What Doosol Points Out
- The hardest part of blogging isn’t writing — it’s figuring out what to write about. I automated that.
- Every morning at 8 AM, a Telegram bot sends me a content brief: AI news, trending Reddit/Hacker News posts, competitor blog updates, and AI-generated topic recommendations.
- It monitors keywords related to my blog (AI, investing, ETFs) and flags when something is trending — so I can write about it while people are searching for it.
- The whole thing cost $0 to build (free APIs) and runs on the same server as my blog. About 3 hours to set up.
- This is the third bot I’ve built with zero coding background. The pattern is always the same: describe what you want to AI, follow the steps, fix the errors, repeat.
Building a blog topic bot changed how I write — and it took less than an afternoon. Two weeks ago, I stared at a blank screen for 45 minutes trying to decide what my next blog post should be.
I had a vague sense that I should write something about AI. Or maybe investing. Or maybe both. But “something about AI” isn’t a blog topic — it’s a category. I needed a specific angle, a timely hook, a reason someone would click on it today rather than next month.
That 45 minutes of indecision bothered me more than the actual writing. So I did what I’ve been doing a lot lately: I built a blog topic bot to solve the problem.
What the Bot Does
Here’s what my blog topic bot sends me every morning at 8 AM:
📝 Daily Content Brief (Mar 16, 2026)
🆕 AI NEWS • Anthropic launched “Claude Projects for Teams” — no reviews yet → First-mover opportunity. Relevance: HIGH
• OpenAI released voice mode on ChatGPT free tier → Angle: “Free vs Paid AI features — what you actually lose”
🔥 TRENDING • r/investing: “Is VOO still the best set-and-forget ETF?” (3.1K upvotes) → You have an ETF article. Follow-up: “VOO vs VTI” comparison
• Hacker News: “I replaced my financial advisor with AI” (482 points) → Directly related to your MCP article. Share + respond opportunity
👀 COMPETITOR POSTS • oneusefulthing.org: “A Guide to Which AI to Use in 2026” → Gap: doesn’t cover hands-on setup. Your MCP article fills this.
💡 TOP 3 TOPICS TO WRITE THIS WEEK
- “VOO vs VTI: Which Total Market ETF?” — high search volume, you have related content already
- “Claude Projects Review” — new feature, zero reviews online yet
- “Free AI vs Paid AI: What $20/Month Actually Gets You” — evergreen + trending
In one message, I know exactly what’s happening in my space, what people are interested in, and what I should write about. The 45-minute decision paralysis is gone.
Why This Matters for Any Blogger
Whether you write about tech, investing, cooking, or fitness, the core problem is the same: you need to write about things people are searching for, at the moment they’re searching for them.
A blog post about a new AI feature published the day it launches gets 10x more traffic than the same post published two weeks later. A comparison article about two ETFs published when Reddit is debating them catches a wave. Timing is everything, and timing requires awareness.
Most bloggers get this awareness by manually scrolling through Twitter, Reddit, news sites, and competitor blogs. It works, but it’s slow, inconsistent, and easy to skip when you’re busy with actual life.
This blog topic bot replaces that manual scanning with a system. Same sources, same analysis, zero effort on my end.
The Four Sources It Monitors
1. AI News (NewsAPI)
The bot checks major tech publications every 24 hours for news about Claude, ChatGPT, Gemini, and AI tools in general. When a company launches a new feature, the bot flags it immediately.
Why this matters: “First review” articles are SEO gold. When Anthropic launched something new last week, my blog was one of the first to review it. That early post captured search traffic before bigger sites published their versions.
2. Reddit and Hacker News (Free APIs)
The bot pulls the hottest posts from subreddits like r/investing, r/ChatGPT, r/artificial, and r/personalfinance. It also checks Hacker News for AI, investing, and productivity-related posts.
Why this matters: Reddit upvotes = real demand. When a post asking “Is VOO still the best ETF?” gets 3,000 upvotes, that means thousands of people have this exact question. If I write a clear, beginner-friendly answer, those people will find my article through Google.
3. Competitor Blogs (RSS)
I added RSS feeds from blogs that cover similar topics. The bot checks for new posts every day and flags them.
Why this matters: You need to know what others are writing — and what they’re missing. When a popular AI blog published “Which AI to Use in 2026,” my bot flagged it. I read it, noticed they didn’t cover hands-on setup or real examples, and knew my existing MCP article already filled that gap. Sometimes the best content idea is one you’ve already written.
