AI-Powered Automation & Content Creation for Businesses
Helping businesses leverage AI, automation, and integrations to streamline workflows and supercharge content creation.
The future of business is AI-driven. I specialize in creating AI-powered solutions that automate processes, integrate seamlessly with your existing tools, and generate content effortlessly. Whether it's WhatsApp and Telegram automation, AI voice agents, or AI-generated videos and images, I help businesses stay ahead of the curve. Let's explore how AI can work for you.
About Me
With over 25 years of experience in IT consulting and over 15 years in photography and videography, I've always been at the forefront of technology and creativity. My journey from visual storytelling to AI innovation has given me a unique perspective on how automation, AI integrations, and content generation can revolutionize businesses.
I now focus on:
- •Developing AI-powered mobile apps
- •Automating workflows with WhatsApp, Telegram, and CRM integrations
- •Creating AI-generated content for businesses, including video and image automation
- •Leveraging local LLMs for secure and powerful AI solutions
Businesses today need to embrace AI to stay competitive. Let's connect and explore how AI can transform your operations.
Services
AI-Powered Mobile Apps
Custom-built AI applications that streamline operations, enhance efficiency, and provide innovative solutions tailored to your business needs.
Automations & Integrations
Seamlessly integrate AI into your business operations with WhatsApp, Telegram, email marketing, and CRM automation.
Voice AI Agents
Enhance customer interactions with AI-driven voice agents, providing automated responses and intelligent customer support.
Local LLM Solutions
AI chatbots and tools that run locally, ensuring privacy, security, and speed for businesses needing on-premise AI.
AI-Powered Content Generation
Revolutionize social media and marketing with AI-generated videos, images, and automated content creation.
Past Work Experience
While I've built a strong foundation in photography and videography over the past 15 years, I've now refocused my expertise on AI solutions and mobile development to help businesses innovate and grow.
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Latest AI News
10 Essential Security Steps for OpenClaw Users to Prevent Hacks
Feb 11, 2026
Security is not a feature when you run OpenClaw. It is the foundation. If you are using ClawdBot (now called OpenClaw), you are effectively running an AI agent with access to API keys, infrastructure, logs, automations and possibly production systems. That is powerful. It is also risky. This article walks through 10 essential security steps that are not “nice to have” tweaks. They are baseline rules. Ignore them, and you are inviting trouble. Apply them, and you dramatically reduce your attack surface. <br><br> <ul> <li><a href="#why-security-matters">Why OpenClaw security is different</a></li> <li><a href="#separate-device">1. Never run OpenClaw on your main device</a></li> <li><a href="#no-root">2. Disable root access</a></li> <li><a href="#change-port">3. Change default ports</a></li> <li><a href="#private-network">4. Keep it off the public internet</a></li> <li><a href="#ssh-fail2ban">5. SSH keys and Fail2Ban</a></li> <li><a href="#firewall">6. Lock down your firewall</a></li> <li><a href="#allowlist">7. Use an allow-list</a></li> <li><a href="#log-monitoring">8. Make OpenClaw monitor itself</a></li> <li><a href="#no-groups">9. Never use group chats</a></li> <li><a href="#least-privilege">10. Apply least privilege</a></li> <li><a href="#interfaces">Popular interfaces: WhatsApp, Slack, Telegram and more</a></li> <li><a href="#risks">Realistic risk scenarios and prevention</a></li> </ul> <h2 id="why-security-matters">Why OpenClaw security is different</h2> <p>OpenClaw is not a passive tool. It can execute commands, interact with APIs, access tokens and perform automated actions.</p> <p>That means:</p> <ul> <li>If compromised, it can expose API keys.</li> <li>It can modify data.</li> <li>It can run commands on your server.</li> <li>It can pivot into other systems.</li> </ul> <p>Think of it as giving a junior sysadmin access to your infrastructure, except this one works 24/7 and follows instructions instantly.