The latest articles on DEV Community by VISHAL (@vishal_363322ef6e3732ec09). https://dev.to/vishal_363322ef6e3732ec09 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3937798%2F4be20301-1188-436d-bf53-681676321241.jpg https://dev.to/vishal_363322ef6e3732ec09 en VISHAL Mon, 18 May 2026 10:33:14 +0000 https://dev.to/vishal_363322ef6e3732ec09/-my-experience-running-openclaw-for-ai-automation-5doa https://dev.to/vishal_363322ef6e3732ec09/-my-experience-running-openclaw-for-ai-automation-5doa <p>Recently, I started experimenting with AI automation tools and local AI workflows using OpenClaw, Claude APIs, Ollama, and self-hosted setups.</p> <p>At first, I thought setting up AI agents locally would be simple… but I quickly learned that running these systems 24/7 requires much more than just installing a model.</p> <h2> What I Explored 🧠 </h2> <ul> <li>Running local AI models with Ollama</li> <li>Connecting Claude API with automation workflows</li> <li>Testing OpenClaw-like agent systems</li> <li>Mini PC and Mac Mini setups for continuous AI workloads</li> <li>Handling memory usage, GPU/CPU limits, and API costs</li> </ul> <h2> Biggest Challenges ⚡ </h2> <h3> 1. Hardware Limitations </h3> <p>Running AI tools continuously is demanding.</p> <p>I tested setups on:</p> <ul> <li>Windows PC</li> <li>Mini PCs</li> <li>Cloud alternatives</li> </ul> <p>One major lesson:<br> RAM and thermal performance matter more than most beginners expect.</p> <h3> 2. API Costs </h3> <p>Claude/OpenAI APIs are powerful, but costs increase quickly if:</p> <ul> <li>agents loop frequently</li> <li>memory grows</li> <li>prompts are unoptimized</li> </ul> <p>Prompt optimization became extremely important.</p> <h3> 3. Local vs Cloud </h3> <p>Local models provide:<br> ✅ More privacy<br> ✅ Lower long-term cost<br> ✅ Offline capability</p> <p>But cloud APIs still outperform most local models for reasoning quality.</p> <h2> What I Learned 📚 </h2> <h3> Good AI systems need: </h3> <ul> <li>reliable hardware</li> <li>efficient prompts</li> <li>automation logic</li> <li>monitoring</li> <li>proper error handling</li> </ul> <p>Not just “install and run”.</p> <h2> My Current Stack 💻 </h2> <ul> <li>React.js</li> <li>Node.js</li> <li>Ollama</li> <li>Claude API</li> <li>Local automation tools</li> <li>Self-hosted experiments</li> </ul> <h2> Advice for Beginners 👇 </h2> <p>If you're starting with AI automation:</p> <ol> <li>Start small</li> <li>Learn prompt engineering</li> <li>Understand system resources</li> <li>Don’t overspend on APIs early</li> <li>Build practical projects instead of chasing hype</li> </ol> <h2> Final Thoughts 🚀 </h2> <p>AI agents and automation tools are evolving incredibly fast.</p> <p>We’re moving toward a future where solo developers can build systems that previously required entire teams.</p> <p>Still learning every day — excited to keep building and experimenting.</p> <p>Would love to hear what AI tools or setups others are exploring 👀</p> <h1> ai #opensource #webdev #react #node #automation #machinelearning </h1> ai opensource webdev productivity