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In 2025, I became a social butterfly the likes of which i’ve never been in my life.

This development coincided with me becoming truly confident, happy, and (mostly) stress-free for really the first time in my life. Huh, how strange.

Introversion, or being anti-social, is just a reflection of how one feels about themself. If you cannot happily, confidently present yourself to the outside world, you will always find it difficult to be social, to be fun around others, and to do so with a carefree, magnetic attitude that draws people in.

It all comes down to what’s in your head.

FRAMEWORK FOR BUILDING A $60K MRR MOBILE APP LIKE THIS

1. Start with a behavior people already have.

Sleeping already happens every night, so the snoring app fits naturally into an existing routine!

2. Tie the app to a question people already think about.

“Do I snore?” often comes up through partners, jokes, or health concerns, so curiosity exists before the app.

This makes your life easier.

3. Use AI to interpret the signal for the user.

The app turns raw audio into meaning by identifying when snoring happens and surfacing what matters.

Tons of niches/ideas are opened up to BECAUSE of AI right now.

4. Deliver the answer immediately.

You wake up, open the app, and see the result from the night before.

Builds the daily habit.

5. Make the result easy to show.

Short audio clips and simple visuals turn into five-second videos, which makes organic sharing effortless.

Virality goes up. Helps with CAC and compounding.

6. Keep the scope narrow and intentional.

The app focuses on one problem instead of becoming a full sleep platform, which keeps it useful and easy to understand.

And the name reflects it too. Says what it does. Autosnore. Snoring recorder.

Perfect.

7. Charge for clarity and peace of mind.

People happily pay to remove uncertainty, especially around health and relationships.

This pattern shows up across a lot of categories because these moments exist everywhere. @ideabrowser has shared a bunch of these ideas.

If people already do the behavior, already ask the question, and react emotionally to the answer, there’s probably a product there.

The fastest way to test it is simple: ship a rough version, show the output on video, and see if people lean in. The response usually tells you quickly whether it’s worth going deeper.

There are more "dumb" categories like this than people realize

Because of LLMs, the only type of people I’d hire now are what I’d call “super-unicorns”

• Developer
• Designer (or great design taste)
• Product-focused (vs feature-focused)
• Marketer
• Agent expert
• High emotional intelligence
• 5+ years experience creating web app products
• Extreme ownership (h/t @jockowillink)

There are very few folks with all these traits …

but I just wouldn’t want to work with someone who didn’t have all these skills/behaviors.

This will keep team sizes very small.

2026 is going to be very interesting for the whole industry.

I’m excited to share a new repo: Agent Skills for Context Engineering

Instead of just offering a library of black-box tools, it acts as a "Meta-Agent" knowledge base. It provides a standard set of skills, written in markdown and code, that you can feed to an agent so it understands how to manage its own cognitive resources.

github.com/muratcankoylan…

Most agent failures are not model failures; they are context failures. This is still an experimental project. The goal is to establish a platform-agnostic standard for context engineering that can be used in Cursor, Claude Code, Copilot or Codex.

skills/
context-fundamentals: What context is, why it matters
context-degradation: How context fails (lost-in-middle, poisoning)
context-optimization: Compaction, masking, caching
multi-agent-patterns: Orchestrator, swarm, hierarchical
memory-systems: Vector RAG, knowledge graphs, Zep
tool-design: Building tools agents can use
evaluation: Testing and measuring agent systems

I believe this is a good start, showing developers how to approach context engineering rather than relying on ready-made tools.

You will also find the aggregated research documents I used to build these skills in the repo. The skills are synthesized from technical blogs on context and prompt engineering that I bookmarked, AI Labs' documentations, and Anthropic Skills examples.

Try the 7 Skills, created using Antrhopic's Skills template format. Experiment with the provided scripts and references, and feel free to contribute to the repo.