Build in Public — The Complete Guide
Building in public is sharing your work-in-progress openly — your competition results, project progress, failures, lessons, and wins — before they're polished. It…
Build in Public — The Complete Guide
What "Build in Public" Means
Building in public is sharing your work-in-progress openly — your competition results, project progress, failures, lessons, and wins — before they're polished. It's the opposite of waiting until something is perfect to share it.
Why it works for competition careers specifically:
- Recruiters at Kaggle GM-level companies (Citadel, Jane Street, Google) actively search Twitter/X and GitHub for competition performers
- Sharing your approach invites feedback that improves your next attempt
- Other competitors remember you when forming teams
- A 3-month trail of consistent public work beats a 1-page resume
The core rule: Post the process, not just the outcome. "I tried X, it didn't work, here's what I learned" gets more engagement than "I won."
WHERE TO POST — Platform-by-Platform Guide
1. Twitter / X — Your Primary Build-in-Public Channel
The center of gravity for #buildinpublic. Most competition builders, ML researchers, and indie hackers live here.
Hashtags to use on every post:
| Hashtag | Audience | Use When |
|---|---|---|
#buildinpublic | Founders + makers | Any progress update |
#100DaysOfML | ML learners | Daily learning posts |
#MachineLearning | ML community | Competition results, model insights |
#DataScience | Data community | EDA, analysis posts |
#Kaggle | Kaggle community | Competition-specific |
#hackathon | Hackathon community | Hackathon progress |
#OpenSource | Dev community | When releasing code |
#AI | Broad AI audience | General AI topics |
Optimal hashtag count: 1–2 per post. More than 3 kills reach.
Post formats that get engagement:
Thread format (highest engagement):
"I just finished [competition]. Here's everything I tried 🧵
1/ First I tried [X]. It gave me CV score 0.87.
2/ Then I added [feature]. Score jumped to 0.91.
3/ The insight that pushed me to top 10%: [Y]"
Single insight (quick engagement):
"One thing I wish I knew before my first Kaggle competition:
Cross-validation strategy matters more than model choice.
Here's why 👇"
Failure post (surprisingly high engagement):
"I spent 3 days on a feature that made my score WORSE.
Here's the lesson about [X]"
Result post:
"Just ranked top 8% on [competition name] 🎉
Dataset: [X] | Model: LightGBM | Key trick: [Y]
Full notebook: [GitHub link]"
Accounts to tag/engage with: @kaggle, @huggingface, @weights_biases, @DoraHacks, relevant competition organizers
2. Indie Hackers — indiehackers.com ★ CORE COMMUNITY
The most established build-in-public community. Focused on builders making money from their projects, but very welcoming to competition builders and ML engineers sharing their journey.
What to post:
- Your competition journey as a "product" — create a page for your "ML Competition Career"
- Monthly revenue/progress updates (even if revenue = prize money won)
- Interviews with yourself about lessons learned
- "Milestones" posts: "First Kaggle submission", "First hackathon win"
How it works:
- Create a free account at indiehackers.com
- Start a "product" — name it something like "My ML Competition Journey" or your actual project
- Post updates regularly (weekly or bi-weekly)
- Comment on others' journeys genuinely — the community is tight-knit and reciprocal
Indie Hackers has a daily leaderboard of build-in-public posts — consistent posting gets you featured
Best use for you: Post after EVERY competition with: what you tried, what score you got, what you learned, what you'll do differently.
3. WIP — wip.co
A focused community of makers who log daily tasks publicly. Simple, low-friction.
How it works: Post daily "todos" publicly. Other makers can see what you're working on. Built-in accountability.
Best for: Daily discipline log — "worked on feature engineering for [competition]", "submitted first hackathon prototype"
URL: wip.co
4. Hacker News (Show HN / Ask HN)
The most respected developer audience on the internet. Getting to the HN front page = 10,000+ visitors in 24 hours. Very hard but very high impact.
Types of posts:
| Format | When to Use | Title Formula |
|---|---|---|
| Show HN | Launching a project/tool | Show HN: [What it does in one line] |
| Ask HN | Seeking feedback/advice | Ask HN: [Specific question] |
| Monthly thread | "What are you working on?" monthly thread | Reply with your project |
Show HN rules that matter:
- Must be something YOU built
- Title = what it does, not what it is. "Show HN: A tool that predicts X using Y" not "Show HN: My new ML project"
- First comment: add context — WHY you built it, HOW it works, WHAT makes it different
- Share the GitHub link. HN audience reads code.
- Best time to post: Monday–Wednesday, 8–10 AM EST
"Ask HN: What are you working on?" monthly thread — Post every single month. Low barrier, direct exposure to 5M+ developers. Just describe your current competition/project in 3 sentences.
URL: news.ycombinator.com Browse top Show HN posts: bestofshowhn.com
5. Product Hunt — producthunt.com
Best for launching finished tools or AI projects you've built from competitions. Not for competition result posts — for actual products.
When to use it: When your hackathon project becomes a real tool.
2026 Launch Strategy:
- Pre-launch (4–6 weeks before): Build a "coming soon" page. Collect emails. Get 50+ people to say they'll upvote.
- Launch day: Post at 12:01 AM PST. Be active all day replying to comments.
- First comment (post it yourself): "Hi PH! I'm [name]. I built [X] because [problem]. Here's a quick GIF of how it works: [link]. Try it free: [link]"
- No upvote begging — PH algorithm detects it. Ask people to "check it out" not "upvote."
