Platform engineering is still a relatively young discipline, but its importance is growing rapidly as organizations look to streamline developer workflows, scale cloud adoption, and prepare for AI-powered workloads.
Yet even as investment surges, many teams fall into the same traps — creating platforms that developers bypass, rebuilding too much at once, or neglecting to define clear success metrics.
The key to avoiding these pitfalls is treating the platform as a product, not just a collection of tools, and focusing relentlessly on developer adoption.
Why Many Platform Engineering Efforts Stall
Derek Ashmore, AI enablement principal at Asperitas, says one of the biggest pitfalls is treating platform engineering as just another infrastructure or operations team.
“When organizations staff it exclusively with infrastructure specialists and don’t include product-minded engineers, the platform quickly becomes a collection of tools rather than a true internal product that developers want to use,” he says.
Henrique Back, head of engineering at Indicium, agrees that mindset is often the root cause of platform failures.
“The biggest mistake is treating the team like a standards enforcement group instead of a product team,” he says. “Another is building something huge without validating with real users. That almost always leads to low adoption.”
The risk is developing a platform no one uses—which is a wasted investment.
“If the platform team doesn’t spend time understanding developer pain points and measuring adoption, they end up with elegant solutions that nobody uses,” Ashmore explains.
Blending Skills to Build a Sustainable Platform
Building a successful internal platform requires more than automation expertise — it demands cross-functional thinking.
Ashmore notes a strong platform engineering team must “bridge two worlds at once”.
“It must be robust, secure, and operationally sound, while also being intuitive, flexible, and enabling for developers,” he says.
Lean too far toward operations, and the platform will be technically stable but developer-hostile; lean too far toward software engineering, and you risk abstractions that don’t scale or meet enterprise governance requirements.
Back recommends hybrid teams that include developers, ops engineers, product managers, and even UX professionals.
“Balance comes from hybrid profiles,” he says. “Because at the end of the day a platform is an internal product.”
Rotating engineers in from application teams and creating constant feedback loops with SREs are additional best practices Ashmore points to for keeping platforms grounded in real-world developer needs.
Avoiding the “Tool Factory” Trap
Even well-staffed teams can fail if they don’t adopt a true product mindset. Ashmore says that without one, platform efforts turn into “tool factories” — teams measure success by outputs (scripts delivered, tickets closed) rather than outcomes (adoption, faster cycle times, fewer incidents).
“The result is low trust and poor adoption — developers simply work around the platform,” he says.
Back says without a product mindset, the platform becomes a pile of scripts. Teams ship features that no one asked for and never measure impact.
The alternative is treating developers as customers, interviewing them, collecting feedback, tracking adoption, and evolving continuously.
That means putting developers in the center of the process, using research, roadmaps, and outcome-based metrics to prioritize improvements that remove friction.
The Perils of the Big-Bang “V2” Rebuild
Another major pitfall is attempting a full-scale platform replacement in one go.
“Attempting a wholesale ‘v2’ rebuild is risky because it almost always leads to long timelines, shifting requirements, and a gap between what developers need today and what the platform team is building for tomorrow,” Ashmore says.
By the time the new platform is ready, developer workflows may have already evolved, leaving teams with a tool that is obsolete on arrival.
Back says he agrees long-running monolithic projects often miss the mark.
“A safer approach is evolutionary, delivering small modules, validating, and scaling,” he says. “Fast iteration always beats a big bang release.”
Ashmore recommends incremental modernization techniques like the “Strangler Fig” pattern — gradually replacing high-friction components such as CI/CD pipelines or secrets management with modernized versions and building adoption step by step.
Lessons from Platform Failures
Both experts have seen platforms fail due to poor adoption and lack of flexibility. Ashmore recalls one large enterprise that spent over a year building an ambitious, automated platform in isolation.
“After more than a year of work, the platform launched with fanfare, only to see very little adoption,” he says. “Developers found it slower and more restrictive than the scripts and processes they already used, so they bypassed it.”
The company eventually pivoted to a narrower, developer-led approach that delivered quick wins and rebuilt trust.
Back says he has seen platforms launched as black boxes that promised to solve everything but were impossible to customize.
“Developers worked around them, and the platform was abandoned in months,” he cautions.
Both cases underscore the same lesson: without developer input, flexibility, and quick value delivery, platforms lose credibility — and adoption plummets.
Measuring What Matters
Defining clear success metrics is essential for demonstrating the platform’s business impact.
Ashmore notes that teams should measure “adoption, developer satisfaction, and productivity impact,” not just the number of tools or integrations delivered. Those metrics provide the feedback needed to justify ongoing investment and guide continuous improvement.
Platform engineering promises to improve developer experience, speed delivery, and reduce complexity — but only if executed well. Success requires cross-disciplinary teams, a product mindset, iterative modernization, and outcome-based metrics.
“Treating the platform as an internal product is not optional,” Ashmore says. “Developers need to be treated as customers, with continuous engagement and feedback shaping priorities.”
Iteration and validation are non-negotiable, with Back cautioning that if it is not flexible and does not show value quickly, adoption will never happen.
“Platform engineering is about more than tools — it’s about building trust with developers,” he says.