Documenting Engineering Solutions

Documentation is one of the most underrated tools in the knowledge worker's kit. Not for compliance. Not for process. But for thinking. It helps us do something seemingly contradictory - hold ambiguity and seek clarity at the same time. When you write down raw thoughts, open questions, or fragmented facts, you’re not just recording - you're revealing. Assumptions surface. Blind spots show. New questions emerge. When you answer those as a self-FAQ, it might feel remedial - but that’s how rigor is built. Documentation invites multiple lenses. It lets ideas evolve. The version history doesn’t just track changes - it shows the evolution of thought. Even if we leap to solutions too fast, it becomes a grounding anchor: “Here’s one path. We’re still thinking.” And perhaps most crucially - it saves hours of meetings. One good doc becomes a shared context, kills tribal knowledge, and becomes an onboarding gift for every future collaborator. When decisions are made, the reasoning doesn’t vanish - it lives in the document. Clarity, scale, and transparency - all in one place. And now, with AI in the loop, it gets even better. AI helps wordsmith, brings external sources, asks provocative questions, and pushes your thinking - all in real time. Whether it’s a Google Doc, a FigJam board, or a messy Figma scratchpad - the solution unfolds as you think, question, and shape. By the time the final design is done, every breadcrumb of the journey is archived. For history buffs and new teammates alike, the ramp-up becomes instant. If Amazon added one chromosome to my DNA, it’s this one — documentation-first thinking. I’m forever grateful for it. #musings

Career advice I’d give my younger self: Keep a record of your wins Document your accomplishments as you go - not just what you did, but the real impact. (Keep this in a personal repository, not at work.) Most of us move from project to project, thinking we’ll remember the details when we need them. Then, when it’s time for a job search or a performance review, we struggle to articulate our impact. Instead, whenever you start a new project, ask yourself: “How will my future self talk about this?” Think in terms of a story - a problem worth solving, a difficult and challenging solution, and a meaningful transformation. You don’t have to wait until the project is finished to start writing it. Step 1: The problem What problem are you solving? A (business) problem worth solving has the problem itself, which lead to symptoms that, if they aren't addressed, can lead to disaster. For example, you might be replacing a legacy workflow. The old workflow is slow and includes manual steps. This results in errors and customer dissatisfaction, which leads to financial risk (due to errors) and churn, resulting in stagnant revenue and declining market share. You'll get more insight over time, but just start at the start. Write down what you know. Step 2: Document the outcomes you (or your leadership) are expecting or hoping for You may not know the final impact yet, but you have a hypothesis. What will change if your project succeeds? More revenue? Higher efficiency? Customer satisfaction improvements? Write that down. The transformation is often the opposite of the problem: if revenue is stagnant, the goal is growth. If churn is rising, the goal is retention. Define the ideal outcome early. Step 3: Capture the key components of the solution As technologists, we naturally document what we built. That’s fine, but remember—hiring managers and execs care less about features and more about impact. And how you collaborated and persuaded stakeholders to create and keep alignment. Step 4: Update your story as you go As your project progresses, go back and update: ✔ What you learned about the real problem ✔ Changes in your approach ✔ The actual results once customers started using your solution Often, the results blossom in unexpected ways - leading to social proof like customer stories, awards, or internal recognition. Capture those. These stories become the basis of a resume that gets interviews and they're great for performance reviews.

𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗮 𝗯𝗲𝘀𝘁-𝗶𝗻-𝗰𝗹𝗮𝘀𝘀 𝗣&𝗜𝗗 𝘀𝗵𝗼𝘂𝗹𝗱 𝗶𝗻𝗰𝗹𝘂𝗱𝗲 (𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝗶𝘁 𝘀𝗵𝗼𝘂𝗹𝗱𝗻’𝘁) In engineering documentation, few deliverables are as critical as the P&ID. Done right, it’s a comprehensive control and design reference, central to safe operations, commissioning, interlock logic, HAZOP reviews, and maintenance planning. What Should a P&ID Contain? ✔️ Process Equipment Tags: Every pump, exchanger, reactor, vessel, and tank must be shown with unique IDs consistent with the master equipment list. ✔️ Piping Configuration: Includes line sizes, direction of flow, reducers, tie-ins, drains, vents, and bypasses. Each line tagged with a Line Number matching the line list (NPS, spec, fluid, insulation, tracing, etc.). ✔️ Instrumentation and Control Loops: Fully looped instruments (FT, FC, FV, etc.) shown with correct connection type (field-mounted, remote, or panel). Loop numbers should match I/O databases and DCS/PLC tags. ✔️ Control Strategy and Mode: Indicate which valves are locally operated, remotely controlled, or interlocked. Annotate automatic actions during trip conditions, batch sequences, or startup logic. ✔️ Shutdowns, Trips, and Safety Functions: Critical interlocks, ESD logic, and fail-safe conditions (FC/FO) must be clearly displayed. Especially for SIL-rated loops, SIF paths should be traceable from sensor to final element. ✔️ Line Connections to Other Systems: Show boundary limits, tie-ins, interfaces to utilities, and process integration points across P&ID sheets. Use off-page connectors with consistent references. ✔️ Flush, Sample, and Blowdown Lines: Often neglected, these auxiliary lines are critical during commissioning, CIP/SIP, or emergency isolation events. 🚫 What a P&ID Should NOT Include: - Detailed isometrics or fabrication fittings (elbows, tees) - Pipe wall thicknesses or material specs (refer line class index) - Electrical wiring or power distribution (handled in single-line diagrams) - Instrument datasheets or rating tables (handled via instrument index) Why It Matters? Improperly defined P&IDs result in: • Installation errors and field rework • Incomplete HAZOP analysis • Inconsistent automation logic • Costly re-commissioning delays Well-structured P&IDs help align process design, mechanical engineering, and control systems reducing ambiguity and risk across the project lifecycle. 📌 Engineers, what's the most overlooked detail you wish was always captured in a P&ID? Let’s discuss in the comments👇 #ProcessEngineering #PID #Instrumentation #Engineering #Technology #Chemicalengineering #Chemicalengineer #Mechanicalengineering #PipingDesign #ProcessControl #HAZOP #PlantDesign #EngineeringStandards

✅ Good Design Must Be Proven — Not Just Modeled In previous posts, I talked about how CAD isn’t design, and how real design equals CAD + thinking + experience. But even the smartest design means nothing if it’s not validated — and communicated. Here’s how great engineers close the loop between design and delivery: ⸻ 🔍 1. Validate the Design — Beyond the 3D Model A nice model is not enough. A real design must prove it works. 🧠 Functional calculations (static, thermal, fatigue, tolerancing…) 🖥️ Simulation tools (FEA, CFD, motion analysis) 🧪 Physical prototyping and testing (because reality always surprises you) ⸻ 📐 2. Document Clearly No matter how brilliant your concept, it’s useless if no one else can build it. 🔹 Functional drawings with tolerances 🔹 Assembly diagrams and exploded views 🔹 Full and clean Bill of Materials (BOM) 🔹 Specifications for materials, finishes, and coatings ⸻ 🗣️ 3. Communicate With All Stakeholders A design is never used alone — so speak the right language: 🔧 For manufacturers: be precise and realistic 📦 For supply chain: give specs and constraints 🧑💼 For clients: highlight value and use-case 📈 For QA & PM: explain your intent and risks ⸻ 🔁 4. Use Feedback — Improve It Good design is iterative. Accept feedback from tests, production, or field use. The best products evolve — based on real performance, not assumptions. ⸻ 🧠 Bottom line: Great design is not just built — it’s proven, explained, and improved. #MechanicalDesign #DesignValidation #EngineeringCommunication #ProductDevelopment #FEA #CAD #TechnicalDrawing #EngineeringDocumentation #MechanicalEngineering #DesignProcess #DFM #Simulation #Prototyping