- Post in relevant categories: "Artificial Intelligence", "Developer Tools", "Productivity"
AI is heavily favored on Product Hunt in 2026 — the "AI agents" and "AI software" categories are the most active
6. Dev.to — dev.to
The most beginner-friendly developer blogging platform. High organic reach for technical posts.
What to post:
- "How I approached [competition]" writeups
- "What I learned from [hackathon]" posts
- Technical tutorials based on your competition work
- Your ML pipeline or code snippets with explanations
Why dev.to:
- Posts indexed by Google immediately
- Built-in audience of 1M+ developers
- Reactions + comments from day 1 (unlike a personal blog with 0 readers)
- Cross-posting is fine — they add a canonical URL
Tags to use: #machinelearning, #python, #datascience, #ai, #tutorial, #kaggle, #hackathon
URL: dev.to
7. Hashnode — hashnode.com
Better than Dev.to if you want to own your content on your own domain while still tapping into a developer network.
Why Hashnode:
- Posts live on YOUR domain (e.g., yourblog.hashnode.dev or yourname.com)
- Strong SEO — your posts rank on Google under YOUR name
- Developer-focused audience (not general public like Medium)
- AI-powered writing assistant built in
Best for: Long-form writeups of your competition solutions and project deep-dives.
URL: hashnode.com
8. Medium / Towards Data Science
The highest-prestige platform for ML writing. Top ML engineers publish here. Getting into the "Towards Data Science" publication = 500K+ readers.
How to get into Towards Data Science:
- Write a genuinely insightful article (not a basic tutorial)
- Submit to the publication from your Medium account
- They review within 2–4 weeks
Best post types for TDS:
- "How I won [competition] — a full technical breakdown"
- "The feature engineering trick that took me from rank 200 to top 50"
- "Lessons from 12 months of Kaggle competitions"
URL: medium.com / towardsdatascience.com
9. Reddit — Where to Post What
| Subreddit | Subscribers | Post Format | What to Share |
|---|---|---|---|
| r/MachineLearning | 3M+ | [P] tag = Project | Competition solutions, ML tools you built |
| r/learnmachinelearning | 500K+ | Any | Learning progress, tutorials |
| r/datascience | 1M+ | Discussion | Career posts, project showcases |
| r/SideProject | 200K+ | "I built X" | Hackathon projects turned real |
| r/kaggle | 200K+ | Any | Competition discussion, notebooks |
| r/artificial | 500K+ | News/Projects | General AI projects |
| r/algotrading | 300K+ | Strategy posts | WorldQuant/IMC competition approaches |
| r/webdev | 1M+ | Show off | Hackathon web projects |
Reddit posting rules that matter:
- Always be the FIRST commenter on your own post — add context, say you're the author, ask specifically for one type of feedback
- Don't cross-post the same thing everywhere at once — wait 2–3 days between subreddits
- Title format for r/SideProject: "I built [X] — [one-line description of what it does]"
- Title for r/MachineLearning: "[P] [Project name] — [what it does and key result]"
10. Build-in-Public Specific Communities
#buildinpublic on X / Twitter
Not a platform — a live hashtag community. Follow it, post to it, reply to others in it.
Makerlog
Simple daily task logger with a public feed. Ships a "streaks" system like GitHub contribution graph. URL: getmakerlog.com
Publicly
Alternative to WIP focused on sharing milestones and progress.
GitHub "Awesome Build in Public" list
github.com/johnnybuildsyo/awesome-buildinpublic — curated list of tools, templates, and examples
THE BUILD-IN-PUBLIC CONTENT CALENDAR
This is your weekly posting system. Takes ~30 min/week total.
| When | Platform | What to Post | Time |
|---|---|---|---|
| Competition starts | Twitter/X | "Starting [competition]. Goal: top 20%. Will share weekly updates. #buildinpublic #MachineLearning" | 5 min |
| After EDA | Twitter/X | "EDA done on [comp]. 3 interesting things I found: 1/ [X] 2/ [Y] 3/ [Z] #buildinpublic" | 10 min |
| Baseline model | Twitter/X | "Baseline: CV = 0.87. LightGBM out of the box. Now the real work starts 🛠️ #Kaggle" | 5 min |
| Key breakthrough | Twitter/X | Thread explaining what worked and why | 20 min |
| Competition ends | Indie Hackers | Full update post: approach, score, rank, lessons | 30 min |
| 1 week later | Dev.to or Hashnode | Full technical writeup with code | 60 min |
| 2 weeks later | r/MachineLearning or r/kaggle | Reddit post linking to writeup | 10 min |
| Hackathon built | Product Hunt (if real tool) | Launch when ready | Full day |
| Monthly | HN "What are you working on?" | 3-sentence project update | 5 min |
WHAT NOT TO DO
- Don't wait until it's perfect: Post the process. "I tried X and it failed" is more valuable than a polished post-mortem.
- Don't just broadcast: Reply to others' posts. The #buildinpublic community is reciprocal.
- Don't spam all platforms at once: Stagger your posts. Same content across 5 platforms in one day looks like spam.
- Don't chase vanity metrics: 10 engaged followers who are ML engineers > 10,000 random followers.
- Don't post without a point: Every post should give one insight, ask one question, or share one specific result. Vague posts get ignored.