</p> <br><br> <h2 id="separate-device">1. Never run OpenClaw on your main device</h2> <p>Do not install OpenClaw on your daily laptop that stores:</p> <ul> <li>Personal photos</li> <li>Saved passwords</li> <li>Browser sessions</li> <li>Private documents</li> </ul> <p>Use:</p> <ul> <li>A separate VPS</li> <li>A dedicated Mac mini</li> <li>A cloud server with isolated credentials</li> </ul> <p><strong>Risk example:</strong> A malicious prompt injection causes OpenClaw to read local files. If it runs on your personal laptop, it could access sensitive directories.</p> <p><strong>Prevention:</strong> Isolate it. If something goes wrong, you wipe the machine. No personal damage.</p> <br><br> <h2 id="no-root">2. Disable root access</h2> <p>Never let OpenClaw operate as root.</p> <p>Root means full system control.</p> <p>Instead:</p> <ul> <li>Create a limited user</li> <li>Disable root SSH login</li> <li>Grant only required permissions</li> </ul> <p><strong>Risk example:</strong> If OpenClaw executes a malicious command as root, it can modify system binaries, delete logs or install backdoors.</p> <p><strong>Prevention:</strong> Limited user accounts contain the blast radius.</p> <br><br> <h2 id="change-port">3. Change default ports</h2> <p>Default ports are scanned constantly by bots.</p> <p>Changing the port does not make you invincible but it removes you from automated mass scans.</p> <p><strong>Risk example:</strong> Automated scanners find your default gateway and start brute-forcing credentials.</p> <p><strong>Prevention:</strong> Change the port and combine it with firewall restrictions.</p> <br><br> <h2 id="private-network">4. Keep it off the public internet</h2> <p>Expose nothing publicly if possible.</p> <p>Use a private networking solution like <strong>Tailscale</strong> to create a private mesh between your devices.</p> <p>This way:</p> <ul> <li>OpenClaw is invisible to the public internet</li> <li>You can access it securely from anywhere</li> </ul> <p><strong>Risk example:</strong> A publicly exposed dashboard with weak auth gets indexed or brute-forced.</p> <p><strong>Prevention:</strong> Zero public exposure.</p> <br><br> <h2 id="ssh-fail2ban">5. SSH keys + no passwords + Fail2Ban</h2> <p>Passwords can be guessed or leaked.</p> <p>Instead:</p> <ul> <li>Use SSH keys only</li> <li>Disable password authentication</li> <li>Install <strong>Fail2Ban</strong></li> </ul> <p>Fail2Ban blocks repeated failed login attempts automatically.</p> <p><strong>Risk example:</strong> Botnet attempts 10,000 login attempts per hour.</p> <p><strong>Prevention:</strong> Keys + automatic IP banning.</p> <br><br> <h2 id="firewall">6. Lock down your firewall</h2> <p>Use UFW or similar firewall tooling.</p> <p>Close everything except:</p> <ul> <li>SSH from your private network</li> <li>Specific required services</li> </ul> <p><strong>Risk example:</strong> An exposed database port becomes accessible externally.</p> <p><strong>Prevention:</strong> Default deny. Only open what is absolutely required.</p> <br><br> <h2 id="allowlist">7. Use an allow-list</h2> <p>Configure OpenClaw to respond only to approved identities.</p> <p>Allow-list specific:</p> <ul> <li>User IDs</li> <li>Phone numbers</li> <li>Slack user IDs</li> <li>Telegram handles</li> </ul> <p><strong>Risk example:</strong> A random user discovers your bot endpoint and starts sending commands.</p> <p><strong>Prevention:</strong> Only pre-approved users can trigger actions.</p> <br><br> <h2 id="log-monitoring">8. Make OpenClaw monitor itself</h2> <p>Let OpenClaw monitor:</p> <ul> <li>Auth logs</li> <li>System logs</li> <li>API usage spikes</li> </ul> <p>Trigger alerts when:</p> <ul> <li>Unknown IP connects</li> <li>API usage jumps unexpectedly</li> <li>Unexpected commands execute</li> </ul> <p>This turns your AI into a watchdog instead of just an executor.</p> <br><br> <h2 id="no-groups">9. Never use group chats</h2> <p>Only use Direct Messages.</p> <p>In group chats:</p> <ul> <li>Someone can accidentally trigger commands</li> <li>Someone can inject malicious prompts</li> <li>Logs become messy and ambiguous</li> </ul> <p><strong>Risk example:</strong> A team member jokingly writes “delete everything” and the bot interprets it literally.</p> <p><strong>Prevention:</strong> Strict DM-only command channels.</p> <br><br> <h2 id="least-privilege">10. Always apply least privilege</h2> <p>Start with minimal permissions.</p> <p>Do not:</p> <ul> <li>Grant full filesystem access by default</li> <li>Give admin API tokens unnecessarily</li> <li>Allow unrestricted command execution</li> </ul> <p>Add permissions only when required.</p> <p><strong>Risk example:</strong> Compromised bot token has admin-level API access across systems.