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I built a platform to validate that non-technical users actually want AI agents

TL;DR: I built a platform to validate a hypothesis: If we lower the barrier to entry for using and productizing agents, will normal users actually like them? I’m looking for builders to test it out. You can take your existing agent code, f…

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TL;DR: I built a platform to validate a hypothesis: If we lower the barrier to entry for using and productizing agents, will normal users actually like them? I’m looking for builders to test it out. You can take your existing agent code, fill out a simple manifest, run a few CLI commands, and have a shareable, web-accessible agent in 10 minutes. Links at the bottom.







Happy New Year, everyone.



I assume most of you here are tech professionals or enthusiasts. Over the past year, AI Agent has been the biggest buzzword. It’s reached a point where hearing someone say “I’m building an AI Agent” almost gives me a visceral reaction lol. But looking back, despite the hype, the actual market adoption has been… tragic. I think the growing “AI bubble” narrative today is, to a large extent, driven by how hard it’s been for agentic applications to actually land in the real world.



The funny thing is, if you look around, there are tons of products claiming to help you build agents. Diverse frameworks, tools, and templates are everywhere. Everyone tells you their product makes things easier. But in reality, very few agents are actually being used by the market, and most of the adoption is concentrated among a handful of big players. At the end of the day, what we build has to create real value for people, right?



What’s even more interesting is that research shows the most adopted agents right now are coding agents and web-scraping agents, and their target audience is mostly developers and creators. Yep, it’s pretty much the same group that’s building them. The ecosystem is basically self-producing and self-consuming.



And the truth is, most normal users don’t even know the difference between an Agent, a Generative App, or a Chat UI. They use ChatGPT, maybe Suno, Loveable, but “Agents” are still alien to them.



After digging deep, I realized low adoption probably isn’t because agents suck. I’ve tried a lot of open-source agents that are actually useful. The real issue is understanding, delivery, and the reliability vs. complexity paradox.



First, the vast majority of agentic apps require you to deploy or set things up, of course including preparing your API keys. With requirements like that, you can basically say bye-bye to normal users.



Sure, you can say, “I can build the website, set up the server, handle payments, manage keys,” etc. But isn’t that way too heavy for an app? In business, the hard part is never the code itself, it’s delivering at scale to users. Anyone who’s tried knows exactly what I’m talking about. In reality, most agents aren’t really meant to be used continuously every single day. To justify those costs, you’ll likely start expecting your agent to do more. But that leads to a new problem is the impossible triangle between autonomy, complexity, and reliability. Once you add more nodes and components to make the agent “stronger,” execution accuracy drops exponentially. Your agent turns into a rambling, confused idiot. From the user’s perspective, that’s even less acceptable. This is exactly the dilemma most commercialized agent products face today: you want an agent to cover an entire human workflow, achieve product-grade stability and reliability, and still charge enough to cover your costs. That’s insanely hard.



Single-purpose agents (agents that focus on doing one thing well) actually work. I’ve tried many of them, and I genuinely believe they can win users’ hearts. They just need to be seen and be easily accessible. Pushing agents to be more complex doesn’t just restrict what we can build, but also makes shipping them much harder. So even though infrastructure is advancing rapidly, the market still can’t seem to ship more than a handful of actually usable agents.



I also ran an experiment about this. A few months ago, I started deploying some agents I thought were pretty cool and let friends with no technical background use them. The reactions were mostly great. Funny enough, everyone’s favorite was an entertainment-focused fortune-telling agent. It’s not the kind of agent people would intuitively think of, but the girls loved it and kept saying it was spot on.



Thus, I built a distribution platform for agent apps. It includes app packaging, automatic isolated runtime environments, handling system/app dependencies, multi-turn memory storage and injection, version control, UI generation, and key management + encryption, so builders only write logic, and users don’t have to care about any of the setup. If they’re interested, they just click and use.



I want to validate one thing. If we make agents dead simple to deliver and use, with one click, no setup, and no prior knowledge, will normal users actually embrace them? Can this help people discover and benefit from genuinely useful agents? And will it push builders to create more interesting apps, instead of only giant “super agents” getting adopted?



So here’s the invitation. If you already have a runnable agent, upload it and give it a shot. Your agent doesn’t need to be super powerful. It just needs to do one thing well, and that thing should be valuable.



Let’s prove that these ideas have value beyond GitHub stars. We’ve actually built a lot. People just haven’t seen it yet. It’s a way to validate your market idea early and see if there’s real user demand.



The whole process is very simple, only need to:




  1. Prepare your agent code.

  2. Copy the template and fill out a simple manifest.

  3. Run a few CLI commands.

  4. Done in ~10 mins. Your agent is live and interactive.



Even if you don’t have an agent, feel free to browse and try out the creative apps others have built. You might unexpectedly find something useful or fun.



(Note: I’ve implemented key management and injection logic. Because I think requiring BYOK, to some extent, goes against my original intention of lowering the experience barrier as much as possible. But since I can’t afford everyone’s API costs yet, I encourage bringing your own keys to test the agents for now.)



This is still the first MVP, so you might run into some bugs or rough spots. If you have feedback or ideas, feel free to lmk via GitHub issue or the community. I’m currently working solo, so replies or fixes might take a bit time. Thanks for your patience!



Register your agent



Try agents

1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
Syntax validiert (0 Fehler)
title: Detect Exploitation - I built a platform to validate that non-technical users actually want AI agents
id: 232785c3-1fbb-4c24-ab4d-5e8c46e3138d
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "I built a platform to validate" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("I built a platform to validate that non-")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*I built a platform to validate that non-*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "I built a platform to validate that non-"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

CTI Threat Relationship Graph2 Knoten / 1 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
-
Resource Development
-
Initial Access
Execution
Persistence
-
Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
-
Lateral Movement
-
Collection
-
Command and Control
Exfiltration
-
Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich I built a platform to validate that non-.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
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