← All Articles

10 Months of Struggle: Building My Own Lean Agentic AI with Smart Routing and Offline Execution✎ Edit

👁 120 views
10 Months of Struggle: Building My Own Lean Agentic AI with Smart Routing and Offline Execution

Finally, after 10 months of struggles, failures, and endless troubleshooting, I've managed to build my own modified Agentic AI with both Web-CLI and Telegram interfaces.

OpenClaw (OC) is good, but it's becoming too bloated with features, dependencies, and complexity that most of us don't really need.

In my opinion, nearly 80% of those features are unnecessary for everyday use.

My Agent AI comes with Personal Smart Routing, allowing the system to select the most suitable AI model based on task complexity. Not every task requires a powerful or expensive LLM.

I've also integrated Offline Functions, allowing repetitive and routine tasks to run directly without calling an LLM or consuming tokens. This significantly reduces API dependency, token usage, and operating costs.

My goal is simple: build an AI agent that is lighter, faster, more efficient, and fully under my control.

Less bloat. Smarter routing. More offline execution. Lower costs.

Sometimes, innovation isn't about adding more features. It's about removing what we don't need and making better use of the resources we already have.

Ruang pembaca

Apa pendapat anda?

Komen disemak sebelum diterbitkan. Email diperlukan untuk moderasi dan tidak dipaparkan kepada pembaca.

✦ Reaksi dijana sistem - contoh automatik, bukan komen pembaca sebenar
Ginsang Kadazan, Malaysia

Terus terang, 80% ni menarik.

Dimas Indonesia

Still thinking about it's about removing.

Ayu Indonesia

I've also integrated offline functions is the part I would forward to my boss.

Narin Thailand

The numbers around my Agent AI comes make more sense than most posts I read.

Suda Thailand

พูดตรง ๆ 80% ก็น่าสนใจ

Miguel Philippines

Kung may kasunod tungkol sa 80%, babasahin ko iyon.

Artificial Intelligence

Article image
BioResearch Microbiology & cancer disease research intelligence 6 inputs → traceable research priorities Explore →
Edge AI IoT & embedded Linux intelligence at the edge 14 edge agents → offline-capable Explore →
IC DesignOps Repeatability, traceability & verification intelligence 21 detached services → 85% without LLM Explore →
Robotics Governed robotics at the industrial edge Perception → safety gateway → controller Explore →
AINNA Ecosystem

Keep exploring after this article.

Every article page should end with a clear path into the wider AINNA, Agent, and NeuralOps ecosystem.

Current topic Artificial Intelligence Author profile Masli Yahaya AINNA Main ecosystem hub Agent Private autonomous agent hub NeuralOps AI automation and business systems Lead form Start a pilot discussion
AINNA Agent AI

Deploy Our AINNA AI Agent

Linux is the core path, Windows is supported, and Android / Termux works as the companion layer.

13 downloads
Linux / macOS curl -fsSL https://ainna.bond/install | bash
Verify ainna --version
AINNA
CLICK ME

Site Sections

No section data available yet.

Sites with documented sections will appear here.