</p> <p><strong>Prevention:</strong> Scope-limited tokens and role separation.</p> <br><br> <h2 id="interfaces">Popular interfaces: WhatsApp, Slack, Telegram and more</h2> <p>OpenClaw often integrates with:</p> <ul> <li><strong>WhatsApp</strong></li> <li><strong>Slack</strong></li> <li><strong>Telegram</strong></li> <li><strong>Discord</strong></li> <li>Custom web dashboards</li> </ul> <p>Each interface increases your attack surface.</p> <p>Security steps must apply to each integration separately.</p> <br><br> <h2 id="risks">Realistic risk scenarios and prevention</h2> <h3>Scenario 1: Prompt injection via Slack</h3> <p>A malicious user embeds hidden instructions in a document link shared in Slack. OpenClaw processes it and executes unintended actions.</p> <p><strong>Prevention:</strong></p> <ul> <li>Restrict file access scope</li> <li>Scan inputs for suspicious instructions</li> <li>Use confirmation layers for destructive actions</li> </ul> <h3>Scenario 2: API key leakage</h3> <p>Logs accidentally expose API keys in debug output.</p> <p><strong>Prevention:</strong></p> <ul> <li>Mask sensitive data in logs</li> <li>Rotate keys regularly</li> <li>Limit key permissions</li> </ul> <h3>Scenario 3: Compromised VPS</h3> <p>Unpatched server vulnerability allows remote execution.</p> <p><strong>Prevention:</strong></p> <ul> <li>Regular updates</li> <li>Automated patch management</li> <li>Infrastructure isolation</li> </ul> <br><br> <p>Security is not something you “add later.”</p> <p>If you treat OpenClaw like a toy, you will eventually get burned.</p> <p>If you treat it like production infrastructure from day one, you reduce risk dramatically.</p> <p>Security is not a feature. It is your foundation.</p>
Claude Opus 4.6 Explained: Why This Is a Major Shift Toward AI Colleagues
Feb 6, 2026
test1Claude Opus 4.6 is live and this is not a routine model refresh. With this release, Anthropic is making something very clear: large language models are no longer being optimized mainly for “better answers,” but for sustained, complex work. Claude Opus 4.6 feels less like a chatbot upgrade and more like a structural step toward AI that can reason, plan, and collaborate over long horizons. This is the kind of release you don’t fully appreciate in a demo. You feel it once you put it into real workflows. <br><br> <ul> <li><a href="#what">What Claude Opus 4.6 actually is</a></li> <li><a href="#context">The 1-million-token context window (and why it matters)</a></li> <li><a href="#reasoning">Stronger reasoning, coding, and planning</a></li> <li><a href="#agents">Agent teams: multiple AIs working together</a></li> <li><a href="#usecases">Concrete use cases across teams</a></li> <li><a href="#business">Business value and workflow impact</a></li> <li><a href="#shift">From chatbot to AI colleague</a></li> </ul> <h2 id="what">What Claude Opus 4.6 actually is</h2> <p><strong>Anthropic Claude Opus 4.6</strong> is the most capable model Anthropic has released to date. While previous versions already positioned Claude as a strong reasoning and writing model, 4.6 shifts the emphasis toward:</p> <ul> <li>Long-horizon reasoning</li> <li>Deep contextual understanding</li> <li>Multi-step planning and execution</li> <li>Collaboration between multiple AI agents</li> </ul> <p>This is not primarily about being more “creative” or more “human-like.” It’s about reliability when tasks get large, messy, and interconnected — the exact conditions of real knowledge work.</p> <br><br> <h2 id="context">The 1-million-token context window (and why it matters)</h2> <p>The headline feature many people focus on is the <strong>1-million-token context window</strong>, currently available in beta. On paper, that sounds abstract. In practice, it fundamentally changes what you can hand to a model in one go.</p> <p>Examples that now become realistic:</p> <ul> <li>An entire production codebase with documentation and test files</li> <li>Multiple long contracts plus historical amendments</li> <li>Years of internal strategy notes and meeting summaries</li> <li>Large financial models with assumptions, notes, and commentary</li> </ul> <p>Before this, even strong models required careful chunking and re-feeding of context. With Opus 4.6, you can often provide the whole picture once — and reason on top of it.</p> <p>This reduces:</p> <ul> <li>Context loss</li> <li>Repetition of instructions</li> <li>Human “prompt glue” work</li> </ul> <p>For teams, that means fewer fragile workflows and more trust in long-running analysis.