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Report abuseYour developers are shipping faster than your documentation can keep up. Features launch without guides. APIs go undocumented. New users open support tickets instead of reading docs that don't exist yet.
I fix that.
I'm a technical writer who builds and tests before writing. Before I document a Kubernetes deployment, CI/CD pipeline, or API integration, I run through it hands-on — which is why I maintain a 95% first-submission editorial approval rate and helped one client grow organic traffic by 30% in 6 months.
Over the last 5+ years I've published 100+ technical articles, tutorials, and API references for platforms reaching millions of developers — Baeldung (10M+/mo), Vultr (1M+ devs), Cherry Servers, SmythOS, MCPevals, Hostman, LinuxOpSys, and Warp's Terminus.
I specialize in AI/ML documentation — LLM workflows, agent frameworks, and the Model Context Protocol (MCP) — backed by deep DevOps and cloud-infrastructure chops (Docker, Kubernetes, CI/CD, AWS, bare metal). If your product runs AI in production, I can document both the model and the infrastructure it rides on.
Three pieces that show how I think, not just what I've shipped. Full case studies in my docs-case-studies repo.
DevOps · decision framework · 10M+ monthly readers
A cornerstone reference on CI/CD covering build reliability, secrets, observability, and deployment patterns. Written for senior engineers designing pipelines, not just configuring them.
Kubernetes · observability · AI infra foundation
Hands-on guide pairing PromQL with the K8s metrics model. Foundational for anyone running inference or training workloads on Kubernetes.
Architecture · decision doc · senior-engineer audience
A head-to-head that engineering leads can hand to their team to make an actual platform choice. Covers operational cost, compliance, and day-2 ops — not feature bullets.
Browse all published work — 100+ articles across 9 platformsProduct walkthroughs, feature demos, and code-along screencasts that pair with written docs to cut onboarding time and reduce support load.
AI/ML: OpenAI · Anthropic · LangChain · Model Context Protocol · Prompt engineering · RAG DevOps & Infra: Docker · Kubernetes · Jenkins · GitHub Actions · GitLab CI · Ansible · Terraform Cloud: AWS · Azure · Linux administration · Bare metal Docs tooling: Markdown · MkDocs · Docusaurus · Hugo · Confluence · Git API tooling: OpenAPI/Swagger · Postman Languages: Python · JavaScript · Bash · YAML · JSON
Every number below is tied to a real engagement — client names available on request.
What clients say on Upwork (from verified reviews):
"Emmanuel is awesome to work with. He needs minimal direction, does the work, meets the deadline, and there's no drama and no issues. I'm a returning customer." — Technical book editor · Python / Java / SQL / JavaScript project
"Knowledgeable and fast worker." — AI Agent Development client (SaaS)
"He followed what I asked for to a tee, and the deliverable met my expectations." — Coding-book ghostwriter · Python
Upwork-verified client tags from my reviews: Committed to Quality · Reliable · Collaborative · Accountable for Outcomes · Clear Communicator · Detail Oriented.
Response time: 0–4 hours · Availability: 30+ hrs/week · Time zones: US / EU friendly · Open to: contract-to-hire
If your product is technical and your docs don't match, let's fix that.
Case studies of technical documentation I've shipped — the brief, my approach, and outcomes.
This simple project demonstrates how to containerize a Node.js Express application using Docker. It includes a basic Express server, a Dockerfile, and clear instructions.
JavaScript 1
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