Learn to document your processes, your reasoning. Future you will not remember why you made specific analytical choices, how you handled edge cases, or what assumptions you built into your projects. When stakeholders ask for "something similar to last year's analysis," you'll waste days trying to reverse-engineer your own thinking instead of building on documented knowledge. Documentation feels like overhead when you're focused on solving problems, but it becomes essential when you need to recreate, modify, or explain your work months later. Write documentation for the person who will inherit your work, even if that person is you six months from now. Your future self will thank you for explaining your current self's reasoning. (No, you won't remember it next week).

Hazal Mestci at Oso took an approach to documentation modernization that I think more engineering teams should consider. She treated docs infrastructure with the same rigor as production systems. The problem? Their documentation platform (Nextra/React) had become a liability. Unmaintained dependencies meant security vulnerabilities were piling up, navigation was confusing, and content was verbose. The platform was actively hurting the developer experience they were trying to enable. The opportunity became clear. Rather than patching an aging system, they saw a chance to rethink their entire documentation strategy. This meant not just the tooling, but the information architecture and content quality. After evaluating Mintlify and other vendors, they chose our platform. But the real work was in the migration itself. What made this successful? 📊 Audited 200+ pages of existing content 🗺️ Created comprehensive URL mappings for zero downtime migration ✍️ Rewrote content for clarity rather than just moving it over ⚡ Leveraged built in features like visual editor and AI search 🔒 Stabilized on a secure, maintained platform The results speak for themselves. Faster load times, improved searchability, better collaboration workflows, and simplified maintenance. More importantly, they've set themselves up for sustainable documentation practices going forward. What stands out to me is how Hazal approached this as a holistic DX problem rather than just a tooling swap. The platform matters, but so does the content strategy, information architecture, and migration execution. If your docs platform hasn't been updated in years and you're accumulating technical debt in your documentation stack, it might be time to consider whether you're just maintaining the status quo or actively improving your developer experience. Link to the full blog post in the first comment below 👇

