Software Development Archives

Why Most Software Projects Fail Before a Line of Code Is Written

When software projects go sideways, everyone looks at the developers.
But here’s the truth we’ve seen again and again:

Most failures happen before the first line of code is even written.

It’s not the coding. It’s what happens—or doesn’t happen—before coding starts.

1. The goals aren’t clear

Ask five stakeholders what success looks like, and if you get five different answers, you’re headed for trouble.
Without a shared definition of “done,” projects drag, priorities shift, and the final product pleases no one.

Fix it:
At Intertech, we don’t write code until everyone agrees on goals, guardrails, and outcomes. No guesswork. No assumptions.

2. Requirements are rushed

“We need a login, some reports, and a dashboard.” That’s not a spec—it’s a wish list. Too many projects jump into development with vague features and unclear logic.

Fix it:
Slow down to speed up. We workshop requirements, ask hard questions, and pressure test assumptions before a developer touches the keyboard.

3. The users are missing

We’ve seen projects stall because they were built for what management thought users wanted—not what users actually needed. That disconnect is expensive.

Fix it:
User interviews. Prototypes. Feedback loops. Involve the people who will live with the software from day one.

4. There’s no plan for change

Scope creep doesn’t kill projects—poor change management does. Requirements shift. Priorities evolve. But if you don’t have a process to manage that, chaos takes over.

Fix it:
We build in checkpoints. We communicate trade-offs. And we use tools that make it easy to update without blowing up the timeline.

5. The team is misaligned

Even with great tools and talent, if your internal team and your vendor aren’t on the same page, it shows. Missed messages. Missed deadlines. Missed expectations.

Fix it:
We overcommunicate early. Daily huddles, shared channels, clear escalation paths—because alignment beats brilliance every time.

The takeaway?
A successful project starts before the kickoff.
It starts with clarity, discipline, and a partner who’s not afraid to slow down to get it right.

We’ve seen it. We’ve learned it. We build for it.

Intertech Launches AI Application Development Course

This one-day interactive course equips intermediate software developers with the knowledge and hands-on experience needed to use Generative AI effectively within the software development lifecycle. Participants will explore practical prompt engineering techniques using GitHub Copilot as the primary interface for interacting with leading LLMs, including ChatGPT, Claude, and others.

Visit the Intertech website to learn more and enroll.

What I’ve Learned from Working with Hundreds of CIOs

Over the years, I’ve had the chance to work with hundreds of CIOs—from Fortune 500s to fast-growing mid-market companies. Different industries. Different styles. But if there’s one thing I’ve learned, it’s this:

CIOs don’t want more tech. They want better outcomes.

They’re not looking to chase trends—they’re trying to solve real business problems. Quickly. Clearly. Without drama.

Here are a few lessons I’ve learned working alongside them:

1. Simplicity beats cleverness
CIOs don’t need consultants to show off. They need partners who simplify, prioritize, and deliver. If you can explain the solution in plain English and connect it to a business objective, you’ll go far.

2. Speed matters—but predictability matters more
Yes, CIOs want fast results. But they’ll take a steady, low-risk rollout over a “hero” team that burns out mid-project. On-time and drama-free often wins the renewal.

3. Trust builds over time—and disappears fast
One missed deadline or dropped ball, and you’re back to square one. But if you consistently deliver (even small wins), you become part of their inner circle. That’s where real partnership lives.

4. Every CIO has a top 3 list
It might not be printed on their whiteboard, but they’re always carrying three priorities—revenue, risk, or roadmap related. If your solution doesn’t map to one of those three? It’s noise.

5. They’re under more pressure than you think
CIOs today are expected to be technologists, strategists, diplomats, and firefighters—all at once. The best thing we can do is make their life easier, not harder.

Bottom line?
CIOs don’t care how brilliant your code is or how advanced your architecture looks. They care about outcomes. Alignment. And trust.

You win with CIOs by listening well, thinking clearly, and delivering consistently.

That’s been true for over 30 years. It’s still true now.

If AI Is So Smart, Why Can’t It Run a Project?

