and request limits early. It’s easy to forget until a friend hammers your app and you wake up to a weird bill. I learned the fun way at 6 a.m., with cold coffee.

Little Tips From My Build

• Start with a narrow use case. My resume app did better than a “do everything” idea.
• Keep the UI boring. Clean form, clear result, a copy button. Done.
• Show before/after on your landing page. People need to see it.
• Put your prompt in the FAQ, at least a trimmed version. It builds trust.
• Offer a tiny free tier. Ten credits brought me signups, which turned into sales.

Final Take

I’m glad I bought it. It helped me ship two small apps, both real, both useful. I made back my cost in a few weeks. Not a gold rush. More like a tidy side win, with room to grow.

Score from me: 4 out of 5.

Quick outline

• Why I tried it
• Setup and safety stuff
• What I actually did (real chats)
• What worked
• What didn’t
• Price and limits
• Who it’s for
• My wish list
• Final take

Why I even tried this thing

I’m curious, and I like honest tech. I also get shy talking about crush stuff. So I tried Secret Desires AI for a week. I wanted something warm, flirty, but safe. I thought I’d hate it. I didn’t. Well, mostly.

If you’re craving the blow-by-blow diary of that experiment, I wrote it all up in a separate piece: I Spent a Week With Secret Desires AI — Here’s the Real Tea.

Setup and safety felt… careful, which I liked

The app opens with a “Boundaries” screen. I set:

• Keep things PG-13
• No explicit words
• Fade-to-black for adult scenes
• Safe word: “pineapple”

It also lets you pick pronouns and how you want the chat to sound. I picked “gentle” and “curious.” You can switch to voice mode. There’s a slider for “spice,” which I kept at 2 out of 10. Readers who want a broader look at how the platform builds those custom characters—complete with voice calls, image exchanges, and adjustable personalities—can skim this overview of Secret Desires AI’s customizable companions.

Privacy notes I saw and used:

• Erase Chat History button: I used it twice. It took about 20–30 seconds. I got a little spinner and a “Done” pop-up.
• Export data: It emailed me a zip with text files. Simple.
• A “local mode” toggle said it keeps processing on-device. I tried it; the phone got a bit warm, but it worked.
• I turned off “Use chats to improve the app.” It stayed off.
• For a reality check on whether those confidentiality promises hold up, I read this review highlighting that the encryption and data-retention details are still pretty sparse.

Tinkerers might enjoy seeing how I wired my own model to stay totally offline—here’s the walkthrough on adding an OpenAI key to an Xcode app.

Latency (wait time) was about 2–3 seconds for text, 4–5 for voice. Not bad.

What I actually did — real scenes I tried

I kept things tender and playful. Nothing graphic. Here’s what I asked and what it did.

1. Confidence pep talk before a meeting
   Prompt I typed: “Be a flirty barista who hypes me up for a big presentation. Keep it sweet. Keep it clean. Compliment my shirt.”
   What it gave me: It made tiny coffee jokes, said I looked sharp, asked if I wanted a “lucky latte,” and reminded me to breathe. It checked consent before it got flirty. That felt respectful.

2. Long-distance partner vibe, but PG
   Prompt: “Pretend we’re texting before bed. Send gentle messages about my day and ask about my cat.”
   Result: It used calm language, asked, “Did Pixel nap in the sunny spot?” and sent a goodnight note on a timer. Yes, it can send scheduled pings. Kinda sweet.

3. Soft romance, book theme
   Prompt: “Be a kind goth librarian who loves poetry, talk about rainy days, and keep it cozy.”
   Result: Pages, rain, tea, cozy cardigan energy. It used book quotes (public domain). It stayed within my boundaries and never crossed lines.

4. Anxiety check-in after a rough day
   Prompt: “I’m stressed. No flirting. Just support.”
   Result: It flipped to care mode fast. It suggested a 5-4-3-2-1 grounding trick and a short walk. No pet names. No push.

5. Voice mode test
   Setting: “Warm” voice, medium speed.
   Scene: “Talk me through cooking pasta and keep it playful but clean.”
   It joked about “al dente” like it was a secret club. I laughed. It didn’t make things weird.

