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.
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.
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.
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:
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.
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.
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.
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.
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.
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.
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.
Software development projects are notorious for their complexity and the challenges they bring. Even the most seasoned managers can fall prey to common pitfalls. Here are the top five mistakes made in software development projects and some practical advice on how to sidestep them.
The Mistake: Starting a project with unclear or constantly changing requirements leads to scope creep, delays, and budget overruns. This mistake often stems from insufficient communication between stakeholders and developers.
How to Avoid:
The Mistake: Projects often fail because teams underestimate the time, resources, and complexity involved. This leads to missed deadlines, overworked teams, and ultimately, a rushed, lower-quality product.
How to Avoid:
The Mistake: Ignoring end-users during the development process can result in a product that doesn’t meet their needs or expectations. This often leads to rework and dissatisfaction.
How to Avoid:
The Mistake: Poor communication between development teams, stakeholders, and management can lead to misunderstandings, duplicated work, and missed goals.
How to Avoid:
The Mistake: Rushing to meet deadlines often results in insufficient testing, which can lead to bugs, security vulnerabilities, and a poor user experience.
How to Avoid:
Conclusion: Avoiding these common pitfalls can significantly improve the chances of success in your software development projects. By being proactive and implementing best practices, you can deliver high-quality software on time and within budget.