✅ Manage your projects

Oct 23, 2023·
Brian Jalaian, Ph.D.
Brian Jalaian, Ph.D.
· 2 min read
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Easily manage your projects - create ideation mind maps, Gantt charts, todo lists, and more!

Ideation

Hugo Blox supports a Markdown extension for mindmaps.

Simply insert a Markdown code block labelled as markmap and optionally set the height of the mindmap as shown in the example below.

Mindmaps can be created by simply writing the items as a Markdown list within the markmap code block, indenting each item to create as many sub-levels as you need:


```markmap {height="200px"}
- Hugo Modules
  - Hugo Blox
  - blox-plugins-netlify
  - blox-plugins-netlify-cms
  - blox-plugins-reveal
```

renders as

- Hugo Modules
  - Hugo Blox
  - blox-plugins-netlify
  - blox-plugins-netlify-cms
  - blox-plugins-reveal

Diagrams

Hugo Blox supports the Mermaid Markdown extension for diagrams.

An example Gantt diagram:

```mermaid
gantt
section Section
Completed :done,    des1, 2014-01-06,2014-01-08
Active        :active,  des2, 2014-01-07, 3d
Parallel 1   :         des3, after des1, 1d
Parallel 2   :         des4, after des1, 1d
Parallel 3   :         des5, after des3, 1d
Parallel 4   :         des6, after des4, 1d
```

renders as

gantt section Section Completed :done, des1, 2014-01-06,2014-01-08 Active :active, des2, 2014-01-07, 3d Parallel 1 : des3, after des1, 1d Parallel 2 : des4, after des1, 1d Parallel 3 : des5, after des3, 1d Parallel 4 : des6, after des4, 1d

Todo lists

You can even write your todo lists in Markdown too:

- [x] Write math example
  - [x] Write diagram example
- [ ] Do something else

renders as

  • Write math example
    • Write diagram example
  • Do something else

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Brian Jalaian, Ph.D.
Authors
Associate Professor
Dr. Brian Jalaian is an Associate Professor at the University of West Florida and a Research Scientist at IHMC, where he leads cutting-edge work at the intersection of machine learning, AI assurance, and systems optimization. His research spans large language models (LLMs), AI model compression for edge deployment, uncertainty quantification, agentic and neurosymbolic AI, and trustworthy AI in medicine and defense. Formerly a senior AI scientist at the U.S. Army Research Lab and the DoD’s JAIC, Brian has shaped national efforts in robust, resilient, and testable AI. He’s passionate about building intelligent systems that are not only powerful—but provably reliable. When he’s not optimizing AI at scale, he’s mentoring the next generation of ML engineers or pushing the boundaries of agentic reasoning.