Using Diagrams to Enhance Code Understanding

𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲: 𝗦𝘁𝗼𝗽 𝗗𝗿𝗮𝘄𝗶𝗻𝗴, 𝗦𝘁𝗮𝗿𝘁 𝗖𝗼𝗱𝗶𝗻𝗴 Manual diagrams are dead documentation. They rot the moment you save them as "architecture_v2_final.png". Earlier, documenting systems was tedious. You had to draw every line manually and fix messy arrows. Comparing versions meant opening two images and looking closely to find changes. 𝗧𝗵𝗲 𝘁𝗿𝘂𝘁𝗵: If your architecture isn't code, it is invisible to your best tools. 𝗗𝗶𝗮𝗴𝗿𝗮𝗺𝘀 𝗮𝘀 𝗰𝗼𝗱𝗲 turn architecture into a source of truth stored in Git. It is easy to traverse the history and see exactly how the logic evolved over time. Why this is better for the AI era: • 𝗔𝗜 𝗰𝗮𝗻 𝗿𝗲𝗮𝗱 𝗶𝘁: AI tools understand text logic better than pixels. • 𝗙𝗮𝘀𝘁 𝘀𝘂𝗺𝗺𝗮𝗿𝗶𝗲𝘀: Ask AI to summarize a complex system just by reading the code file. • 𝗔𝗜 𝗰𝗮𝗻 𝘂𝗽𝗱𝗮𝘁𝗲 𝗶𝘁: Ask your assistant to "Add a retry loop" and let it update the diagram logic for you. 𝗠𝘆 𝗽𝗲𝗿𝘀𝗼𝗻𝗮𝗹 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄: I use 𝗩𝗶𝘀𝘂𝗮𝗹 𝗦𝘁𝘂𝗱𝗶𝗼 𝗖𝗼𝗱𝗲 𝗽𝗹𝘂𝗴𝗶𝗻𝘀 for these tools. It allows me to stay in my IDE and 𝗰𝗼𝗼𝗽𝗲𝗿𝗮𝘁𝗲 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗖𝗼𝗽𝗶𝗹𝗼𝘁 to generate or refactor complex diagrams in seconds. My toolkit for better design: • 𝗣𝗹𝗮𝗻𝘁𝗨𝗠𝗟: The powerhouse for heavy UML and logic. It also supports MindMap, Network diagram, and ArchiMate. Test it here: https://www.planttext.com/ • 𝗠𝗲𝗿𝗺𝗮𝗶𝗱.𝗷𝘀: Simple syntax for quick flowcharts, uml diagrams, and timecharts. It works natively on GitHub and GitLab. Test it here: https://mermaid.live/ • 𝗠𝗮𝗿𝗸𝗺𝗮𝗽: The best for interactive mindmaps. It is more flexible than Mermaid for hierarchical brainstorming. Test it here: https://lnkd.in/dD4MTz_3 • 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗶𝘇𝗿: The gold standard for the C4 model. It focuses on the underlying software model, not just visual lines. Test it here: https://lnkd.in/dYc2Dw2h 𝗧𝗵𝗲 𝗥𝘂𝗹𝗲: If it is worth building, it is worth versioning. Review your diagrams in your 𝗣𝘂𝗹𝗹 𝗥𝗲𝗾𝘂𝗲𝘀𝘁𝘀 just like your source code. 𝗪𝗵𝗶𝗰𝗵 𝘁𝗼𝗼𝗹 𝗱𝗼 𝘆𝗼𝘂 𝘂𝘀𝗲 𝘁𝗼 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝘆𝗼𝘂𝗿 𝘀𝘆𝘀𝘁𝗲𝗺𝘀? 𝗣.𝗦. Follow me for AI-Driven Integration & MuleSoft tips. #MuleSoft #softwareengineering MuleSoft Community

Your AI just wrote 2,000 lines of code in 3 seconds. And you have no idea if it's taking you in the right direction. Here's the visualization trick that keeps you in control. I discovered this after weeks of drowning in AI-generated code. The problem: AI writes code fast. Really fast. So fast that you lose sight of the bigger picture. Like trying to see a forest while standing inches from a tree. But here's what changed everything for me: I ask the AI to create a mermaid diagram of the application logic. Think of it as an aerial view of your codebase. Every flow, connection, and relationship - mapped instantly. Here's the exact process I use: - Request a mermaid diagram of the entire application flow - View it using any online mermaid viewer - Start a fresh conversation with the AI - Ask it to verify the diagram against your code - Update based on AI's assessment The result? - Crystal clear understanding of complex systems. - No more getting lost in the details. - No more building in the wrong direction. - Just clean, verified architectural maps of your AI applications. — Do you prefer visual maps or diving deep into code? — Enjoyed this? 2 quick things: - Follow me for more AI automation insights - Share this a with teammate 

