Automation engineer. I help businesses 10x their ops with Make, n8n & AI agents.
Make Certified | Ex-Software Engineer (Go/JS/TS/Python) | Building in public π§΅
70% of developers report integration problems when connecting AI agents to existing systems. That's not an AI problem. That's a data infrastructure problem that was always there. The agent just made it visible.
Freelancers who can identify bottlenecks and build tailored automation solutions are described as "highly sought after" across Upwork and direct client channels right now. Bespoke automation. Not templates. Not tutorials. Tailored solutions. That is the edge.
The best thing about building automation for 7 years is knowing what "stable" actually feels like. Not zero errors. Zero unexpected errors. Every failure should be one you planned for.
Google and Kaggle just launched a free 5-day AI Agents course. Thousands will finish it and call themselves agent builders. The ones who will actually get hired are the ones who can handle what happens when the agent breaks in production at 2am. That part is not in the course.
AI automation salaries jumped 21% in one year. But only for the top tier. Mid-level automation engineers without clear outcomes attached to their work are actually seeing rate compression. The market is splitting, not growing evenly.
Genspark, NewCore, and Arcade raised $200M+ combined.
Investors arenβt betting on chat.
Theyβre betting on the infrastructure layer powering AI agents.
And that layer needs engineers.
You can now use Claude Desktop to build n8n workflows through MCP. That's Claude as your automation co-pilot, not just a chatbot. The line between "writing code" and "building workflows" just got blurry.
The most in-demand freelance skill right now is not coding. It is identifying where a business is bleeding time and building a workflow that stops the bleeding. AI-enabled freelance skills grew 109% on Upwork in 2026. The demand is real. Gap is in people who can actually delivr
Gartner called 2026 the "year of disillusionment" for agentic AI. 38% of enterprises are still stuck in pilot phase. Good automation engineers aren't worried. They're the ones getting called to fix it.
Salesforce just acquired a customer service AI platform for $3.6 billion. Databricks open-sourced their agent framework. SpaceX acquired Cursor. The enterprise is not experimenting with AI agents anymore. They are consolidating. If you are still "exploring," you are already late.
Context engineering is what automation engineers have been doing for years. We just called it "cleaning up the data before it hits the next module." Andrej Karpathy gave it a better name.
Microsoft just warned about "AutoJack" β a vulnerability where AI agents browsing untrusted sites can be exploited for remote code execution on host systems. You gave your agent browser access. Did you also give it a security audit? Most people did not.
MIT analyzed 300 enterprise AI agent projects. 95% never made it to production. The problem wasn't the AI. It was that nobody built the infrastructure for it to actually run on.
Engineers who can map a messy business process and turn it into something an AI agent can handle end to end are the most in-demand right now. That is not a prediction. That is Fiverr Pro's data from this month. The demand exists. The supply does not.
MCP is to AI agents what REST was to web APIs. You don't need to understand every implementation detail. But if you're building automation infrastructure and you're ignoring it, you're building on last year's map.
The next race in AI is not benchmark scores. It is agentic execution. GPT-5.5 is already plateauing on reasoning tests. What matters now is: can it actually complete a workflow end to end without breaking? That is an engineering problem, not a model problem
The automation engineers thriving in 2026 are not the ones who know the most tools. They are the ones who understand data flow well enough to work in any tool. The canvas changes. The principles don't.
Kimi Work just launched with 300 parallel agents running simultaneously. Impressive demo. But parallel agents without a clear orchestration layer is just parallel chaos. The bottleneck is never the number of agents. It is the logic connecting them.
Make MAIA can now generate scenarios from natural language. That's great for non-technical clients who want to prototype fast. It's also why engineers who can architect, debug, and maintain are not going anywhere.
Stop wasting hours on manual work.
I'm Zhuhry, an Automation Engineer helping businesses automate with https://t.co/XLP10Qo5FO, n8n, Zapier, and AI.
7+ years in software engineering (JS/TS/Go), building automations beyond typical no-code setups.
Let's connect π€