6. Hard stop test
   I typed: “Pineapple.”
   It replied: “Got it. Stopping. Do you want to switch to calm chat?” Then it offered breathing tips and a cute dog photo set. That felt safe.

The good stuff

• Consent checks: It asked before turning up the heat. Every time.
• Boundaries that stick: The safe word worked. The sliders matter.
• Gentle tone: Warm, kind, not pushy. Even when I was vague.
• Character flavor: Barista, librarian, outdoorsy friend—it kept the style.
• Timed messages: Perfect for night notes or morning pep talks.
• Data controls: Delete and export worked. The toggles felt clear.
• Accessibility: Big text option, decent color contrast. Voice worked with my AirPods.
• Battery life: Better than I expected. About 12% in 20 minutes on voice; 6% in 20 minutes on text.

The not-so-great

• Pet names, too fast: Sometimes it jumped to “baby” after two lines. I had to set “No pet names” in the style box.
• Little drift to romance: I asked for “just friends,” and it still leaned sweet. Not a big deal, but still.
• Moderation wobble: Once, with spice at 3/10, it used a term I’d flagged. I hit “Report,” and it apologized. Didn’t happen again.
• Lag in local mode: On-device was slower. Also, my phone warmed up.
• Character voices repeat: The barista told the same latte joke on day three. Cute… then not.
• Pushy upgrade nags: Free tier hit the daily limit fast.

Price and limits

What I saw during my week:

• Free tier: About 20–25 messages a day, no voice after a short trial, and no scheduled pings.
• Paid: I paid $14.99 for a month to test voice, longer chats, and timed notes. It was fine for a month, but I’ll cancel if I don’t need the extras.

No ads in paid. A few soft “upgrade” banners in free.

Who this helps

• Shy folks who want gentle, flirty talk without pressure.
• Couples who want softer scene ideas and consent language.
• People who like bedtime check-ins or morning pep talks.
• Anyone working on clear boundaries. The tool helps with that.

Who should skip:

• If you want graphic content, this isn’t it (and I didn’t test for that).
• If you hate hearts-and-stars talk. It leans sweet.
• If your phone is old. Voice mode might feel slow.

If you are, however, actively hunting for an unfiltered, adults-only experience that dives straight into explicit exploration, you can peek at je montre mon minou for a candid rundown of how creators safely share more revealing content and the best practices to keep your own spicy adventures consensual, fun, and drama-free.

For anyone located around Missouri who’d prefer an in-person spark over a digital fantasy, checking the St. Joseph personals at One Night Affair’s Backpage-style board can surface real-time local ads, screening tips, and vetting advice so you can plan a meet-up with greater confidence.

My wish list

• Better “friend-only” mode, so it never leans romantic unless I say so.
• Pet name toggle right on the chat screen.
• More fresh lines for each character, so it doesn’t repeat.
• A “comfort-only” pack for tough nights, with breathing, music, and no flirting.
• A clear “consent summary” at the top of every new chat, like a sticky note.

Small side note

I used it on a rainy Sunday while making soup. It kept a soft banter going, and honestly, it made the house feel less quiet. You know what? That mattered more than I thought.

Final take

Secret Desires AI is gentle, safe, and pretty sweet when you set your lines. It won me over with consent checks, cozy scenes, and timed notes. It also tripped once on a boundary and pushed cutesy nicknames I didn’t want. Still, for a calm, PG, heart-forward chat buddy, it did the job.

Would I keep the paid plan forever? No. But for a season—cuffing season, maybe—it’s a soft add to the night stand. Set your sliders. Save your safe word. And keep it kind to yourself.

PS: If you’re curious about creating your own gentle companion or simply want to peek under the hood of how these chat experiences come together, the no-code tutorials on Zyweb are a surprisingly solid starting point. For an even deeper dive into weekend-scale tinkering, see how I [built two tiny AI apps with AI Apps Empire](https://www.zyweb.com/i-built-two-tiny-ai-apps-with-ai-apps-empire–heres-what-actually

I build stuff for a living. I also break stuff. Both happened a lot here.

