Writing code is the fun part. There's a problem to solve and the solution comes down to creativity and engineering skill. It's engaging, intellectually stimulating, and the point at which most developers get into a state of flow.
But individual flow is almost without responsibility: it's just you and the problem. For the broader health of the product, though, all the unfun work also has to happen: builds, deployments, dependency management.
And few things are more disruptive to a team’s flow than a build system that throws a 45-minute delay in the way of every change.
Multiply that by a team of eight, across several builds a day, and you're looking at 30–40 hours of lost engineering time each week. That’s one FTE lost to waste. Even shorter build delays put delivery at risk.
Perhaps the root problem is that many teams have become disconnected from their builds. When the process is hidden behind an IDE’s play button, it becomes something to complain about, rather than something to understand and improve.
In this article, we’ll look at how to spot the signs of a sick build: long delays, brittle workflows, and invisible friction that chips away at confidence and delivery speed. And we’ll share three ways to turn your build from an inconvenience to becoming a first-class citizen in your toolchain.
A sick build should be obvious, right? But the pain builds up over time and, eventually, it’s just the way things are. And, so, teams develop workarounds.
But rather than wait for a new team member to join and point out the obvious, you can begin the journey of fixing your build by identifying what’s wrong today.
So, what should you be looking out for?
Often, the root cause is a combination of lack of ownership and inconsistent standards. Teams that would never accept flaky application logic somehow tolerate builds that fail randomly or produce different outputs from identical inputs. And when no one owns the build, no one fixes it. Problems linger, workarounds pile up, and eventually the pain just becomes part of the job.
But fixing a sick build is about more than addressing the symptoms. It’s about adopting the right philosophy.
The underlying principle for fixing builds is straightforward: make the right thing easier than the wrong one.
But that’s rarely how things work by default. Every new service needs deployment config and there’s a working example from the last project sitting right there. So, of course, teams copy and paste. Running tests locally takes too long, so people push to CI and hope for the best. Updating a shared library requires coordinating across multiple teams and repos, so changes get batched up and delayed.
None of this happens because people don’t care about quality. It happens because the path of least resistance leads away from good practices.
But when you design systems where the right thing really is the easiest thing, behaviour shifts on its own. Teams run builds more often when they’re fast. They test more thoroughly when it’s simple to do so. They make smaller, cleaner changes when the tooling supports it.
Applying this principle means rethinking three fundamental aspects of how builds work: how tasks are isolated and cached, how dependencies are coordinated, and when validation happens in your development cycle.
The same code should produce the same results every time and everywhere. But that only happens when builds are reproducible. If your process depends on undocumented setup steps, local quirks, or mismatched toolchains, you're not building software: you’re debugging environments.
Here’s how to make reproducibility the default:
Teams don’t always notice when reproducibility starts to slip. Local builds get slower. A few developers can’t get things running without a workaround. Eventually, the path of least resistance becomes using remote dev boxes—just to keep things moving.
In one case, that shift had become normal: every developer ran builds on a remote machine because local setups had grown too unreliable to trust. Reproducing the environment locally wasn’t just fragile, it was actively avoided. Rather than fix the underlying issues, the team had built infrastructure around the pain.
Reproducible builds avoid that trap. They eliminate “works on my machine” problems, reduce onboarding from days to minutes, and make failures predictable. Teams spend time building features instead of fighting environments.
When dependencies are scattered across multiple repositories and build systems, small changes require massive coordination. Teams end up avoiding updates, batching changes, and losing delivery predictability.
How to consolidate dependencies:
Consider a team that had split their monolith into microservices, putting shared libraries in separate repositories. What seemed like good modularity became a coordination nightmare. Every small utility function update required pull requests across a dozen repos, each with its own build and review process.
The shift came when they moved back to a single repository. Multi-day coordination efforts became single atomic commits. They added local tests covering affected services, and post-merge bugs dropped off dramatically. They even removed obsolete services that nobody had been willing to touch because of coordination overhead.
Consolidated dependencies eliminate coordination bottlenecks, reduce the risk of version conflicts, and make delivery timelines predictable again. Teams can make changes confidently rather than avoiding them.