𝗛𝗼𝘄 𝘁𝗼 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗲 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲? When developing software, it is essential to have a clear plan and understand how different system components will work together. Documentation and diagramming help us to achieve this by providing a 𝘃𝗶𝘀𝘂𝗮𝗹 𝗿𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲. This enables different stakeholders, like developers, testers, and clients, to have a common understanding of the software design. One of the preferred ways to visualize the software architecture is 𝘁𝗵𝗲 𝗖𝟰 𝗺𝗼𝗱𝗲𝗹, developed by Simon Brown, a software architect and author. The C4 model examines a software system's static structures, containers, components, and code. The C4 model consists of 𝗳𝗼𝘂𝗿 𝗹𝗲𝘃𝗲𝗹𝘀 𝗼𝗳 𝗮𝗯𝘀𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻, which are represented by four different types of diagrams: 🔹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 (𝗟𝗲𝘃𝗲𝗹 𝟭): System Context diagram - This diagram shows the system in context, providing an overview of the system and its environment. The system here has the highest level of abstraction, and it shows the system under consideration as a box in the center, surrounded by its users and other systems that interact with it. 🔹 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀 (𝗟𝗲𝘃𝗲𝗹 𝟮): Container diagram - This diagram shows the high-level components or services within the system and how they are connected. It shows each component as a box with its internal details abstracted away, separately deployable or executable. Containers can represent APIs, databases, file systems, etc. 🔹 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 (𝗟𝗲𝘃𝗲𝗹 𝟯): Component diagram - This diagram shows the internal components of a container and how they interact with each other. Here, we can visualize abstractions in our codebase. For example, C # is an implementation class behind some interface. 🔹 𝗖𝗼𝗱𝗲 (𝗟𝗲𝘃𝗲𝗹 𝟰): Code diagram - This diagram shows the detailed structure of a single component or module, including its classes and their relationships. Most teams should, at the very least, produce and keep up-to-date 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝗮𝗻𝗱 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗱𝗶𝗮𝗴𝗿𝗮𝗺𝘀 for their software system. Component diagrams can be made if they are helpful, but you'll need to figure out how to automate changes to these diagrams for long-term documentation needs. #technology #softwareengineering #programming #techworldwithmilan #softwarearchitecture

MERMAID. I use Mermaid for probably 80% of the diagrams I create, here on LinkedIn and at work. It’s a tool that's not very subtly become a staple in my workflow, especially when I need to explain complex technical concepts or workflows or architect a plan. Here is all you need to now to get started on Mermaid diagrams, because they really are one of the most useful tools in my day-to-day work in bioinformatics engineering. If you've not used mermaid before, the appeal is simple: Diagrams as code. Versioned, reviewable, reusable, and close to the logic they describe. (If you don't think you've seen mermaid scripted diagrams before, you must be new to my posts. Welcome!) Mermaid scripts render or show up in more places than you might realise: - GitHub and GitLab READMEs ( and potentially other Git hosting platforms in wikis etc) - MkDocs, Docusaurus, Sphinx and other doc sites - Code editors / IDEs like VS Code - Notebooks and internal developer portals including Quarto and Jupyter - Confluence and other internal wikis - mermaid.live, draw.io and other online renderers That alone makes them useful for keeping architecture and workflows close to the code. The uses of scripted diagrams are super xmapsnive: - You can track them across repos and docs - You can template them or parameterise them - You can refactor diagrams alongside code changes - They survive copy-paste far better than PNGs ever will - No more "this diagram is slightly out of date but it will do". Utilising the power of various renderers and UIs you can make: - The most beutiful animated flows - Cleaner layouts without needing to drag boxes around - Themed diagrams that actually look presentable in docs or slides and can be exported in various formats - Shareable links to diagrams that can be edited and rendered by anyone, without needing to install software or use a specific editor There are a few tools that make a big difference here, especially when you want something more polished than default markdown rendering, ou can include your own (or organisational) branding classes to apply across all diagrams. Mermaid supports a large range of useful diagram types, not limited to. - Flowcharts and decision trees - Sequence diagrams - Git graphs (this one is really fun for the git nerds out there) - State diagrams - Timelines - Gantt charts - Architecture-style dependency graphs A non exhaustive list of uses I have found for these diagram types in my work includes: - Workflow managers and execution paths (FYI: Nextflow and SnakeMake can output DAG as mermaid) - Configuration precedence and overrides - CI pipelines - Infrastructure and data flow - API interactions and sequence diagrams - Project timelines and milestones - Schematcis - Git history and branching strategies #mermaiddiagrams #bioinformatics #engineering #snakemake #nextflow

"LLMs can’t handle complex tasks." You sure about that? Try this: Documentation Driven Development (DocDD). 👨💻 I was troubleshooting a semantic versioning bug in our microservices DevOps pipeline. Instead of jumping into code, I started with: “Step one: draw me a picture.” Why? Because pictures don’t just help me understand the system—they help the LLM understand it too. LLMs are surprisingly good at reasoning about Mermaid diagrams in markdown. The visual becomes a shared language—something we can both use to communicate, debug, and design. ➡️ Step two: We used the diagram to explore possible solutions. ➡️ Step three: The LLM helped generate the code to fix it. Turns out, complex tasks aren’t so complex when you and the AI are looking at the same picture. 🖼️ The image below is a de-identified version of the real problem we solved—just enough to illustrate the power of this approach without revealing anything sensitive. #AI #DocDD #DevOps #LLMs #Mermaid #SoftwareEngineering #PromptEngineering Let me know if you're posting this with an actual image—I can help fine-tune the caption too.

𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐢𝐚𝐠𝐫𝐚𝐦𝐬: 𝐌𝐚𝐤𝐢𝐧𝐠 𝐂𝐨𝐦𝐩𝐥𝐞𝐱 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐚𝐛𝐥𝐞 System diagrams are visual representations of how a software system is structured and how its components interact. They turn abstract ideas into something tangible, making it easier to design, explain, review, and scale systems. Instead of reading pages of documentation, a single system diagram can show: User entry points (Web, Mobile, Admin portals) Services and modules Databases and storage APIs and integrations Data flow and communication paths Infrastructure components (gateways, load balancers, queues) In short, system diagrams help everyone, developers, architects, stakeholders, and clients, see the system as a whole. 🔍 𝐖𝐡𝐲 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐢𝐚𝐠𝐫𝐚𝐦𝐬 𝐌𝐚𝐭𝐭𝐞𝐫 Clarify system boundaries and responsibilities Reveal bottlenecks and single points of failure Improve team communication and alignment Help with onboarding new developers Support better architectural decisions Make discussions faster and more effective A well-drawn diagram often prevents costly design mistakes. 🛠 𝐓𝐨𝐨𝐥𝐬 𝐈’𝐯𝐞 𝐔𝐬𝐞𝐝 𝐟𝐨𝐫 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐢𝐚𝐠𝐫𝐚𝐦𝐬 I’ve personally used: Draw.io (diagrams.net) – simple, fast, and very flexible Miro – great for collaborative design and brainstorming Other popular tools worth mentioning: Lucidchart Whimsical Figma / FigJam Creately Excalidraw Microsoft Visio C4-PlantUML (code-based diagrams) Mermaid.js (diagrams as code) The tool matters less than the clarity of thought behind the diagram. 🧠 𝐖𝐡𝐚𝐭 𝐚 𝐆𝐨𝐨𝐝 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐢𝐚𝐠𝐫𝐚𝐦 𝐒𝐡𝐨𝐮𝐥𝐝 𝐒𝐡𝐨𝐰 Clear entry points and user types Well-defined services or modules Data ownership and storage Communication style (sync vs async) External integrations Scalability and security boundaries It doesn’t need to show everything, only what’s necessary to understand the system at that level. ✨ 𝐅𝐢𝐧𝐚𝐥 𝐓𝐡𝐨𝐮𝐠𝐡𝐭 System diagrams are not just drawings, they are thinking tools. If you can clearly diagram your system, you likely understand it well. If you can’t, that’s usually a sign the design needs more clarity. If you can’t explain it visually, you probably don’t fully understand it yet.

A model is worth 1,000 lines of code. Architecture diagrams aren't documentation. They're decision-making tools that prevent expensive mistakes: 1) Design Intent - Your team understands WHY, not just WHAT 2) Testability - You spot integration issues before hardware exists 3) Maintainability - New engineers onboard in days, not months 4) Scalability - You make the right tradeoffs early I've seen teams spend 3 months refactoring because they skipped this step. I've also seen teams ship complex embedded systems in 6 months because they invested 2 weeks upfront modeling their architecture. The teams that win? They can draw their entire system on a whiteboard. The teams that struggle? They rely on "tribal knowledge" locked in senior developers' heads. If your team can't see the system, they'll never be able to scale it. Start modeling before coding. Your future self will thank you. #EmbeddedSystems #SoftwareArchitecture #Firmware

Writing makes things clearer, it helps you think and visualize non-material concepts. But how does it help software engineers? When you start with a problem, write down what you currently know and what you want to achieve. Think of modules/services, abstract out the functionalities that each module/service will expose, and try connecting the dots between them. Ultimately, your solution will be a set of abstractions for the external world. To implement these abstractions, your modules/services need to communicate over the interfaces they expose and they need to implement them independently. But isn't that too chaotic? How do you visualize all the systems interacting to solve a problem? To visualize my solution, I draw sequence diagrams to understand the flows. Drawing can be tedious and time-consuming, so I use PlantUML. It's an easy-to-learn tool for creating such diagrams from text. I've also encouraged my team members to adopt sequence diagrams for discussing problems within the group. Trust me, it saves time and builds clarity even before you start writing code. #writing #clarity #solutioning #software #engineering #architecture #sequencediagrams #microservices