AI can draft an email, summarize a meeting, write code, and even crank out a blog post like this one (with help). But there’s one thing it still can’t do:

Run a real project.

We’ve tried. We’ve experimented with AI for status reports, timelines, risk assessments, and backlog grooming. It’s impressive—fast, helpful, and often accurate. But project management? That’s still human territory.

Here’s why:

1. AI can’t read the room.
Deadlines shift. Priorities change. A stakeholder’s “no big deal” tone in an email actually means “I’m about to escalate this.”
AI doesn’t catch nuance. It doesn’t read body language, office politics, or tension over Teams calls. Project leaders do.

2. Projects don’t follow scripts.
Even the best Gantt chart goes sideways by week two. People get sick. Budgets get cut. A client pivots.
AI is great at pattern recognition—but projects are often the opposite: messy, emotional, and unpredictable. Leading through ambiguity takes real-time judgment, not pre-trained algorithms.

3. Relationships still matter. A lot.
When things go south (and they will), people want to talk to someone they trust—not a chatbot.
A seasoned project lead knows how to listen, adjust, empathize, and reset expectations without blowing up the timeline—or the relationship.

4. AI doesn’t know your business.
It knows businesses in general. It doesn’t know your unique challenges, team dynamics, or what happened last quarter that’s still lingering in the background.
Good project leadership isn’t just about tasks. It’s about context—and context still requires a human brain.

That said—AI is an amazing co-pilot.
It can flag risks faster. Draft communication. Generate insights from sprint notes.
But it’s not leading the call, navigating egos, or rescuing a deliverable gone off the rails. That’s you.

So no, AI can’t run a project.

But it can help you run one better.

Emerging Tech Trends: Navigating the Future of Software Development

As we step into 2025, the landscape of software development continues to evolve at a breakneck pace. Staying ahead of the curve not only requires awareness but also strategic foresight. Here are the key technology trends that are shaping the future of our industry and how businesses can leverage them for growth:

1. Artificial Intelligence (AI) and Machine Learning (ML) Expansion

AI and ML are no longer just buzzwords but are core components of business strategy. This year, we see these technologies becoming more integrated into everyday applications, enhancing everything from analytics to user interfaces. Companies can harness AI for predictive analytics, customer service, and personalized user experiences.

2. Quantum Computing Goes Mainstream

With major advances in quantum technology, 2025 might be the year it transitions from experimental to practical applications. Quantum computing offers unprecedented processing power, which can solve complex problems much faster than traditional computers. Businesses in fields such as pharmaceuticals, aerospace, and finance stand to benefit immensely.

3. Increased Adoption of Edge Computing

As IoT devices proliferate, edge computing is becoming crucial in handling data efficiently. By processing data near its source, edge computing reduces latency and conserves bandwidth. This trend is vital for businesses that rely on real-time data processing, like those in manufacturing and logistics.

4. Blockchain Beyond Cryptocurrency

Blockchain technology is finding new applications beyond its initial use in cryptocurrency. From supply chain enhancements to secure voting systems, blockchain offers transparency and security in transactions. Businesses should consider how blockchain can be integrated into their operations to enhance trust and efficiency.

5. Sustainable Tech Innovations

As environmental concerns mount, sustainable technology is more crucial than ever. Innovations in energy-efficient computing and environmentally friendly data centers are gaining traction. Companies focusing on sustainability will not only reduce costs but also attract eco-conscious consumers.

6. Cybersecurity Advancements

With the rise of digital transformations, cybersecurity remains a top priority. New technologies are emerging to tackle the increasing sophistication of cyber threats. Businesses need to stay updated with the latest security technologies to protect sensitive data and maintain customer trust.

7. The Rise of Augmented Reality (AR) and Virtual Reality (VR)

AR and VR are transforming various industries, from retail to real estate. These technologies offer immersive experiences that enhance customer engagement and operational training. Businesses should explore how AR and VR can be integrated into their customer offerings and internal processes.

Navigating these trends requires not only technological adoption but also a cultural shift within organizations. Businesses that embrace these changes and invest in upskilling their teams will thrive in the evolving digital landscape.