# Living with AI — Elena Daehnhardt's Blog

> AI, Python coding, and machine learning blog by Elena Daehnhardt (PhD, Computer Science, Heriot-Watt University) — practical tutorials, tool reviews, and honest field notes from a machine learning engineer and researcher.

Elena writes about applied AI, Python, and machine learning, plus the tools and workflows around them. The series below are the best entry points into a topic — each is a structured, multi-part guide meant to be read in order. Individual blog posts (linked from each series, and from https://daehnhardt.com/) cover specific tools, tutorials, and experiments in more depth.

## Series

- [AI Challenges, Questions, Law and Ethics](https://daehnhardt.com/series/ai-challenges-questions-law-and-ethics/): A practical reading path on AI risks, regulation, trust, and broader societal questions.
- [AI Coding Assistants & IDE Workflows](https://daehnhardt.com/series/ai-coding-assistants-ide-workflows/): A practical series on AI coding assistants, IDE workflows, and real-world developer setups.
- [AI Image Generation in Practice](https://daehnhardt.com/series/ai-image-generation-in-practice/): A practical series on AI image generation, from prompts to production workflows.
- [AI Orchestration with LangGraph](https://daehnhardt.com/series/ai-orchestration/): A complete practical guide to building production-ready AI workflows with LangGraph, Ollama, OpenAI supervision, MCP tool isolation, and human approval gates.
- [AI Productivity Workflows](https://daehnhardt.com/series/ai-productivity-workflows/): Hands-on workflow posts for automation, local AI labs, and practical delivery systems.
- [AI Safety](https://daehnhardt.com/series/ai-safety/): Security and privacy practices for AI systems, assistants, and infrastructure.
- [AI Terms Explained](https://daehnhardt.com/series/ai-terms-explained/): A plain-English glossary series translating AI and LLM jargon into everyday analogies, from foundational terms to the vocabulary of a real model release.
- [Applied ML & Model Engineering](https://daehnhardt.com/series/applied-ml-model-engineering/): Applied machine learning in practice: real datasets, model engineering, evaluation, and the tools that turn ideas into working systems.
- [Codex CLI](https://daehnhardt.com/series/codex-cli/): A complete four-part guide to mastering Codex CLI, OpenAI's coding agent for your terminal.
- [Creative AI Tools](https://daehnhardt.com/series/creative-ai-tools/): Explorations of generative AI tools for voice, avatars, creative projects, and experimentation.
- [Generative AI Applications](https://daehnhardt.com/series/generative-ai-applications/): Practical, real-world use cases of generative AI apps in everyday workflows.
- [GitHub Pages](https://daehnhardt.com/series/github-pages/): A complete guide to hosting, designing, and testing your blog with GitHub Pages, from first setup to a live custom domain.
- [Git Survival Guide](https://daehnhardt.com/series/git-survival-guide/): Practical Git and GitHub workflows for daily development: recovery, collaboration, and troubleshooting.
- [Machine Learning](https://daehnhardt.com/series/machine-learning/): A structured path from beginner ML foundations to modern fine-tuning workflows.
- [Managing Emails](https://daehnhardt.com/series/managing-emails/): A practical series about cleaning, automating, and intelligently managing email using Gmail tricks, AI tools, and Python automation.
- [MLOps & Deployment](https://daehnhardt.com/series/mlops-deployment/): Shipping models and apps: Docker, CI/CD, runtimes, DNS, and the deployment plumbing that takes a project from localhost to live.
- [Neural Network Architecture](https://daehnhardt.com/series/neural-network-architecture/): A multi-part guide to modern neural network architecture, from residual connections to frontier research.
- [Python Basics](https://daehnhardt.com/series/python-basics/): A practical series on Python foundations for real projects, from core scripting to machine-learning-ready workflows.
- [Python Projects & Utilities](https://daehnhardt.com/series/python-projects-utilities/): Applied Python posts covering utilities, Flask projects, environments, and development practices.
- [Technical Blogging & SEO Systems](https://daehnhardt.com/series/technical-blogging-seo-systems/): Building and growing a technical blog: writing systems, SEO, analytics, and the tools that bring readers back.

## Key pages

- [Home](https://daehnhardt.com/): Latest posts and blog overview.
- [All series](https://daehnhardt.com/series/): Index of every multi-part series on the blog.
- [About Elena](https://daehnhardt.com/blog/2021/10/20/edaehn-about-me/): Author bio — PhD in Computer Science (Heriot-Watt University), machine learning engineer and researcher specialising in social data mining, adaptive web applications, and deep learning.
- [Contact](https://daehnhardt.com/contact/): Get in touch with Elena.

## Optional

- [Sitemap](https://daehnhardt.com/sitemap.xml): Full, auto-generated list of every published URL on the site.
- [RSS feed](https://daehnhardt.com/feed.xml): Subscribe to new posts.