Make Better Build vs Buy Calls for Engineering Teams
Engineering leaders constantly face the critical decision of whether to build custom solutions or buy existing tools. This article presents a strategic framework for making these high-stakes choices, backed by insights from seasoned experts who have navigated these decisions at scale. The twelve principles outlined here will help teams allocate resources effectively and maintain competitive advantage.
Build What Creates True Differentiation
We built our core capability in house and it was the hardest, slowest, and most important decision I have made as a founder.
Simply Noted makes handwritten notes using proprietary robotic pens. When I started in 2018, the obvious move was to buy existing pen plotting hardware and customize it. Plenty of machines could hold a pen and drag it across paper. Launching that way would have saved us months.
I chose to build because every off the shelf option had the same problem. The output looked mechanical. Letters were too uniform, pressure too consistent, and anyone picking up the card could tell a machine wrote it. Our entire value depends on notes looking like a real person wrote them. If we could not control pen pressure and stroke variation at the hardware level, we did not have a product.
That decision cost about 18 months of extra development. But today we hold six patents pending and no competitor can replicate what our machines produce. The handwriting passes what I call the grandmother test. Show it to someone's grandmother and she believes a person wrote it.
The lesson is straightforward. If the capability is the thing your customers are actually buying, build it and own every piece. If it is a supporting function like billing or analytics, buy the best tool you can find and move on. The distinction is whether it touches your core differentiation.
Choose Moats, Calculate Opportunity Cost
I burned $400,000 building custom warehouse management software in 2016 when I should have bought off the shelf. That mistake taught me the framework I still use today.
Here's what happened. My fulfillment company was scaling fast and our existing WMS felt clunky. I convinced myself we were special, that our workflows were so unique we needed proprietary tech. We hired developers, spent six months building, and ended up with software that did 80% of what the $30,000 annual SaaS product already did. Worse, we now owned the maintenance burden. Every time a carrier changed their API or a client wanted an integration, my team was on the hook.
The decision cost us more than money. It cost focus. While I was managing developers and debugging code, competitors were optimizing operations and winning clients. I was playing CTO instead of CEO.
Now my filter is simple: build only what creates defensible competitive advantage that customers will pay more for. Everything else, buy. When I started Fulfill.com, people asked why we didn't build our own CRM or payment processing. Because Salesforce and Stripe do it better than I ever will, and zero customers care if I built my own billing system.
The trap is thinking speed to launch is the only variable. It's not. The real cost is opportunity cost over three years. That custom WMS? If I'd bought the SaaS product, I could have spent those six months signing ten new clients instead of writing code. The revenue gap compounded.
One question changed how I evaluate these decisions: Will owning this capability in five years be worth more than what I could build with that time and capital deployed elsewhere? For my fulfillment company, custom WMS wasn't. For Fulfill.com, our matching algorithm absolutely was. That's our moat.
The irony is that the best build versus buy decisions feel boring. You buy the stuff that works and build the thing only you can build. Most founders get that backwards because building feels like progress. Sometimes writing a check is the bravest move.
Keep Method, Control Proof and QA
When I decide build versus buy, I start with one question: is this capability how we win clients, or just how we keep the lights on? At Scale By SEO our edge is search visibility through full site audits, Google Business Profile management, citations, backlinks, blog content, and the consistent monitoring behind our six-month performance guarantee on Pro, Elite, and Enterprise plans. That delivery method deserves long-term ownership even when we rent software underneath.
Speed to launch still drives half the call. Small businesses and professional services can't sit idle while we custom-build every internal tool. I buy when the product is proven, pricing is predictable, and we can export data and swap vendors without breaking client reporting. I build, or more often build a thin internal layer on top of off-the-shelf tools, when the workflow is unique to how we prioritize fixes, communicate progress, and hit agreed KPIs.
One past decision still shapes every criteria discussion: we bought an all-in-one SEO platform to accelerate audits and dashboards. We went live fast and sales conversations looked sharper. Then local SEO and GBP priorities shifted and we couldn't reshape the workflow without waiting on their roadmap. We had time to market on day one and less control exactly when performance guarantees were on the line.