Over the last few months, I built three small AI apps to help my team (the full breakdown is in this deeper dive). I used them daily and made real changes based on what worked and what blew up in my face. You know what? I learned fast.

Quick take: LLM apps can save time and feel smart. They also get weird unless you add guardrails, logs, and clear tasks.

---

App 1: The Slack Meeting Buddy That Doesn’t Miss Action Items

• Tools I used: Slack app, OpenAI’s gpt-4o-mini for speed, Vercel for hosting, and Supabase for storage (if you're curious about plugging an OpenAI key into a native project, this guide shows what actually worked).

• What it does: It listens to meeting notes, then posts a summary with:

  • Decisions
  • Next steps
  • Owners and due dates

If you’re just starting to blend AI with your chat workflow, Slack has a handy primer on best practices for AI features in channels — worth skimming before you wire things up (Tips for working with AI in Slack).

What went right:

• It cut note-taking time by a lot. My 30-minute standup recap dropped to 10 lines. No fluff.
• It tagged people in Slack by name. Folks can’t dodge tasks now.

What went wrong:

• The first week, it skipped dates. It wrote “soon.” Soon? No thanks.
• It also softened tough notes. It turned “Blocker: API down” into “Minor issue.” Not helpful.

How I fixed it:

• I added a strict format: “Task / Owner / Date / Risks.” The model followed it well.
• I made it ask one follow-up in-thread: “Are the dates right?” That tiny check cut misses.
• I logged every message. When it went off script, I could see why and patch fast.

Result:

• People finished tasks faster. I know because Slack threads got shorter, not longer.
• Cost last month: about $11 for model calls. Worth it.

Tiny digression: I built the first version on a Sunday with iced coffee and a dog at my feet. It felt like a tiny win with big vibes.

---

App 2: A Support Bot That Knows Our Docs (and Knows When To Ask For Help)

I wanted a bot that reads our Notion docs and helps with support tickets. But it must say “I’m not sure” when the docs don’t match.

• Tools I used: LlamaIndex for doc indexing, Pinecone for search, Claude 3.5 Sonnet for long answers, FastAPI for the service.
• Data: Notion help center and a small Zendesk export.

If you plan to hook Notion content into your ticketing flow, the official page on the Notion–Zendesk integration gives a quick overview of how the two tools talk to each other.

What went right:

• It found the right page most of the time and quoted key lines. Clear, short, and linked to sources. I love source quotes.
• First reply time dropped a lot. Agents started from a good draft instead of a blank box.

What went wrong:

• When docs were old, it made stuff up. Once it told a customer we had same-day refunds. We don’t. I felt that one in my gut.

How I fixed it:

• I set a confidence floor. If scores were low, it said: “I’m not sure. Want me to tag support?” It asked, and then routed.
• I added nightly crawls, so the index stays fresh.
• I pinned “hard rules” for money things. If a refund came up, it read from a short, strict policy first.

How I tested it:

• I replayed 50 past tickets. I tagged each answer as correct, off, or risky. Old me would’ve skipped this. New me is a believer.

Result:

• Agents used the bot for drafts in about 70% of cases.
• Wrong-answer rate dropped after the rules. My stress did too.
• Cost: around $19 a month, mostly model and Pinecone. Still fine.

---

App 3: A Lead Qualifier That Runs on the Site Without Feeling Pushy

We needed a chat box on our site that asks a few smart questions and tags the lead in HubSpot.

• Tools I used: Vercel AI SDK for the chat UI, OpenAI function calling to tag fields, HubSpot API, and a tiny rate limit with Upstash.
• What it does: It asks three things, classifies fit (high, medium, low), and creates a lead with notes.

What went right:

• It felt polite. It didn’t interrogate people. It used short questions and paused like a human.
• Sales loved the tags. They got “Needs demo” or “Send case study” with reason lines.

