Technical SEO
Sep 29, 2026
Claude AI Ka YouTube Checklist: Video Optimization Ka Asaan Tareeka
A video on using Claude to prepare a YouTube video optimization checklist.
Watch on YouTube ↗HELLO, I'M FAZAL. I BUILD THINGS.
AI is interesting.
Making it work
is the good part.
Agents that use real tools. Models that run on your own machine. Software that solves a specific problem. I build it, test it, and share what I learn.
Here’s what “an agent” actually means.Tools do the work. Permissions, validation and human approval define the boundaries. Errors need a visible recovery path.
THE AGENT WORKBENCHWorkflow illustration
01
YOUR REQUEST
A task, with context.
02
REASON & PLANUnderstand the task.
Choose the next tool.
Choose the next tool.
Keep actions inside the allowed scope.
03CALL THE RIGHT TOOL
Research
Retrieve data
Connect APIs
04 / CHECK
Validate. Get approval
when needed.
05 / DELIVER
Take the action.
Keep a record.
I build it, test it, and share what I learn.
WATCH THE WORK
Builds, tests & breakdowns.
AI Agents
Apr 15, 2026
How to build a multi agent team with Openclaw | urdu/hindi
A walkthrough about building a multi-agent team with OpenClaw, presented in Urdu/Hindi.
Watch on YouTube ↗
AI Agents
Mar 7, 2026
Is Your Openclaw Broken? The Fix You Need Right Now
A practical OpenClaw troubleshooting video from Fazal Shah.
Watch on YouTube ↗READ THE METHODS
Notes you can build from.
Human approval for AI agents: review the exact action
Design approval requests with clear payloads, reviewers, expiry and safe recovery instead of a vague approve button.
Read the articleAgent retries and idempotency: recover without duplicate writes
Design retry budgets, logical action identifiers and reconciliation for agents calling external systems.
Read the articleAI agents for SEO automation: build an evidence-to-review pipeline
Design an SEO automation workflow that collects crawl evidence, drafts fixes, validates output and measures changes without invented ranking gains.
Read the articleTAKE SOMETHING USEFUL
Free resources.
A practical place to start.
AI Agent Production Readiness Checklist
A practical checklist covering permissions, failure recovery, evaluation, monitoring and deployment.
Download free resource ↓AI SEO Audit Checklist
Review crawlability, indexability, canonicals, structured data and migration risks.
Download free resource ↓Local LLM Coding Benchmark Kit
A blank CSV and testing protocol for recording reproducible local-model experiments.
Download free resource ↓CURRENTLY ON THE WORKBENCH
Good questions.
Time to build the tests.
These experiments are planned. No published results or pretend play buttons.
LOCAL AI / HARDWARE EXPERIMENT
UPCOMING EXPERIMENT / 01How much Mac
How much Mac
does local AI need?
Test useful workloads, memory pressure and the cost of the hardware. Start with the smallest machine that can do the job.
Read the experiment plan ↗Can a local model take over the coding?
The same tasks, reviewed outputs, and the tools behind the result.
Explore the plan ↗Let AI help.
Keep the evidence.
Automate the checks. Document the changes. Measure before making claims.
Explore the plan ↗THREE WAYS TO BUILD
Different tools.
The same engineering mindset.
AI agents, with boundaries.
Tools, permissions and recovery paths. Build workflows you can inspect, test and improve.
Explore the workLocal AI, on real hardware.
Explore memory limits, inference engines and useful workloads. Find the trade-offs behind the specs.
Explore the workSoftware that does the work.
Connect APIs, automate repeatable tasks and turn experiments into maintainable products.
Explore the workWHY THE TESTS MATTER
The first version
is never the whole story.
I look for the missing data, the broken tool call and the task the model couldn’t finish. Those are the parts worth understanding.
Build → test → learn.
Then do it again.
A useful experiment gives you the method as well as the result. What ran? What failed? What would I change?
Read the engineering notes ↗ENGINEERING LOOPIllustrated, not live
FROM WORKBENCH TO PRODUCT
Things I’m building
and working on.
01 / AGENT WORKFLOWS
AgentMagic
A platform we’re building to coordinate AI workflows and business automation.
Explore AgentMagic02 / VISUAL TOOLS
IconKing
SVG icons, Lottie animations and a browser-based visual asset workflow.
Explore IconKing03 / OUR AI AGENCY
KodeKing
Our AI automation agency for SMEs: integrations, agent workflows and the infrastructure behind them.
Explore KodeKingBUILD IN PUBLIC
Tools, skills and field notes you can inspect.
I publish Mac utilities, agent infrastructure and reusable workflows on GitHub. Start with the code and documentation, then adapt the parts that fit your setup.
Auto Pause Mac Apps
A macOS menu bar utility for pausing background apps and managing memory headroom before local model work.
Explore on GitHub ↗Turnstile
A concurrency-capping FIFO proxy in front of a local model endpoint, designed to keep multi-agent requests from overwhelming one GPU.
Explore on GitHub ↗Claude skills
Reusable skills covering living documentation, self-healing MCP services and coverage-verified RAG indexing.
Explore on GitHub ↗LET'S BUILD SOMETHING USEFUL
Your workflow.
A system that fits it.
From agent architecture to private AI deployments, I help founders and teams turn a specific problem into a tested implementation.
Tell me what you're buildingSTART WITH A PROBLEM
Run the numbers. Find the next fix.
Not sure whether to change the model, the hardware or the workflow? Start with the lab results, test your assumptions with a tool, or bring me the problem.