That's why my rule today is simple and I share it plainly with stakeholders: rent commodities, own the checklist, QA, and proof. If we can't walk away in thirty days with intact data and the same standards, that vendor doesn't become the core of how Scale By SEO delivers. We integrate best-in-class tools and keep our method, guarantees, and accountability in-house.
Buy Plumbing, Guard Clinical Expertise
I weigh build versus buy by asking whether the capability carries our clinical judgement or simply helps us move faster. For example, I would not outsource the way we explain blister prevention, dressing choice or product suitability, because that comes from 30 years in podiatry and sits at the heart of trust. But I will buy tools for payments, fulfilment, email flows or stock alerts if they save time and protect the customer experience. A past lesson came when we tried to make a generic support tool fit our blister advice workflow. It saved admin time, but it did not understand clinical risk, so we kept the tool for routing enquiries and kept advice review in house. My rule now is simple: buy the plumbing, own the expertise.
Assign Ownership, Set SLAs First
I weigh long-term ownership against time to launch by testing whether we can assign a single accountable owner and explicit service standards before we commit to building. One lesson that now shapes our criteria comes from reorganizing loan operations: giving each file a single "deal captain" with decision authority and a published definition of done dramatically improved outcomes. As a result, we require an accountable owner, SLAs, and kill criteria to be defined up front for any build decision. If those controls cannot be secured, we favor buying to meet time-to-launch needs.
Source Tools, Command the Playbook
My build versus buy rule is simple: buy the commodity capability, build the operating discipline around it. I would not build my own model or agent platform just to prove ownership, because speed matters when the market is moving. But I do want to own the workflow: how context is gathered, how requirements are approved, what humans review, and where risk gets escalated.
One lesson that shaped this was using Claude and Manus instead of trying to build everything internally. The value was not the tool alone. It was the internal process we built around it, with clear requirements registers, human approval points and repeatable delivery standards.
Prioritize Workflow, Favor Speed and Reliability
When deciding whether to build a solution or use a third-party application, you need to consider whether it is a commodity or a competitive advantage. Based on my experience with digital experiences and BPO operations, I've seen most companies make the mistake of creating an infrastructure internally when the function is a common practice in the industry. By building a tool that does exactly what several existing solutions do, you are not only incurring the expense of developing it but you are also taking on a long-term maintenance cost that removes your best engineering talent from addressing unique issues.
I categorize projects based on their effect on customer experience. If new technology is going to create differentiated interactions with our customers that are fundamental to our brand identity, or if it is a unique and complex customer need (like an AI-powered workflow for processing healthcare claims), then it's a build. We have complete control, will continue to iterate based on our unique operational requirements, and control the data layer. Conversely, if the function is a support function (such as a basic ticket routing solution or a standard reporting dashboard), we buy the solution. From my previous operations, the most successful deployments usually reward speed to market and reliability over poor coded customizations.
Additionally, I have a guiding principle from an earlier project: We once delayed a launch by several months to develop a custom dashboard because we wanted it to look a certain way. After we launched, we learned that agents preferred to use a third-party dashboard that integrated into their workflow. This delay caused us to lose both time-to-market and customer confidence. Now I prioritize user workflow over my desire to maintain complete control.
When I can find an existing application that will meet 80% of my needs, I buy it and concentrate my internal resources on meeting the remaining 20%—the proprietary portion of the solution that will enhance the overall customer experience. Build the experience's soul and buy the infrastructure to support it.
Adopt Infrastructure, Focus on Value Layer
The question we always come back to is: is this capability part of what makes our product different, or is it just infrastructure? If it's the former, we build it. If it's the latter, we find the best existing solution and move on. Spending engineering time rebuilding something that's already been solved well is just a distraction.
The lesson that shaped this for us was around audio processing early on. We had a conversation about whether to build our own transcription layer from scratch. The honest answer was that transcription itself isn't our differentiator. What we do with the transcript afterwards, how we analyse it through the lens of an accounting conversation and turn it into something genuinely useful, that's where our value is. So we made the call to use proven infrastructure for the transcription piece and put our energy into the layer on top. That decision probably saved us months and let us focus on what actually mattered.