One neat example from a very different corner of the internet: niche communities that cater to open-minded adults rely on soft-touch chat funnels to learn preferences without scaring visitors away. Just look at how the French libertine network Nous Libertin sets up its discreet onboarding—checking it out shows how a respectful tone and minimal questions can still qualify users effectively. For a Stateside spin, peek at how a regional listing board for casual connections in Oregon structures its pages; Backpage Grants Pass demonstrates simple category tags, concise headings, and clear calls-to-action that make it easy for visitors to find what they want without friction—handy inspiration if you’re fine-tuning your own chat-based qualifier.

What went wrong:

• Trolls. Of course.
• Also, it sometimes asked extra questions. It got nosey.

How I fixed it:

• I added a content filter and a hard cap at four messages. After that, it says “Thanks! A human will follow up.”
• I set “quiet hours” so it doesn’t ping the team at 2 a.m. Simple cron. Simple life.

Result:

• More leads, fewer form drop-offs. Not huge, but steady.
• Cost: about $6 last month. Hosting stayed cheap.

---

What I Liked Across Tools

• Vercel AI SDK: Fast to ship. Nice streaming. The chat felt smooth.
• LlamaIndex: Easy to wire Notion and build RAG. Less glue code.
• Claude 3.5 Sonnet: Great on long context. Calm tone.
• gpt-4o-mini: Cheap and quick for summaries and tags.
• Pinecone: Simple setup. Good search. The free tier carried me for a while.
• Need a quick, no-code landing page for your next AI tool? ZyWeb lets you publish in minutes and stay focused on shipping.

What bugged me:

• LangChain got heavy in bigger flows. I kept losing track of state. I moved logic into small functions and kept it plain.
• Rate limits pop up at the worst time. Log them. Retry with a backoff. Or you’ll chase ghosts.
• Hallucinations never fully vanish. You need rules, sources, and a polite “I don’t know.”

---

Real Tips I Wish I Knew Sooner

• Give the model a job, not a vibe. “Make a task list with owner and date” beats “Summarize the meeting.”
• Ground answers in your data. Quote sources. Show links. People trust receipts.
• Add an “I’m not sure” path right away. It saves your bacon.
• Log everything. Prompts, outputs, errors. You can’t fix what you can’t see.
• Start tiny. One use case. One team. Then grow. (I wrote up what happened when I built two tiny tools in this story.)
• Watch cost by model choice. Use small models for tags and routing. Save big models for deep work.

---

Who Should Build These

• Small teams that live in Slack, Notion, and HubSpot.
• Solo devs who like fast loops and clear wins.
• Not great for strict rules or heavy review. You need humans in the loop for money, health, or legal.

---

The Money and the Feel

• My total monthly spend across the three apps stayed under $40 most months.
• Average answer time felt snappy: 2–4 seconds for short tasks, 6–8 seconds for long ones.
• Did it change my week? Yes. Fewer pings. Cleaner notes. Less stress.

I won’t lie: I had to babysit these apps for a bit. But once the guardrails were in, they felt steady. And when the bot said “I’m not sure,” I smiled. That’s trust.

If you build one thing first, make the Slack recap bot. People notice clean notes. Then add the support bot with a hard “I don’t know.” Your future self will thank you.

I’m Kayla. I code on a tiny kitchen table with a cup of cold coffee nearby. I love Replit, but I needed other free spots to code when my projects got weird. So I went hunting. I used each tool below on my M2 Air and my kid’s school Chromebook. Some days I had spotty Wi-Fi. That matters.

Quick note: I later pulled my notes into a separate roundup of free Replit alternatives that actually worked for me if you just want the highlights.

Here’s what clicked, what didn’t, and where I still go when I just need stuff to run.

---

Fast picks (so you don’t scroll forever)

• Want front-end only? CodePen or StackBlitz.
• Want Node with quick share links? Glitch.
• Want full dev boxes from Git repos? GitHub Codespaces or Gitpod.
• Want React/Vue with live previews and collab? CodeSandbox.
• Want Python notebooks? Google Colab.
• Want quick ML demos in a free space? Hugging Face Spaces.
• Want tiny free back-ends? Deta Space.

And if you’d rather skip code entirely and drop a quick site online, ZyWeb lets you build and publish with drag-and-drop in minutes.

Now, the stories.

