In the fast-paced world of software development, teams often prioritize speed, especially during the early stages of product development. Startups and established organizations alike feel the pressure to deliver customer value quickly, maintain a competitive advantage in emerging markets, and meet business-critical deadlines. This drive to "move fast and break things" frequently leads to scrappy development practices—building fast with little planning, delaying technical debt. While this approach can offer short-term advantages, such as rapid market entry and early user feedback, it often incurs significant long-term costs and has profound adverse societal consequences [1]. Many organizations were able to bear these long-term costs by hiding behind operations, expanding teams, and slowing down later in the process. However, this raises the question of whether such an approach is universally effective. The Imperative of Speed in Organizational Success Is Speed Bad? No. More importantly, it’s not a question of whether it’s good or bad—it’s absolutely necessary. Speed can mean life or death for startups and smaller companies, while for larger organizations, it prevents stalled growth or missed opportunities. No organization wants to fall behind. Speed drives growth, and growth triumphs all [2] and growth delivers higher returns, predicts long-term success, and more. The more time we have, the more developers may focus on perfecting solutions, which can lead to analysis paralysis—obsessing over flawless code and other details. At this point, perfection becomes the enemy of progress. Speed’s Long-Term Pitfalls in Software Development If speed is entirely beneficial and essential, then what is the problem? While speed is undeniably valuable and often essential, pushing it without guardrails or balance can get us in trouble. As software scales with tiny tech debts or shortcuts for speed, it’s like death by a thousand cuts. It backfires big time—teams get stuck working on operations with no time for new development, so you end up hiring more people to keep up. Teams lose confidence to push changes to production because the system’s so fragile it slows everything down, especially when you tweak something and don’t know what else will break. People get frustrated and leave. It messes with the organization’s agility, customer experience, and developer experience. After a while, we just call those systems legacy and start plotting replacements. If you succeed in building new systems, you must then migrate all the legacy customers and data to the new platform. This process is highly challenging, depending on the system’s size, and often extremely expensive. Striking a Balance Between Speed and Stability Speed in the early stage is absolutely necessary but shouldn’t mean shortcuts. Spend a bit more time on long-term architecture, set up solid code quality standards and enforce it strictly, and build a proper developer environment where testing happens in advance so you can iterate faster. Speed here isn’t just growth—it’s technological agility. One software market trends report shows fast-moving organizations adopting AI and cloud tech have a 50% higher retention rate with enterprise clients compared to slow adopters [4]. Mark Zuckerberg, CEO of Meta, said in an interview [5], “Well, great engineering and speed and iteration are actually two different values. They’re not necessarily at odds, but I think there are a lot of great engineering organizations that try to build things that are super high quality and have good competence around that. But there’s a certain personality that goes with taking your stuff and putting it out there before it’s fully polished”. “Well, great engineering and speed and iteration are actually two different values. They’re not necessarily at odds, but I think there are a lot of great engineering organizations that try to build things that are super high quality and have good competence around that. But there’s a certain personality that goes with taking your stuff and putting it out there before it’s fully polished”. It might have worked for Meta because of its strong foundational infrastructure. It’s one thing if your product isn’t fully polished, but it’s a whole different ballgame if your foundational technologies aren’t. That latter one has serious consequences. Big players like Meta might be able to pause some of the feature development for a year or more—like they did in 2012 [5]—to get back on track, but in this day and age, almost no company can afford that. Call to Action Call to Action Estimate Right:
Software projects are always underestimated. Don’t be a hero and estimate aggressively. Something always comes up. It could be scope creep you can’t avoid, unknown unknowns, engineers going on vacation, or a critical issue that needs the team’s attention. So, give some buffer in the estimates.


Build to Last:
As the company grows and matures, at some point it reaches "build fast but don’t break things." As we add more features or expand the product, the codebase and system complexity can grow really fast. If we just pay attention to "what" we build and not "how" we build it, it’s a recipe for disaster. Also, it is critical to invest in testing environments and keep them working as the system grows; it tremendously increases development velocity by enabling faster iteration and reducing post-production bugs.


Quality Controls:
With the DevOps models, there are no longer traditional QA teams anymore. Each team is responsible for managing the quality of their services. It is very important to establish baseline code and documentation quality guidelines and strictly enforce them. Allocate some time to refactor to maintain the code quality, do a periodic review, and update as required. Make sure the code coverage expectations are set each release and the integration tests are written for critical call paths.


Operational Excellence:
Bad software can keep going with good operations, but good software can’t survive with bad operations. Operational excellence is the most important factor for any production software. Listen to the customers, analyze the metrics, and fix issues as they arise. Don’t just keep solving operational problems with one-off solutions and create the illusion that more issues are resolved; address the root cause instead.


Learn to Say No:
When we want to move fast, product teams come up with lots of new ideas. Sometimes, we may not deliver everything with reasonable quality. Push back on feature delivery and ask for more time if the pace negatively impacts your foundational systems.