Treat Dependence Risk as a First-Class Factor
I weigh build versus buy by asking one blunt question first: if this capability works extremely well, does it become part of why customers choose us and stay with us? If the answer is yes, I lean toward building it in house, even if the first version is narrower. If it is important but not differentiating, I prefer buying so we can launch faster and preserve attention for the parts of the product that actually create leverage.
As a SaaS founder working on AI-driven creator tools and content workflows, I have learned that speed to launch matters most when you are still validating demand, but ownership matters most once a capability starts shaping your margins, roadmap, reliability, or customer experience. In practice, my filter is usually: build for strategic differentiation, unique workflow logic, or anything tightly connected to pricing power; buy for payments, basic analytics, commodity infrastructure, and supporting tools that can be swapped out without breaking the product.
One lesson that now strongly shapes my criteria came from relying too heavily on third-party components early because they got us to market faster. That was the right move at first, but later we discovered that one dependency sat too close to the user experience and product economics. Every change in pricing, limits, or roadmap on their side affected our own plans. We had effectively outsourced part of our flexibility. Since then, I treat "future dependence risk" as a first-class factor, not an afterthought.
So my current rule is: buy to learn, build to own the advantage. I am comfortable renting a capability during the validation phase, but if it becomes central to customer value, data ownership, performance, or cost control, I want a path to bring it in house before it turns into a constraint. The real mistake is not buying early. The mistake is failing to revisit that decision once the capability becomes core.
Shape the Experience That Drives Preference
I'm Runbo Li, Co-founder & CEO at Magic Hour.
The default answer in most startup advice is "buy everything, move fast, don't reinvent the wheel." That's wrong if the thing you're buying sits in the critical path of your product experience. My rule is simple: if it touches the user and defines how they feel about your product, build it. If it doesn't, buy it yesterday.
Here's the lesson that burned this into my brain. Early on, we evaluated using a third-party video rendering pipeline. It would have saved us weeks. The integration was clean, the docs were solid, and on paper it was the rational choice. We almost pulled the trigger. But we realized that rendering speed, output quality, and the ability to iterate on templates daily were the entire reason users would pick us over alternatives. If we outsourced that, we'd be at the mercy of someone else's roadmap, someone else's latency decisions, someone else's priority queue. We'd lose the ability to ship a better experience on a Tuesday afternoon just because we had a new idea.
So we built it. It took longer upfront. But within months, we were iterating on our rendering pipeline multiple times a week, tuning it in ways no third-party vendor would ever prioritize for us. That speed of iteration became a compounding advantage.
Meanwhile, for things like payments, email, analytics, auth, we buy without hesitation. Those are solved problems. Nobody ever chose Magic Hour because we had a slightly better Stripe integration.
The framework I use now: ask yourself, "If this breaks or underperforms, is the fix a support ticket to someone else, or is it something I need to control in the next hour?" If the answer is the latter, you build. Ownership isn't about ego. It's about cycle time on the things that actually determine whether you win.
Match Ambition with Sustained Capability
The rule of thumb here is pretty straightforward: build something that sets you apart and buy something that allows you to get things done faster without harming the customer experience.
The experience that taught me this lesson is that of seeing ecommerce teams look into the development of their mobile apps. In theory, developing everything from scratch seems like an interesting proposition. However, when you take all the necessary components into account such as iOS, Android, updates, integration, testing, and maintenance - the question changes.
The real issue is not whether the team can build it once. It is whether they are the right team to keep improving and maintaining it over time.
This is now my approach to the question of build vs. buy. If the capability is part of your competitive edge and the team is able to maintain and improve it, then building it makes sense. But when speed and reduced burden on operations become your goals, buying might be the answer.
Stabilize Process before Systems or Automation
When choosing between long-term ownership and speed to launch, I start by assessing process readiness in quote-to-cash rather than defaulting to build or buy. If a step is stable, repeatable, and has clear data ownership, I favor building in-house to secure durable ownership; if the step is variable I automate carefully with guardrails, and if it is broken I will not automate it. The lesson that shapes my criteria is simple: do not automate a broken process until failure points are understood and controlled. Before selecting a third-party product for a fast launch I require clear business rules, reliable data, defined exception paths, and measurable outcomes so we do not simply move errors faster through CRM, CPQ, ERP, billing, and reporting systems.