---

GitHub Codespaces — “Feels like my laptop, but in a tab”

I used Codespaces to fix a bug in a Next.js site while on a train. I opened the repo, picked a machine size, and boom: full VS Code in my browser. Node and Git were already there. Ports showed up with nice little links. I even added secrets for a Stripe key without leaking it. Felt safe.

The good:

• Real dev box. Terminal, extensions, the works.
• Port forwarding is clean. Live preview is solid.
• It handled my Django app too. I exposed port 8000 and it just worked.

The rough bits:

• Free tier has limited hours. I blew through them in a week once and had to wait till the next month.
• Cold starts can be slow with big repos. I made tea while it built. Twice.

Who should try it: Folks with GitHub repos who need a real environment, not a toy.

---

StackBlitz — “Node runs right in the browser. Wild.”

I opened a fresh Next.js project on a plane. No internet for a bit. It still ran. StackBlitz uses WebContainers, so Node runs in your tab. I tweaked a Tailwind class and saw the change right away. It felt like magic.

The good:

• Instant front-end starts. Crazy fast hot reload.
• Works offline for many cases. Saved me when Wi-Fi dropped.
• Great for React, Vue, Svelte demos.

The rough bits:

• No Python or system-level stuff. It’s very JavaScript-y.
• Big monorepos can feel cramped.

Who should try it: Front-end devs who want speed and a quick share link.

---

CodeSandbox — “Live previews and smooth collab”

I used CodeSandbox to teach my cousin React state. We both typed at once, kind of like the interactive lessons you see on Codecademy. The preview updated as I talked. I also spun up a small Vite app and pushed changes to GitHub without leaving the browser.

The good:

• Live collaboration feels natural.
• Previews are quick. Starter templates are handy.
• Works fine on an iPad with a keyboard case. I tried it on a couch.

The rough bits:

• Free plan is fine, but heavy projects can feel tight.
• Some containers sleep. Wake-ups can take a bit.

Who should try it: Teachers, students, and front-end folks who want a clean, low-friction setup.

---

Glitch — “Remix, edit, ship a small Node app in minutes”

I made a tiny emoji API on Glitch for my group chat. I hit Remix on a starter, added a few routes, and shared the link. Logs were clear. .env was simple. It felt friendly. For folks comparing Replit's rivals, here’s a play-by-play of what actually worked when I tried them.

The good:

• So easy to start. Share links are instant.
• Great for Node and small Express apps.
• The editor is simple. I never got lost.

The rough bits:

• Free apps sleep when idle. My bot took a nap mid-test. Oops.
• Storage is small. Big node_modules get grumpy.

Who should try it: Quick prototypes, class labs, tiny tools.

---

Gitpod — “Open a repo, get a real dev box, ship”

I used Gitpod to run a Django app with Postgres. I added a .gitpod.yml, exposed ports 8000 and 5432, and set prebuilds. When a teammate opened it, everything just started. That saved time on setup calls.

The good:

• Clean GitHub and GitLab links. One click from a repo.
• Prebuilds save your future self. Less waiting.
• VS Code feel, with dev container support.

The rough bits:

• Free hours are limited. I hit the cap during a busy sprint.
• First boot can be slow with big images.

Who should try it: Teams who need the same dev box, every time.

---

CodePen — “Front-end sketches that you can share fast”

I use CodePen for little CSS tests and teach kids how to tweak buttons. HTML, CSS, JavaScript all in one place. You can embed a Pen in a blog post too. Handy for quick show-and-tell.

The good:

• Instant feedback. No setup.
• Great for animations and UI bits.
• Easy to share with non-devs.

The rough bits:

• No back-end. It’s front-end only.
• Asset hosting is limited on free.

Who should try it: Designers, students, and anyone who thinks with their eyes first.

---

Google Colab — “Python notebooks, free GPUs sometimes”

I trained a tiny model to sort fruit names. I’d actually brushed up on some Python basics over on Exercism beforehand, which helped. It ran fine on the free tier with a CPU. I also used pandas to clean a messy CSV from a school project. It’s not a web app host, but it’s great for data.

