AI Workflow & Automation
Design practical AI, automation, and API workflows that teams can actually run in production.

Senior Dev × AI Systems
Helping teams build production-ready AI workflows, automation, internal tools, and infrastructure that actually hold up in real work.
This is the home for practical lessons from real engineering work — from architecture and APIs to deployment and AI-assisted workflows that do not lower the quality bar.
What I help with
The content and the work both revolve around systems that can actually be shipped, maintained, and used to reduce repetitive work.
Design practical AI, automation, and API workflows that teams can actually run in production.
Connect systems, reduce manual work, and build internal tools that make teams measurably faster.
From deployment and cloud to CI/CD and production hardening for systems that have to survive after launch.
Work with me
Best for teams that want less repetitive work, clearer systems, and AI or automation embedded into real workflows in a maintainable way.
Service 01
For teams that need a clear operating workflow where AI, human review, and automation can work together safely.
Expected outcome: workflow map, tool choices, integration direction, and the next implementation step.
Service 02
For reducing manual work, connecting APIs, building dashboards, or creating internal tools that speed teams up.
Expected outcome: a working system, a clearer ops flow, and less repetitive work.
Service 03
Use this when the team needs cleaner deployment, CI/CD, cloud setup, or production hardening.
Expected outcome: a clearer delivery path, fewer bottlenecks, and systems that are easier to maintain.
Best fit
Projects tend to be a strong fit when the team has a clear pain point and wants someone who can work across systems, implementation, and business outcomes.
Start here
YouTube is the content source, the website is the authority layer, and Facebook carries short updates and highlights from real work.
Internal
See how Dev with Bebz works with teams and the principles behind each build.
External
Deep dives on AI workflows, automation, infrastructure, and lessons from real engineering work.
External
Short takes, highlights from videos, and practical notes you can consume quickly.
Contact funnel
Start by understanding the approach, verify the technical depth from the content, then reach out with the right context so the first conversation can move quickly.
Step 1
Start with the About page to see whether the system design approach and AI usage philosophy match your team.
Open AboutStep 2
Use YouTube or the articles to evaluate the depth, thinking style, and problem-solving approach.
Watch YouTubeStep 3
Once the problem is clear, use the Facebook page as the first contact point to share the problem, goals, and team context.
Open Facebook PageWhat to send
The clearer the problem and context are at the start, the faster the first conversation becomes.
What happens next
This gives a clearer expectation for what happens after first contact.
Step 01
Start by locating the real pain point, the people involved, and the actual operational constraints.
Step 02
Evaluate what should use AI, what should use automation, and what standard engineering already solves better.
Step 03
Convert the direction into a plan, implementation path, or working system that can actually move forward.
Public proof
Before a real project conversation, you can evaluate the thinking depth and working style from these public artifacts.
Best for seeing the problem breakdown, workflow reasoning, and how trade-offs are handled in detail.
Watch YouTubeUse the articles to evaluate how systems are explained, scoped, and reasoned about in a structured way.
Read articlesIf you want to know how I work with teams and what kinds of problems fit best, start here before reaching out.
Open AboutLatest Dispatches
Recent posts spanning Senior Dev × AI, infrastructure, automation, and security labs.

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