Beyond the Simple Assumption
The Three Universal Constraints of a Scalable Coda Doc
When a client first asked me to build a resource planning tool in Coda, I started with a simple use case: hotel rooms. The key assumption was straightforward — a room is for the night, so the logic was anchored to dates. But as the scope expanded, so did the assumptions. I moved to meeting rooms and lockers, which needed to be bookable 24/7. Then came bikes with a fixed operational window, followed by the need to book multiple items at once, like two meeting rooms or five lockers.
This journey taught me a powerful lesson: our initial assumptions are almost always incomplete. It’s easy to build a system that works for a hotel room or a 24/7 locker and assume that same logic will scale. But what happens when you introduce a bike rental business that closes on Sundays and takes a lunch break on weekdays? A truly robust and scalable Coda doc is built on a foundation of explicit, universal assumptions that can handle all of these nuanced scenarios.
The blinking cursor on a blank Coda doc promises limitless possibility, but that’s only half the story. The paradox is that while the blank page offers complete freedom, it also presents a paralyzing lack of structure. Starting from scratch is difficult because it demands a clear, pre-defined vision of your desired outcome and the underlying data architecture. Without that blueprint, it’s easy to make fundamental architectural mistakes that will cause problems later on.
Templates, while helpful, often fail to solve this core problem because they can be rigid and don’t necessarily teach the user how to think structurally. Instead of simply providing a pre-built solution, the true need is for a calm, deliberate process of defining the “rules of the game”. This means taking the time to write down and formalize the logical structure and constraints before building. By first articulating the problem — as I did with the resource booking tool — and listing the core assumptions, any user can transform the blank canvas from a source of anxiety into a space for deliberate creation. This intentional process is what separates a simple document from a robust, production-ready application.
Defining the Core Constraints
To build a single system that handles all of these scenarios, you must stop treating them as separate problems and start formalizing their core assumptions. We discovered that our initial assumption — that every resource, whether a hotel room or a bike, could be treated the same — was a mistake. The reality is that we needed to make our assumptions explicit. This is where the concept of Service Hours comes into play; it’s a critical constraint that makes your Coda doc resilient and scalable, because it accounts for the real-world limitations of a local business run by people, not robots.
Building a robust Coda doc isn’t about conjuring the perfect solution from thin air. It’s about a humble, disciplined process of discovering and defining the rules of your system. You start with a simple idea, and as you confront the messy reality of a client’s needs, you realize you’ve made a host of silent assumptions. This is where the real work begins — the hard, deliberate task of turning those assumptions into explicit, universal constraints.
The Uncomfortable but Essential Questions
Before you can build anything that lasts, you have to ask a few uncomfortable but essential questions. This is a journey of discovery,and for each product or service you want to manage in your doc, you need to define its fundamental constraints:
- Availability Profile: Is this resource always available, or does its access follow a specific schedule? It’s easy to assume a hotel room is simply a “day,” but what about a bike shop that has a lunch break on Tuesdays and is closed on Sundays? Your doc needs to know this. You can handle this with a
Service Hourstable that links to your product. For a 24/7 locker, you can simply leave the fields blank. - Duration Constraint: How long can this item be booked for? A meeting room might have a maximum duration of eight hours, while a bike rental has a limit of seven days. This isn’t just about what’s possible; it’s about enforcing your business rules. By setting a
[Min Duration]and a[Max Duration], you guide your users and prevent bookings that don't make sense for your business, whether they're too short or too long. - Quantity Tracking: Can a user book more than one of this item at a time? This depends on whether your products are interchangeable. You can’t book five unique meeting rooms with a single action, but you can book five identical folding chairs from a stack of 50. Your system needs to differentiate. For interchangeable items, your doc must track the total
[Quantity]available, allowing you to handle multiple bookings in a single transaction.
By formalizing these assumptions into simple, universal variables, you can start building. This foundational work allows you to craft a single, elegant formula that handles any resource type, regardless of its unique constraints. It’s an act of walking step by step, admitting you don’t have all the answers from the start, and it’s the only way to build a Coda doc that truly scales.
The Quest for Maximum Information
The moment you start applying this disciplined approach, a new challenge emerges: how much information do you truly need before you begin? Your first instinct might be to account for every single scenario — holidays, special events, or weather-related closures — but that can quickly lead to over-engineering and a document that’s far more complex than it needs to be.
This is where the list of constraints we’ve defined becomes a powerful diagnostic tool. You don’t need a complex Service Hours table for a product that doesn't require one. If a product, like a locker, is genuinely available 24/7, you simply leave the relevant fields blank and move on. If a company isn't affected by holidays, you can safely skip that entire piece of logic.
The goal isn’t to build the most complex system imaginable; it’s to build the most robust system for the task at hand. By systematically evaluating each product against a checklist of potential constraints — availability profile, duration constraint, and quantity tracking — you can determine precisely which data you need to gather, and which tables and formulas you can safely omit. This disciplined approach ensures you don’t waste time on features you don’t need, allowing you to build a system that is as elegant as it is effective.
The Role of AI: From Builder to Validator
In the future, AI assistants within Coda may dramatically change this process. Instead of you needing to define every constraint and table yourself, you might simply state your objective in plain language, such as, “I need to track students and their classes,” and the AI could automatically infer the correct relational structure, including the need for a third table to join them.
However, this doesn’t remove your role in the process. AI is a brilliant intern, capable of handling the manual clicking and building. But it still requires a human to act as the architect. Your job would evolve from giving the AI detailed, step-by-step instructions to validating and refining its architectural proposal. You would use your real-world business context to check for “architectural hallucinations” and ensure the elegant solution the AI provides is actually the correct one for your needs.
I hope this article was informative and helpful. Did it help you to solve a problem you unlike would have solved other ways? What about a donation?
My name is Christiaan, and I regularly blog about Coda. While this article is free, my professional services (including consultations) are not, but I’m always happy to chat and explore potential solutions. You can find my free contributions in the Coda Community and on X. The Coda Community is a fantastic resource for free insights, especially when you share a sample doc.