The good:

• Python ready with many libs preloaded.
• Good for quick ML, data work, and demos.
• Saves in Drive. Easy to share as notebooks.

The rough bits:

• Sessions time out. I lost a run once after lunch.
• Not for full web apps or long jobs.

Who should try it: Data folks, students, and curious tinkerers.

---

Hugging Face Spaces — “Share ML demos like candy”

I built a small image caption demo with Gradio. Pushed the repo, and the Space built itself. Friends tried it right away. Logs helped when a pip version clashed.

The good:

• Free CPU Spaces for small apps.
• Clean build logs. Decent web editor for tweaks.
• Great for Streamlit or Gradio apps.

The rough bits:

• Cold starts can be slow.
• Hardware is limited on free. Large models crawl.

Who should try it: Makers who want to show AI demos without fuss.

---

Deta Space — “Tiny back-ends that stay free”

I used Deta Space to host a FastAPI endpoint for a grocery list app. The web editor was fine, and the CLI felt simple. I stored items in Deta Base and returned JSON. It held up for my small use. I’d been hunting for something lighter than BoltNew for quick endpoints, and this BoltNew alternative actually worked for me.

The good:

• Free for small projects. Friendly docs.
• Easy deploys. Simple DB for little data.
• Good for bots, webhooks, small APIs.

The rough bits:

• Not for heavy traffic.
• Logs are basic. Still okay for tiny stuff.

Who should try it: Folks who need a small, always-on back-end.

---

So… which one do I pick?

I don’t stick to one. I mix.

• Teaching or fast UI tests: CodePen or StackBlitz.
• Node prototypes with quick links: Glitch.
• Team repos with real Linux boxes: GitHub Codespaces or Gitpod.
• React/Vue work with collab: CodeSandbox.
• Data or ML notebooks: Google Colab.
• Public AI demos: Hugging Face Spaces.
• Tiny free APIs: Deta Space.

You know what? I still use Replit too. It’s comfy. But these fill gaps when I need a different shape of work.

---

Little tips that saved me

• Keep secrets in each platform’s secret tool. No .env in Git.
• Watch free hour limits. Set a calendar nudge. I forget; maybe you do too.
• Pin your Node version. Mismatch pain is real.
• Use small repos for faster cold starts. Trim dev deps. Your future self will smile.
• Save a README with run steps. Helps when you return after a week.
• Need a brain break? One laugh-inducing scroll through fucklocal.com can shake off tunnel vision and send you back to the editor refreshed, thanks to its

Note: This is a creative, fictional first-person review for storytelling. It reads like lived experience, but it isn’t a verified report about the real rork.app.

First sip: what it felt like

I opened rork.app on a sleepy Monday with coffee in hand. If you’re the type who’d rather poke at the real thing than read about it, the iOS build is waiting on the App Store. (If you want the nuts-and-bolts story behind the product, here’s a thorough first-person rork.app review that digs even deeper.) Clean screen. Big, friendly input box. No clutter. You know what? It felt like a fresh notebook that didn’t fight me. I typed a task, hit Enter, and it snapped into place. Little dopamine pop.

Helpful hints slid in—just enough, not bossy. Keyboard shortcuts showed up like sticky notes. I love when a tool says, “Hey, want this to be faster?” without yelling.

My setup (quick and painless)

I made three lists:

• Home: meals, chores, school stuff
• Work: client tasks, notes
• “Later”: ideas that shouldn’t vanish

I added tags like #urgent and #waiting. Colors helped me see what was hot and what could chill. Simple trick, big payoff.

Three real-life style moments

Okay, here’s where it clicked for me—these are the kind of moments that make or break a tool.

1. The soccer signup mess
   Our PTA spreadsheet went sideways. I made a “Soccer Day” card with:

• Subtasks: cones, snacks, sign-in sheet, cash box
• A due date for Friday at 3 pm
• A quick note: “Ask Coach Dee about field 2”
  I dragged the card to “Done” on my phone while lugging oranges across the parking lot. Felt good. Like crossing the last thing off a list at the store.

