The meeting that kills most software projects before they start

A software project meeting focused on requirements, system architecture, technology stack, and planning before development begins.

Research from the Project Management Institute has consistently connected poor requirements management with project waste and failure. Its research found that 5.1% of project expenditure was wasted because of poor requirements management, equivalent to $51 million for every $1 billion spent. That makes the first software meeting much more than a formality. It is where uncertainty should be reduced before uncertainty becomes expensive code.

The meeting that kills most software projects before they start

A software project can have a good idea, a capable development team and a healthy budget and still go wrong before development really begins. It usually starts with a meeting. The founder explains the idea. The product team lists the features. Someone asks how quickly it can be built. The development team estimates the work. Everyone leaves with a roadmap and a deadline. Then the questions begin. What exactly does "customer account" mean? Who approves a transaction? What happens when payment fails? Does the system need to support multiple branches? Which users can see financial data? What happens when an external API goes down? They can change the product architecture, technology stack, development timeline and budget.

Research from the Project Management Institute has consistently connected poor requirements management with project waste and failure. Its research found that 5.1% of project expenditure was wasted because of poor requirements management, equivalent to $51 million for every $1 billion spent. One of the easiest ways to derail a software project is to discuss technology before understanding the business problem.

A founder might say, "Let's build it with React and Node.js." Another might suggest Python because AI may be added later. Someone else may recommend microservices because the product needs to scale. None of those decisions are necessarily wrong.

They are simply premature. A good software discovery process first establishes what the system actually needs to do. For example, a furniture retailer may say it needs inventory software. That could mean a basic stock counter, or it could mean a multi-branch system connecting showrooms, warehouses, sales orders, production, delivery and customer records. The technology stack changes depending on that answer.

Technology stack should follow the workload:

Requirement	Possible stack	Why it fits
SaaS/web application	React or Next.js + Node.js/TypeScript + PostgreSQL	Strong ecosystem and good fit for API-driven applications
AI-enabled application	React/Next.js + FastAPI/Django + Python + PostgreSQL	Python has a mature AI and data ecosystem
Enterprise platform	React/Angular + Java/Spring Boot + PostgreSQL	Mature architecture and enterprise tooling
Microsoft-heavy organisation	React + ASP.NET Core + SQL Server + Azure	Strong Microsoft ecosystem integration
Real-time application	React/Next.js + Node.js + PostgreSQL/Redis	Well suited to I/O-heavy and real-time workloads
Cloud-native platform	Application services + Docker + Kubernetes + managed cloud services	Useful where independent deployment and operational scale justify the complexity

A PostgreSQL database can support a very large application if the data model, queries, indexes and infrastructure are designed properly. Redis can improve response times when caching is appropriate. Docker can make environments more consistent. Kubernetes can help manage complex containerised workloads. But adding all of them to a small application does not make the application better.

What the first meeting should actually uncover

How to avoid the meeting that kills most software projects before they start: The first meeting should be less about presenting a finished solution and more about exposing the unknowns. PMI research identifies incomplete requirements, lack of user involvement, unrealistic expectations and changing requirements among recurring sources of project problems. A good discovery conversation should therefore map the actual workflow, not simply collect a list of features. The questions worth asking before development starts:

Question	Why it matters
Who are the primary users?	Determines permissions, interface and workflow
What problem are we solving?	Prevents building features without business value
What is the current workflow?	Reveals real operational requirements
What happens when the normal workflow fails?	Exposes edge cases early
What systems need to integrate?	Identifies technical dependencies
What data needs to be stored?	Influences database architecture
Who can access sensitive information?	Establishes security requirements
How many users are expected?	Helps determine infrastructure requirements
What must work in version one?	Controls scope and budget

This is also where functional and non-functional requirements need to be separated. This discipline becomes even more important as software teams adopt AI coding tools. DORA's 2025 research found that 90% of technology professionals surveyed were using AI at work, with more than 80% saying it improved their productivity. At the same time, DORA found that increased AI adoption was associated with higher software delivery throughput and higher delivery instability. This is also where software development companies with substantial project experience can provide value before development even begins. A company that has worked across enterprise software, SaaS, healthcare, manufacturing, eCommerce and AI projects has seen how apparently simple requirements can become complicated once they meet real-world workflows.

Kaz Software's 22-year history is relevant in that respect. The company has worked on software across multiple industries and international markets, including enterprise applications, SaaS products, AI systems, manufacturing and eCommerce. That experience means the discovery phase can draw on previous engineering patterns rather than treating every project as a blank slate.