Problems discovered late in the development cycle cost exponentially more to fix. When validation only happens during deployment, integration testing, or after code review, teams waste time on preventable issues and lose confidence in their changes.
How to shift left:
Teams often fall into heavyweight testing by default, spinning up entire environments and testing everything through the UI. We at Pelo.tech know of one team that was spending hours running end-to-end tests that could have been replaced with contract validation during the build, catching issues earlier with less effort and more confidence.
Deployment complexity adds its own friction. In one team, every new AWS Lambda required 40 lines of copied boilerplate. Switching to a shared build plugin turned that into a single line of configuration, so there was less room for error and less time wasted. It also made system upgrades dramatically easier: instead of tracking down and updating 40 lines of copy-pasted code across dozens of services, they could simply bump the plugin version to roll out improvements everywhere at once.
Shifting validation left catches problems when they’re cheapest to fix, speeds up delivery, and gives teams the confidence to focus on business logic instead of infrastructure mechanics.
The principles outlined in this article—reproducibility, consolidation, and early validation—aren’t abstract ideals. They’re practical defaults you can work towards incrementally. Most teams won’t implement everything at once, and they don’t need to. What matters is choosing a direction and making steady progress.
Start by understanding how your build system behaves today. Track build times across local and CI environments. Count the manual steps required to deploy a service. Note how often you hear “works on my machine.” These small signals often point to bigger problems.
Look out for escape hatches—places where teams work around the build system. Common examples include shell scripts coordinating between stages, Dockerfiles that live outside the main build logic, or services that can only be tested remotely.
Audit how your build tool is actually being used. Partial adoption—mixing in shell scripts, skipping declared inputs—often breaks caching and reproducibility, even when the tool supports them.
Introduce basic observability. Track slowest tasks, cache misses, and failure rates to guide future optimization efforts.
Once you’ve mapped the landscape, go after the easiest wins. If your build tool supports it, enabling remote caching can cut build times dramatically. One team we worked with at Pelo.tech reduced their builds from 45 minutes to 12 just by turning on Gradle’s remote build cache.
Reproducibility is the right place to begin. Pin dependency and tool versions. Remove undocumented setup steps. Ensure a new developer can clone the repo, run the build, and get a working result within minutes.
Standardise build conventions across teams to reduce friction and avoid knowledge silos.
Then consolidate your dependency management. Whether or not you move to a monorepo, you need a single source of truth for versions and shared build logic. Use tools like build plugins, version catalogs, or BOMs (Bill of Materials) to manage dependency versions centrally, along with shared config files to eliminate duplication and coordination overhead.
Bring validation closer to the developer. Add static analysis to the local build: linters, security scans, and dependency checks. When feedback happens early, it gets acted on.
With solid foundations in place, you can start shifting more responsibility into the build system without making it heavier.
Replace brittle integration tests with fast, reliable contract tests. Mirror production dependencies locally using containers orchestrated by your build tool. Take boilerplate deployment steps and turn them into shared plugins that encode best practices once.
Track the impact. Measure build time trends, PR cycle times, deployment frequency, and developer sentiment. Pair hard metrics with regular feedback: What’s still painful? What feels slower than it should? What’s working?
You’ll find small improvements compound quickly. Faster builds lead to more testing. More testing builds confidence. And confident teams ship better code, faster.
You don’t need a perfect system, just steady movement toward a build developers trust and rely on.
Treating builds as first-class citizens changes how teams work. When builds are fast, predictable, and reproducible, developers stop working around them and start trusting them. That trust becomes the foundation for better habits: more frequent testing, smaller commits, faster reviews, and fewer last-minute surprises.
It also removes a constant source of frustration. Poor build systems quietly drain morale by slowing people down, breaking unpredictably, and making good practices harder to follow. Fix the builds, and you fix the daily experience of development. Developers feel more in control, more confident in their changes, and less tempted to cut corners.
Most importantly, strong builds unlock long-term improvements. When teams trust the system, they refactor with confidence. They tackle technical debt, raise quality standards, and ship improvements without fear. It's not just about saving time, it’s about creating the conditions where great software and happy teams can thrive.
If you’d like to learn more about how we at Pelotech can help improve your build systems and developer workflows, get in touch. We’d love to hear about what’s slowing your team down and how we can help clear the way.