As an SDE, writing clean code is vital, but writing clear documentation is just as crucial. Good documentation bridges gaps between technical and non-technical teams, aligning everyone and ensuring your work leaves a lasting impact. If it isn’t clear enough for a non-SDE to understand, it’s not complete. 𝐓𝐡𝐞𝐬𝐞 𝐚𝐫𝐞 𝐬𝐨𝐦𝐞 𝐭𝐢𝐩𝐬 𝐈 𝐮𝐬𝐮𝐚𝐥𝐥𝐲 𝐟𝐨𝐥𝐥𝐨𝐰 𝐰𝐡𝐢𝐥𝐞 𝐰𝐫𝐢𝐭𝐢𝐧𝐠 𝐝𝐞𝐬𝐢𝐠𝐧 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐬: 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗕𝗮𝘀𝗶𝗰𝘀: Overview: Briefly describe the purpose of the document. Why does this solution matter? Objective: State clear goals and expected outcomes. Avoid technical jargon. 𝗜𝗻𝗰𝗹𝘂𝗱𝗲 𝗮 𝗚𝗹𝗼𝘀𝘀𝗮𝗿𝘆 Define technical terms or abbreviations (e.g., SQS, SNS). Don’t assume everyone knows them. 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝘁𝗵𝗲 '𝗪𝗵𝘆' Background: Explain the context, problem, or gap your design addresses. Motivation: Highlight what’s driving the need for this solution and its potential impact. 𝗕𝗿𝗲𝗮𝗸 𝗗𝗼𝘄𝗻 𝘁𝗵𝗲 '𝗛𝗼𝘄' 𝗖𝗹𝗲𝗮𝗿𝗹𝘆 Use High-Level Design (HLD) diagrams to visualise the flow. Add a Low-Level Design (LLD) section for SDEs to delve into technical details. 𝗕𝗲 𝗨𝘀𝗲𝗿-𝗖𝗲𝗻𝘁𝗿𝗶𝗰 Write Functional Requirements from the perspective of the end user (e.g., “As a customer, I should…”). 𝗕𝗮𝗹𝗮𝗻𝗰𝗲 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝗻𝗱 𝗡𝗼𝗻-𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀 Include specifics like performance SLAs or scalability needs to align expectations. 𝗦𝗵𝗼𝘄 𝗗𝗮𝘁𝗮 𝗙𝗹𝗼𝘄 Use visual aids like flowcharts to make complex processes easy to understand. 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 𝗘𝗱𝗴𝗲 𝗖𝗮𝘀𝗲𝘀 𝗮𝗻𝗱 𝗟𝗶𝗺𝗶𝘁𝗮𝘁𝗶𝗼𝗻𝘀 Be upfront about known issues and trade-offs. It builds credibility and prepares readers for challenges. 𝗦𝘂𝗺𝗺𝗮𝗿𝗶𝘇𝗲 𝗧𝗿𝗮𝗱𝗲-𝗢𝗳𝗳𝘀 Compare alternative solutions (e.g., Lambda vs. Poller) with pros, cons, and costs. This is invaluable for decision-makers. 𝗪𝗿𝗶𝘁𝗲 𝗳𝗼𝗿 𝗬𝗼𝘂𝗿 𝗔𝘂𝗱𝗶𝗲𝗻𝗰𝗲 Use plain language for non-technical readers. Reserve code snippets and technical details for appendices or LLD sections. 𝗘𝗻𝗱 𝘄𝗶𝘁𝗵 𝗙𝘂𝘁𝘂𝗿𝗲 𝗣𝗹𝗮𝗻𝘀 Show the roadmap to inspire confidence in your solution’s scalability. What’s your approach to writing effective documentation? Share your tips below! 🚀 #SoftwareEngineering #TechDocumentation #DesignDocs #CleanCode #DeveloperLife #EngineeringBestPractices #TechnicalWriting #ScalableSolutions #SDESkills #ClearCommunication

In any data analytics project, documenting your work will save a lot of headaches in the long run. One of my favorite ways to do that is by using my a well written README file. Think about the README file as a “fools proof” recipe, where anyone can read and understand what your project is about. Here is what you can include: ⭐️ Project Overview: Start with a description of what the project goals are. In here you can put the scope of your analysis. ⭐️ Data Sources: Provide an overview of where the data comes from. This is specially helpful if you have multiple sources of data. ⭐️ Project Structure: Explain the organization of the project’s files and directories. This helps users know where to look for scripts, datasets, and outputs. ⭐️ Assumptions and Limitations: State any assumptions made during the analysis and acknowledge the project’s limitations, such as data quality or model constraints. ⭐️ Version Control: Maintain records of code and dataset versions to track changes and revert if necessary. ⭐️ ETL/Processing Pipelines: Document each step in data extraction, transformation, and loading processes, including the rationale behind any data cleaning, filtering, or transformation decisions. ⭐️ Business Logic: Clarify how the data connects to the business logic. For instance, how missing data is handled or the logic behind specific business rules applied to the data ⭐️ Analysis and Insights Documentation: Be clear about how the analyses was performed, which models were used, and how that relates to the project goals. This helps future users or team members understand how conclusions were reached. A solid documentation takes time. Remember that those tips are good not only for your coworkers, but your future self will also thank you Be curious and keep on nerding 😊