4. GPT Analysis (The Brain)
All the raw data — news, Reddit posts, HN posts, competitor articles — gets sent to GPT-4o. The AI’s job is to synthesize everything and answer one question: “What should I write about this week, and why?”
It considers timeliness (what’s new), demand (what’s trending), competition (what’s already been written), and my existing content (what I can link to). The output is three specific topic recommendations with titles and angles.
This is the part that surprised me most. The AI doesn’t just parrot the trending topics back. It connects dots. It noticed that my ETF article + a trending Reddit discussion + a gap in competitor coverage all pointed toward the same topic. I wouldn’t have seen that pattern on my own.
How I Built It (Third Time’s the Charm)
This is the third bot I’ve built in the past few weeks. The first was a Claude MCP server for stock research. The second was a Telegram bot that sends me stock picks every morning. Each one taught me something.
By my third bot, including this blog topic bot, the pattern was familiar:
- Create a new Telegram bot via BotFather (5 minutes)
- SSH into my Cloudways server
- Make a new project folder, install packages
- Write the Python script (AI generated the code, I pasted it in)
- Add my API keys
- Test it manually
- Set up auto-run with cron
- Set up the bot for on-demand commands with nohup
Total time this round: about 2 hours. Faster than the first two because I’d already made (and fixed) most of the common mistakes.
The funniest part? I didn’t hit a single “Permission denied” error this time. Growth.
What You Need
To build your own blog topic bot, you need:
- Cloudways or any cloud server — I use the same $12/month server that runs my blog
- Telegram account — free
- NewsAPI key — free tier (100 calls/day)
- Reddit API — free, no key needed for basic access
- Hacker News API — free, no auth required
- OpenAI API key — about $0.10-0.20/day for this bot
- feedparser — free Python library for RSS
Everything except the OpenAI API is completely free. And even that costs less than a cup of coffee per week.
The Commands
The blog topic bot runs in two modes: automatic daily brief (via cron at 8 AM) and on-demand (I type commands anytime).
| Command | What it does |
|---|---|
/brief | Full content brief with AI analysis |
/ainews | Just the AI news |
/trending | Reddit + Hacker News hot posts |
/competitors | New posts from tracked blogs |
/keywords | See my monitored keywords |
/addkeyword ETF | Add a keyword to monitor |
/addblog Name URL | Add a competitor blog RSS |
/help | Show all commands |
The /addkeyword and /addblog commands are especially useful. As my blog grows into new topics, I just add keywords and competitor feeds without touching any code.
What I’ve Learned After One Week
After one week with this blog topic bot, here’s what changed: The daily brief changed my writing rhythm. Before, I’d think about blog topics randomly throughout the day. Now I read the brief over morning coffee, pick a topic, and start writing. The decision is made before 9 AM.
Trending topics have a window. When the bot flagged a new Claude feature, I had about 48 hours before every tech blog covered it. Writing within that window meant my article ranked on the first page. Writing after that window would have meant competing with 50 other reviews.
Not every alert is a blog post. Some days the brief is mostly noise — no major news, no trending discussions relevant to my niche. That’s fine. The bot saves me 30 minutes of manual checking and tells me “nothing urgent today” in 10 seconds.
Competitor monitoring is surprisingly motivating. Seeing other bloggers publish regularly makes me want to publish too. It’s like having a writing accountability partner, except the partner is an RSS feed.
The Bigger Pattern
This is the third “I built a bot” article I’ve written, and I want to zoom out for a second.
Six weeks ago, I didn’t know what SSH was. I’d never written a line of Python. The idea of running code on a server felt like something developers do, not product managers.
Now I have three bots running 24/7 on a $12/month server:
- A stock research assistant connected to Claude via MCP
- A daily stock picks bot that sends me AI-analyzed recommendations
- A content strategy bot that finds me blog topics
None of these are impressive from an engineering perspective. The code is simple. The APIs are free. An actual developer would probably cringe at some of it.
But they work. Every day. Automatically. And they solve real problems I actually have.
That’s the real story here. The barrier between “I wish I had a tool that does X” and “I have a tool that does X” has collapsed. Not because I became a developer. Because AI can bridge the gap between what I want to build and what I know how to build.
If you have a repetitive information-gathering task — whether it’s tracking competitors, monitoring trends, scanning news, or screening stocks — you can probably automate it in an afternoon. The tools are free. The AI will walk you through it. The hardest part is starting.
So start. This blog topic bot is the clearest example of that shift.
Disclaimer: This article describes a personal content research tool. The APIs used have free tiers with usage limits — check each provider’s terms. AI-generated topic recommendations should be evaluated with your own editorial judgment.