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What Went Wrong...

Examining the missteps of various software products across industries reveals common pitfalls that can derail even the most promising innovations. From inadequate market research and poor user experience design to insufficient testing and failure to adapt to technological advancements, these challenges underscore the importance of thorough planning and execution. The following section outlines specific cases, offering insights into how these factors contributed to their downfall and the lessons that can be gleaned to inform future endeavors.

Available Lessons:

200

Duolingo Bots (AI Chat Feature)

EdTech

Duolingo

AI-powered bots designed for conversation practice failed to meet user expectations due to limited language capabilities.

WHAT WENT WRONG

  • Poor AI training and inability to handle natural conversations

  • Limited real-world usability for learners

SIGNALS MISSED

  • Early user frustration with repetitive and robotic responses

  • Low adoption rates for the feature post-launch

HOW COULD THEY HAVE AVOIDED THIS

  • Iterative AI testing with real learners before rollout

  • Narrowing focus to improve specific conversational use cases

TEAMS INVOLVED

Product, Engineering, AI, QA, Design

AltSchool Personalized Learning Platform

EdTech

AltSchool

A high-tech learning platform aiming to reimagine classrooms failed due to excessive costs and unclear value to schools.

WHAT WENT WRONG

  • Overengineered software that was too expensive to scale

  • Poor alignment with existing school workflows

SIGNALS MISSED

  • Early user feedback indicating steep learning curves

  • Limited school adoption due to high costs

HOW COULD THEY HAVE AVOIDED THIS

  • Building scalable, affordable solutions tailored for public schools

  • Partnering with educators to align features with needs

TEAMS INVOLVED

Product, Sales, Marketing, CEO, Operations

Knewton Adaptive Learning Platform

EdTech

Knewton

Promised AI-driven personalized learning, but the software failed to deliver meaningful results and was too complex for educators to use effectively.

WHAT WENT WRONG

  • Overpromised AI capabilities without real-world validation

  • Poor user experience and lack of teacher integration

SIGNALS MISSED

  • Teachers reported difficulty integrating the platform into curriculums

  • Low engagement and measurable improvement for students

HOW COULD THEY HAVE AVOIDED THIS

  • Conducting pilot tests with educators for usability feedback

  • Aligning AI development with proven learning outcomes

TEAMS INVOLVED

Product, Engineering, Marketing, Sales, Design, CEO

Bridge (Employee Learning Platform)

EdTech

Instructure

Instructure’s corporate LMS failed to compete with enterprise-focused tools due to lack of features and customer traction.

WHAT WENT WRONG

  • Misunderstanding enterprise customer needs

  • Slow product evolution compared to competitors

SIGNALS MISSED

  • Feedback showing feature gaps for corporate users

  • Low renewal rates during early customer pilots

HOW COULD THEY HAVE AVOIDED THIS

  • Conducting competitive analysis before launching

  • Building a feedback loop with enterprise clients for improvements

TEAMS INVOLVED

Product, Sales, Marketing, Engineering

Blackboard Learn Ultra

EdTech

Blackboard

The revamped version of their LMS (Learning Management System) faced delays, bugs, and usability issues, causing frustration for institutions.

WHAT WENT WRONG

  • Rushed launch with incomplete features

  • Failure to improve outdated user experience

SIGNALS MISSED

  • Beta testers reported numerous performance bugs

  • Negative user feedback on navigation and usability

HOW COULD THEY HAVE AVOIDED THIS

  • Phased release with rigorous QA testing

  • Continuous user testing for real-world educator feedback

TEAMS INVOLVED

Product, Engineering, QA, Customer Success, Design

GreenSky Loan Processing Software

FinTech

GreenSky

GreenSky’s software for approving home improvement loans faced bugs that led to misapproved or delayed applications, triggering customer frustration.

WHAT WENT WRONG

  • Software logic errors in loan approvals

  • Weak monitoring of partner bank integrations

SIGNALS MISSED

  • Partner bank complaints about approval inconsistencies

  • Rising borrower dissatisfaction post-application

HOW COULD THEY HAVE AVOIDED THIS

  • Frequent audits of approval logic and system integrations

  • Building real-time dashboards for error detection

TEAMS INVOLVED

Product, Engineering, Risk Management, Operations

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