Educate People:
Software grows and lives longer, but people come and go. A lot of institutional knowledge leaves with them when they leave. So, keep educating the team, document as much as possible, and constantly emphasize the importance of maintaining quality and building things right. Don’t just aim to grow superstars on the team; focus on developing the next generation of team members who can step in when needed. Estimate Right:
Software projects are always underestimated. Don’t be a hero and estimate aggressively. Something always comes up. It could be scope creep you can’t avoid, unknown unknowns, engineers going on vacation, or a critical issue that needs the team’s attention. So, give some buffer in the estimates. Estimate Right: Estimate Right: Software projects are always underestimated. Don’t be a hero and estimate aggressively. Something always comes up. It could be scope creep you can’t avoid, unknown unknowns, engineers going on vacation, or a critical issue that needs the team’s attention. So, give some buffer in the estimates. Build to Last:
As the company grows and matures, at some point it reaches "build fast but don’t break things." As we add more features or expand the product, the codebase and system complexity can grow really fast. If we just pay attention to "what" we build and not "how" we build it, it’s a recipe for disaster. Also, it is critical to invest in testing environments and keep them working as the system grows; it tremendously increases development velocity by enabling faster iteration and reducing post-production bugs. Build to Last: Build to Last: As the company grows and matures, at some point it reaches "build fast but don’t break things." As we add more features or expand the product, the codebase and system complexity can grow really fast. If we just pay attention to "what" we build and not "how" we build it, it’s a recipe for disaster. Also, it is critical to invest in testing environments and keep them working as the system grows; it tremendously increases development velocity by enabling faster iteration and reducing post-production bugs. Quality Controls:
With the DevOps models, there are no longer traditional QA teams anymore. Each team is responsible for managing the quality of their services. It is very important to establish baseline code and documentation quality guidelines and strictly enforce them. Allocate some time to refactor to maintain the code quality, do a periodic review, and update as required. Make sure the code coverage expectations are set each release and the integration tests are written for critical call paths. Quality Controls: Quality Controls: With the DevOps models, there are no longer traditional QA teams anymore. Each team is responsible for managing the quality of their services. It is very important to establish baseline code and documentation quality guidelines and strictly enforce them. Allocate some time to refactor to maintain the code quality, do a periodic review, and update as required. Make sure the code coverage expectations are set each release and the integration tests are written for critical call paths. Operational Excellence:
Bad software can keep going with good operations, but good software can’t survive with bad operations. Operational excellence is the most important factor for any production software. Listen to the customers, analyze the metrics, and fix issues as they arise. Don’t just keep solving operational problems with one-off solutions and create the illusion that more issues are resolved; address the root cause instead. Operational Excellence: Operational Excellence: Bad software can keep going with good operations, but good software can’t survive with bad operations. Operational excellence is the most important factor for any production software. Listen to the customers, analyze the metrics, and fix issues as they arise. Don’t just keep solving operational problems with one-off solutions and create the illusion that more issues are resolved; address the root cause instead. Learn to Say No:
When we want to move fast, product teams come up with lots of new ideas. Sometimes, we may not deliver everything with reasonable quality. Push back on feature delivery and ask for more time if the pace negatively impacts your foundational systems. Learn to Say No: Learn to Say No: When we want to move fast, product teams come up with lots of new ideas. Sometimes, we may not deliver everything with reasonable quality. Push back on feature delivery and ask for more time if the pace negatively impacts your foundational systems. Educate People:
Software grows and lives longer, but people come and go. A lot of institutional knowledge leaves with them when they leave. So, keep educating the team, document as much as possible, and constantly emphasize the importance of maintaining quality and building things right. Don’t just aim to grow superstars on the team; focus on developing the next generation of team members who can step in when needed. Educate People: Educate People: Software grows and lives longer, but people come and go. A lot of institutional knowledge leaves with them when they leave. So, keep educating the team, document as much as possible, and constantly emphasize the importance of maintaining quality and building things right. Don’t just aim to grow superstars on the team; focus on developing the next generation of team members who can step in when needed. Conclusion Conclusion In the software industry, not speeding kills. Yet racing ahead with shortcuts in foundational tech, quality controls, and engineering excellence can crash just as fast. Small startups fight to survive, big players chase exponential growth—but a shaky foundation threatens both. If an organization manages to survive with a weak foundation and poor engineering quality, it risks collapse when attempting to scale or may grind to a halt. Beyond that, it creates numerous people-related issues—lowering team morale and leading to operational burnout—which can collectively become very costly. Organizations must move quickly, but sometimes we need to say "NO," pause to strengthen the foundation and quality, educate and then continue growing sustainably. Speed wins battles; smart speed wins the war. References References [1] "Software Development: Speed vs. Sustainability" - ACM Digital Library, https://dl.acm.org/doi/fullHtml/10.1145/3244026#body-1 [1] https://dl.acm.org/doi/fullHtml/10.1145/3244026#body-1 https://dl.acm.org/doi/fullHtml/10.1145/3244026#body-1 [2] "Grow fast or die slow" - McKinsey & Company, https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/grow-fast-or-die-slow [2] https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/grow-fast-or-die-slow https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/grow-fast-or-die-slow [3] "483 Startup Failure Post-Mortems" - CB Insights, https://www.cbinsights.com/research/startup-failure-post-mortem/ [3] https://www.cbinsights.com/research/startup-failure-post-mortem/ https://www.cbinsights.com/research/startup-failure-post-mortem/ [4] "2024 Software Market Trends" - Gartner (Note: Exact URL not provided in original; placeholder used: https://www.gartner.com/en/documents/2024-software-market-trends, typically available via Gartner subscription or reports section). [4] https://www.gartner.com/en/documents/2024-software-market-trends https://www.gartner.com/en/documents/2024-software-market-trends [5] https://www.acquired.fm/episodes/the-mark-zuckerberg-interview [5] The opinions expressed in this article are solely those of the authors and not their employers. The opinions expressed in this article are solely those of the authors and not their employers.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

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