</p> <br><br> <h2 id="reasoning">Stronger reasoning, coding, and planning</h2> <p>Claude Opus 4.6 shows clear improvements in tasks that require sustained logical consistency rather than quick answers.</p> <h3>Complex reasoning</h3> <p>In multi-step analytical tasks — such as scenario planning or regulatory analysis — the model is noticeably better at:</p> <ul> <li>Keeping assumptions consistent</li> <li>Referencing earlier conclusions correctly</li> <li>Avoiding contradictory recommendations</li> </ul> <h3>Coding at scale</h3> <p>For developers, Opus 4.6 is particularly strong when dealing with:</p> <ul> <li>Large repositories instead of isolated snippets</li> <li>Refactoring across multiple files</li> <li>Understanding architectural intent</li> <li>Explaining trade-offs, not just syntax</li> </ul> <p>Rather than acting like an autocomplete engine, it behaves more like a senior reviewer who understands the system as a whole.</p> <h3>Planning and execution</h3> <p>Where earlier models might jump straight to output, Opus 4.6 is better at explicitly planning:</p> <ul> <li>Breaking down complex tasks into phases</li> <li>Identifying dependencies and risks</li> <li>Adjusting plans when constraints change</li> </ul> <p>This makes it much more suitable for project-level collaboration, not just task-level assistance.</p> <br><br> <h2 id="agents">Agent teams: multiple AIs working together</h2> <p>One of the most forward-looking elements of Claude Opus 4.6 is support for <strong>agent teams</strong>.</p> <p>Instead of one monolithic model doing everything, work can be split across multiple specialized agents, for example:</p> <ul> <li>One agent analyzes requirements</li> <li>Another designs an architecture</li> <li>A third focuses on implementation</li> <li>A fourth reviews for risks or edge cases</li> </ul> <p>The key difference from earlier “multi-prompt” setups is coordination. These agents can share context, align on goals, and hand off subtasks in a structured way.</p> <p>For teams experimenting with AI-driven workflows, this opens the door to:</p> <ul> <li>Parallel execution instead of serial prompting</li> <li>Clearer separation of concerns</li> <li>More predictable outcomes</li> </ul> <br><br> <h2 id="usecases">Concrete use cases across teams</h2> <h3>Engineering teams</h3> <ul> <li>Reviewing an entire repository before a major refactor</li> <li>Generating migration plans with risk analysis</li> <li>Onboarding new developers using full-context explanations</li> </ul> <h3>Legal and compliance</h3> <ul> <li>Analyzing long contracts and identifying inconsistencies</li> <li>Comparing regulatory frameworks across regions</li> <li>Summarizing historical decisions with supporting references</li> </ul> <h3>Strategy and finance</h3> <ul> <li>Scenario modeling with explicit assumptions</li> <li>Reviewing investment memos end-to-end</li> <li>Connecting operational data to strategic narratives</li> </ul> <h3>Product and operations</h3> <ul> <li>Turning fragmented documentation into coherent playbooks</li> <li>Planning multi-quarter initiatives</li> <li>Identifying process bottlenecks across teams</li> </ul> <p>Across all of these, the value comes from continuity — the model doesn’t “forget” halfway through the work.</p> <br><br> <h2 id="business">Business value and workflow impact</h2> <p>From a business perspective, Claude Opus 4.6 is less about replacing people and more about compressing cycles.</p> <ul> <li>Faster understanding of complex systems</li> <li>Fewer handoffs lost to miscommunication</li> <li>More consistent analysis across teams</li> </ul> <p>Teams that benefit most tend to share three traits:</p> <ul> <li>They deal with large bodies of information</li> <li>They already document decisions (at least partially)</li> <li>They value planning as much as execution</li> </ul> <p>In those environments, Opus 4.6 acts as connective tissue — not a replacement brain.</p> <br><br> <h2 id="shift">From chatbot to AI colleague</h2> <p>The most important shift with Claude Opus 4.6 is psychological.</p> <p>Instead of thinking:</p> <p>“I’ll ask the AI a question.”</p> <p>Teams increasingly think:</p> <p>“I’ll give the AI the full context and let it work through this with me.”</p> <p>That difference matters. It changes how work is structured, how tasks are delegated, and how trust is built.</p> <p>Claude Opus 4.6 is a clear signal that we’re moving from AI that answers to AI that collaborates — plans, reasons, and participates.</p> <p>Not a chatbot. An AI colleague.</p>
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