I

I made a Reddit post scheduler in 83 dev hours

Hacker News

I made a Reddit post scheduler in 83 dev hours

Hey friends! I’d like to introduce my latest product, Flashpost, a post scheduling tool for Reddit. The free tier includes 5 free posts per month so you can give the product a try. It is my first paid product as I try to make it as a solo indie dev! The goal is to offer a simple tool for creators to promote their projects on Reddit without breaking the bank for a single distribution channel. Now for the behind the scenes details. ## The Backstory When I launched my first project TechStackLeads on Reddit, the response was remarkable. My post received 700k impressions, resulting in 20k visitors on the site, and more than 80 signups. Even today I get about 300 visitors per month to the project. Reddit traffic is a hidden gem. I owe a large part of my success to a well timed post when everyone was online. I had no issues waking up early to manually make each post until I moved to Hawaii. If I wanted to post at 8AM eastern time zone, I would need to wake up at 2AM local time. Wild! My first choice was to pay for a social media tool to help schedule my posts. The most popular tools were affordable but did not include Reddit. When I looked at the Reddit-only marketing tools, they are $100 per month for unlimited posts. $1,200 per year is not in my budget! At this point I figure I’ll just build the thing for myself, to solve my own problems. After 30 days of development Flashpost was created. One fun fact is the project only took me 83 hours of dedicated dev time. I know this number because I timebox my dev sessions with Google calendar. The next product won’t take so long because I have a lot of reusable code! If you do choose to try the product, you can reach me on LinkedIn or Twitter with your questions, comments, or concerns. ## The Tech Stack Frontend: HTML, jQuery, AlpineJS. Backend: Python, Flask Database: Postgres (self-hosted) Auth: Supertokens (self-hosted) Ingress: Traefik (self-hosted) Observability: Grafana, Prometheus, Loki (All self-hosted) Service Mesh: Linkerd (self-hosted) Containers: Kubernetes with K3s (self-hosted) Hosting: Linode VM DNS: Cloudflare I self-host most of my software stack components. I want to minimize vendor debugging issues I’ve had in the past (I’m looking at you IAM and Quotas requests). My favorite parts of the stack are K3s and my observability stack. Kubernetes is 100% overkill. But I’m an SRE/DevOps so believe it or not I have templates to get up and running quickly. I do NOT recommend this for beginners. I love the centralized observability stack because all my projects are observable by default. I use Linkerd so I get access to their ready-made Grafana dashboards. For authentication I use Supertokens. I’m not 100% sold on this service. I had a rather brutal time debugging the vanilla javascript integration which revealed a lot of holes in their documentation. They seem to optimize for the ReactJS path. It works fine now but I’m searching for alternatives where I can keep auth mainly server side. Overall I love my stack. I can ship products fast! Thanks for reading until the end. Tell me what you think. Cheers!

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6points
3comments
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
98%98% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: google, single, code · Missing: mac, agents, macos
89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month, google · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid, introduce · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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