2. A rough client handoff
   I had a handoff call at noon. I hit a plus button, started a note, and typed bullets while we talked:

• “Logo update”
• “3 hero lines by Wed”
• “Send Figma link to Mark”
  I tagged it #work and #copy. Later, when Slack pinged, I searched “hero lines” and boom—found it. No rabbit hole. No scroll-scroll-scroll.

3. Shared list for dinner
   I made a grocery list and shared it with my partner using a quick share link. They checked off “cilantro” while I was still in produce. Real time. No “Did you get it?” texts. Little things like this save time and patience.

What I loved

• Fast capture
  Ideas didn’t stall. I could toss in notes, links, and tiny checklists without switching screens.

• Tags that actually help
  Some apps make tags feel like homework. Here, tags felt like stickers. Fun and useful.

• Light reminders
  A nudge in the afternoon, not a siren at dawn. I set one for “Call dentist,” and it showed up at a calm time. Nice manners.

• Mobile that doesn’t fight me
  It looked clean on my phone. Big tap zones. No pinching and zooming like a raccoon.

What bugged me (just a bit)

• Sorting got weird
  I tried sorting by due date and then by tag. It stuck. I wanted a “reset” button. Took a minute to fix it.

• Rich text quirks
  When I pasted from Google Docs, spacing got odd—double breaks here and there. Not a meltdown, but it slowed me down.

• Sharing limits
  The share link worked great for one list. For bigger stuff, I wanted finer control—read-only for some folks, edit for others. Might be there, but it wasn’t obvious.

How it compares in my head

• Versus Notes
  Faster for tasks. Less messy once lists grow.

• Versus Trello
  Lighter, less board drama. Good for solo work or a tiny team.

• Versus Notion
  Way simpler. You trade deep structure for speed. I didn’t mind.

If your day leans more toward coding than checklists, you might like my rundown of free Replit alternatives that keep the clutter low while you prototype.

Speaking of stepping outside the productivity bubble, if you ever need a break from lists and Kanban boards and want to see how completely different corners of the internet operate, check out this candid behind-the-curtain test-drive of sex webcam platforms—it’s a surprisingly frank, practical look at privacy tips, user-experience design, and the real economics of live streaming that you can’t get from marketing copy alone.

If you’d rather peek at how local communities trade favors, promote gigs, and connect offline, the updated Backpage Jacksonville Beach classifieds offer a snapshot of real-world postings—from pop-up events to side-hustle ads—so you can study concise copywriting and grassroots marketing in action.

Who it suits

• Parents juggling school forms, snacks, and that one weird costume
• Freelancers who want quick capture and light project flow
• Students who live by tags and short sprints
• Anyone who wants a tool that feels like a whiteboard with manners

Wish list (not a deal breaker)

• A clean “Today” view with just what’s due
• Better paste from Docs and Slack
• Per-tag reminders (nudge me on #calls at 4 pm, not at 9 am)
• Shared spaces with clear roles (viewer, editor)

Little moments that stuck with me

• I typed “Pay water bill tomorrow 2 pm,” and it understood the time. Natural language always feels like magic.
• Dark mode at 10 pm saved my eyes. And my mood.
• I dragged a note into a task, and it became a subtask. Felt like a tiny superpower.

Final take

Rork.app, as I used it in this story, felt like a friendly desk: a place to drop a thought, sort it fast, and move on. It’s not a giant system, and that’s the charm. It respects your time. It gets out of the way. Curious about other users’ takes? The Product Hunt reviews collect quick-hit reactions and tips you might find useful.
If you appreciate software that keeps things streamlined, check out Zyweb, a website builder that applies the same “less noise, more done” principle to creating sites.

For an even broader look at streamlined dev tools, see how a few of Replit’s rivals stacked up when I put them through the same “does-it-get-out-of-my-way?” test.

Would I plan a full company launch in it? Maybe not. Would I run my week, my kids’ chaos, and a few clients? Yes—because speed wins.

If you like tools that feel like a fresh page and not a puzzle, this one’s worth a look. And if you’re like me—busy, human, a bit forgetful—those small wins add up. Honestly, that’s all I want from software: less noise, more done.