🌈 P&ID’s Development Procedure ✴️ Streamlining the Path to P&ID Excellence In the world of process engineering, precise documentation is crucial for success, safety, and operational efficiency. Developing a comprehensive Piping and Instrumentation Diagram (P&ID) is at the heart of every project, ensuring clarity in design and execution. I recently reviewed an extensive P&ID Development Procedure that encompasses: 🌈 General guidelines and scope ✴️ Drafting systems, symbols, and legends ✴️ Equipment layouts and P&ID workflows ✴️ Revision controls and on-site management ✴️ Detailed piping arrangements From twin unit P&IDs to intricate steam turbine piping arrangements, each section emphasizes meticulous planning and collaborative workflows. One of the most valuable aspects is the focus on: ✔️ Bypass and block valve arrangements ✔️ Utility distribution layouts ✔️ Safety elements like purge systems on flare headers ✔️ Control valve setups and instrumentation numbering The document's robust structure ensures nothing is left to chance—covering every critical element of process design, from thermowell arrangements to steam turbine descriptions. It also features helpful attachments and examples for distribution to users, making it a key resource for engineers working on complex systems. 🌈 Why is P&ID development so vital? Clear, accurate P&IDs enhance communication between teams, simplify troubleshooting, and optimize lifecycle management of process systems. For engineers, they’re not just drawings—they’re roadmaps to operational success! What’s your experience with P&ID workflows? How do you ensure seamless collaboration during development? Let’s discuss!

This is day 4 -- Documents that Product Managers should master Product Requirements Document (PRD) 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮 𝗣𝗥𝗗 A document that includes details about a specific feature, solution, or product. It acts as the central point of information for engineers to understand the solution, and translate it into code. 𝗪𝗵𝘆 𝗮𝗿𝗲 𝗣𝗥𝗗𝘀 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 1. Common understanding: PRDs lay the foundation of common understanding. It ensures engineer's understanding of "what" to build is the same as that of the PM's 2. Agreement: PRDs also act as a contract between PMs and engineers on the specifics of the solution that will be built. It is also an agreement on the quality and success of the solution. 3. Scope: PRDs define what is IN scope. Great PRDs also define what is OUT OF scope. 4. Clarity: PRDs provide a high level of depth into the idea, ensuring low ambiguity 5. Reference: PRDs act as reference for PMs, engineers, stakeholders who want to know why, what, when a feature / solution was developed 𝗪𝗵𝗮𝘁 𝘁𝗼 𝗶𝗻𝗰𝗹𝘂𝗱𝗲 𝗶𝗻 𝗣𝗥𝗗𝘀 A great PRD includes what is important for the team. A few things that I always include: 1. 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝘀𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁 𝗮𝗻𝗱 𝘀𝗶𝘇𝗶𝗻𝗴: The problem that we're solving via this solution. What is the impact of solving this problem. 2. 𝗧𝗮𝗿𝗴𝗲𝘁 𝘂𝘀𝗲𝗿𝘀: mention all users that you could be targeting, and then explain why you have chosen the persona that you have. 3. 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀 (𝗙𝗥𝘀): this is the most critical and lengthy section. It covers 70-80% of the document. It contains a very high degree of detail about every aspect of the of the product. 4. 𝗡𝗼𝗻 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀 (𝗡𝗙𝗥): NFRs are requirements that are not necessarily visible or usable for the end user. Ex: "Netflix must be available 99.99% of the time, allowing users to access content seamlessly without interruptions" 5. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗣𝗹𝗮𝗻: list of tests that have to be passed before the solution can be launched 6. 𝗔𝗰𝗰𝗲𝗽𝘁𝗮𝗻𝗰𝗲 𝗖𝗿𝗶𝘁𝗲𝗿𝗶𝗮: is a checklist, in which every check is critical to be met before the product launvh 7. 𝗢𝗽𝗲𝗻 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀: there will always be open questions. Document them in a separate section. It is important for readers to know that you have considered all questions 𝗠𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝘁𝗼 𝗮𝘃𝗼𝗶𝗱 1. Don't treat PRDs as a static document: PRD is not a one and done document. It is an evolving document. Based on your discussions, feedback, questions, you should update it to keep it relevant and impactful. 2. Make sure there is no ambiguity: Be very sure to reduce / remove ambiguity. Anything you leave for interpretation, will always be interpreted incorrectly. -- That is it for today. Stay tuned for Day 5, where we talk about user stories. If you haven't already, please follow me Sid Arora