"1,096 People Are Talking About Their Projects, But No One Noticed the Same Trend"

"Late Tuesday night, a post appeared on Hacker News with a title as bland as white bread: \"Ask HN: What are you working on? (June 2026).\" 303 upvotes, 1,096..."

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1,096 People Are Talking About Their Projects, But No One Noticed the Same Trend

Late Tuesday night, a post appeared on Hacker News with a title as bland as white bread: "Ask HN: What are you working on? (June 2026)." 303 upvotes, 1,096 comments.

I spent three hours reading through them all. Not to find the coolest project — but to count how many times the same question was asked.

The result made me sit up straight.

Translating This Into Plain English

Let me explain what this thread is about. Every month, HN has a recurring column: developers spontaneously gather and tell the world, "Here's what I'm working on this week." It's not a formal Show HN launch — it's a looser, more honest status update.

Across 1,096 comments, I spotted a recurring sentence pattern:

"I'm building an AI agent that can [specific task] in [specific tool]."

Not once or twice. Dozens of times. And those "specific tasks" are getting narrower — not "general-purpose AI assistant," but "write my Jira tickets for me," "reply to my Slack messages," "create a Notion database for me."

The same day, Product Hunt had the same thing happening:

See the pattern?

Everyone is doing the same thing: stuffing AI into existing workflows, instead of making people learn a new AI tool.

Who's hurting? Teams and individuals drowning in tools. An engineering team might be running Slack, Jira, Notion, GitHub, Linear, and Figma simultaneously. Each tool has its own notifications, its own approval flows, its own context-switching costs. You used to hire a person to handle this. Now you want to hire an AI — but not one that requires opening a new website and signing up for a new account.

Why now? Because Claude Code and GitHub Copilot have already educated the market: AI can do things for you, not just answer questions. But the education is only half-done — users know AI can do stuff, but they don't want to change their work habits to use it.

Pricing anchor: $19–49/month, priced per tool. Or $9/month per tool. A one-time buyout works too — $199 per agent.

There's an Opportunity Hiding Here

Most builders looking at these signals will conclude: "The AI agent market is saturated."

Wrong.

What's saturated is the general-purpose AI agent — the "universal assistant" that can do everything but nothing well. What's not saturated are single-tool, single-task "micro-agents."

Let me be more specific.

In the HN thread, one developer said they're building a "GitHub PR reviewer agent" — not a code-writing agent, but one that does exactly one thing: when a PR is created, automatically check code style, run tests, and leave a comment on the PR. That's it.

Another said they're building a "Slack daily standup agent" — at 9 AM every day, it starts a standup thread in Slack, collects everyone's updates, and compiles them into a Notion page. That's it.

These aren't a startup's core product. They're plugins, extensions, tiny tools. A developer could probably build one in a weekend, price it at $19 one-time or $9/month.

Who pays first?

Mid-level managers crushed by their toolchain. Specifically: an engineering manager running a 5–15 person team, spending 2 hours a day switching between Jira and Slack. They don't need an "AI strategy." They need an automatically generated standup summary waiting for them at 9 AM tomorrow.

Why do most people miss this?

Because most builders chase "bigger" products — full-stack, multi-platform, enterprise-grade. They overlook the small, certain, paid needs hiding inside a single Slack channel, a single GitHub repo, a single Notion database.

Why Most People Miss It

The mainstream view is: build AI products big, make them "AI-native," disrupt workflows.

This view is especially loud on Product Hunt. Look at the top-voted products — Goldfish, Novu Connect, MakersClaw — they all try to be "your second brain" or "AI employee." They're doing it right, but the problem is they look too much like full products.

The real opportunity isn't there.

The real opportunity is inside that engineering manager's Slack channel. They don't need an "AI employee." They need a script that does one specific thing, in one specific channel, at one specific time.

What's the evidence? In the HN thread, the "micro-agent" projects got surprisingly good feedback. One developer building a "Linear → Slack notification agent" said they received 4 paid inquiries within 6 hours of posting. Not because their code was amazing, but because they solved a very specific, very annoying problem.

Another signal: AEVS (129 votes) on Product Hunt is building proof-of-execution for agents — not the agent itself, but proof of what the agent did. This is more noteworthy than the agent itself. Why? Because when agents start doing things for people, people need to know if they did it right. This is a meta-problem — harder to solve than the agent itself.

If It Were Me, Here's What I'd Do

Step 1: Don't build a product. Build a list first.

This afternoon, use a Google Form or a Markdown file. List the 10 most annoying repetitive tasks in your daily work. Describe each as one sentence, like:

Then, go to that HN thread, find the corresponding "micro-agent" projects (they're open source, or at least public), and see how others implemented them. Don't write code yet. Copy someone else's thinking first.

Step 2: 7-day validation plan.

MVP plan: A single README file describing what the agent does, priced at $19 one-time, a payment link (Stripe or Gumroad), then manually execute the first 5 customers. You don't need to write a single line of code to validate demand.

Failure condition: When is this judgment wrong?

If you get zero paid interest in 7 days, or if the interest is all "I want to see how it works" instead of "I need this right now," then the pain isn't sharp enough. Or worse: existing tools already solve this (e.g., Slack's built-in Workflow Builder already handles 80% of the job).

Another failure condition: If engineering managers say, "This is nice, but I need IT department approval" — then you know. This is enterprise sales, not something an indie developer can close quickly.

Other Signals Worth Watching This Week

  1. Edgee Turbo Models (PH, 165 votes): Use other models (Kimi, MiniMax) inside Claude Code. This shows developers want model-switching flexibility, not lock-in to a single vendor.

  2. Kickbacks.ai (PH, 286 votes): Pays you while Claude Code runs. Sounds like a joke, but the pain behind it is real: AI agent execution time is unpredictable.

  3. Veterinarian turned founder, AI lawn diagnosis (HN, 73 upvotes): A vet switched careers to build AI lawn diagnosis. Cross-disciplinary founders are often the best signal for real problems — they don't carry the baggage of "how it's supposed to be done."

  4. Wobo - AI Job Search (PH, 313 votes): Tinder-style job hunting, AI applies for you. This space is heating up, but so is the competition.

  5. MockPilot (PH, 138 votes): Turn real websites into editable mockups. Designer pain points have always existed, but "solving with AI" isn't a silver bullet.

About AimFast.Dev

AimFast.Dev is a signal-driven tool built for indie developers. Every day, it scrapes 6,000+ raw signals from 20+ sources — Hacker News, Product Hunt, Reddit, GitHub, Google Trends, and more — then filters them down to the 5–10 most noteworthy opportunities using a scoring formula.

It's not a news aggregator. It's a complete signal → evidence → translation → action pipeline. Every opportunity includes: who pays, pricing anchor, 7-day validation plan, and failure conditions.

If you're looking for the next small product worth building — not chasing the next big trend — AimFast.Dev is designed for you.

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