Software Development Archives

Generative AI & Prompt Engineering for Software Developers — Join Us October 16!

AI isn’t the future—it’s now. And if you’re a software developer, the question isn’t whether you should learn how to use generative AI, but how fast you can get up to speed.

That’s exactly why we’re offering our live, one-day workshop:
“Generative AI & Prompt Engineering for Software Developers”
–October 16, 2025
–Live & Instructor-Led
–Sign up today!

What You’ll Learn

This isn’t a surface-level intro. We’re going deep on how AI is revolutionizing modern software development and how to take full advantage of it in real-world projects. You’ll learn:

Real-world use cases (and hands-on labs) using the AI tools we’re integrating at Intertech today

How to write precise, effective prompts to get quality output from AI tools

Best practices for using ChatGPT and other large language models in coding, documentation, testing, and debugging

Common prompt pitfalls and how to avoid them

How to speed up project delivery without compromising quality

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.