Why Great Software Still Matters in the AI Era

Every few years, the software industry reaches a moment when people start asking the same question: will this new technology make software less important?

Cloud computing sparked that debate. So did no-code platforms. Now AI is doing it again.

From startup podcasts to social media feeds, the idea keeps resurfacing that AI can build software, so maybe software itself is no longer the competitive advantage.

But after speaking with Mac developers, following product teams, and watching how AI is reshaping desktop apps, one conclusion keeps standing out:

AI isn’t making great software less important. It’s making it more important than ever.

Apple’s WWDC 2026 keynote and MacPaw’s post-keynote discussion reinforced that point. AI may be changing how people interact with software, but the software doing the actual work still matters just as much.

AI changes the interface—not the job

The biggest misconception about AI is that it replaces software.

In reality, it changes how we interact with software.

Instead of opening an application and navigating menus, we’re beginning to describe what we want in natural language.

“Free up storage.”
“Organize these files.”
“Recover the photos I deleted yesterday.”

That’s a dramatically better user experience.

But behind every one of those requests is still a specialized application carrying out the work.

An AI assistant doesn’t know how to repair a damaged disk, recover deleted files, transfer data between iPhones, or safely optimize macOS on its own. Those capabilities come from years of engineering inside dedicated software.
AI understands your intent.

Software turns that intent into action.

The interface is changing.

The underlying software remains essential.

AI makes building software easier. Building products is another story.

There’s no question AI has lowered the barrier to building software.

Developers can prototype ideas faster, write code more efficiently, and launch products in weeks instead of months.

But building software has never been the entire job.

Recently, we read an Entrepreneur interview describing how many companies struggle with AI adoption because they focus on adding AI rather than redesigning workflows around real user problems.

That observation mirrors conversations we’ve had with Mac developers.

Launching version 1.0 has become easier.

Building version 50 hasn’t.

Successful software still depends on product judgment, customer feedback, long-term maintenance, thoughtful design, documentation, support, and thousands of small decisions that shape the user experience over time.

Those aren’t problems AI solves automatically.

They’re what transform software into a product people continue recommending years after its first release.

Trust becomes a feature

As AI becomes more capable, another differentiator is becoming increasingly important: trust.

Users are asking software to access more of their digital lives than ever before — files, photos, emails, passwords, personal workflows. Apple clearly felt this pressure at WWDC26 too: Craig Federighi went out of his way to say “privacy in AI is non-negotiable,” framing Apple Intelligence as something that “stands guard” over user data even as it takes on more agentic tasks.

That’s the same bet MacPaw is making with Eney. Instead of routing every request through the cloud, Eney’s ELIX engine (Eney Local Intelligence MLX) handles reasoning, context search, and skill execution directly on-device by default — only reaching out to the cloud when a task genuinely requires it, like pulling in an external API. The pitch isn’t “smarter model,” it’s “your data doesn’t have to leave your Mac to get this done.”

That’s a deliberate product decision, not just a technical one. As AI gets deeper access to everyday computing, privacy and transparency stop being marketing lines and start being the actual feature people are choosing between.

The smartest software won’t necessarily be the one with the largest language model. It may be the one users trust enough to let AI act on their behalf in the first place.

The future belongs to software with deep expertise

One lesson has become increasingly clear throughout our conversations with developers.

The software categories most likely to thrive in the AI era aren’t necessarily the ones with the flashiest AI features.
They’re the ones built on years of specialized expertise.

Think about the tools many Mac users rely on every day:

• disk management
• file recovery
• Mac maintenance
• iPhone and iPad management
• backup and migration
• etc…

These applications don’t simply generate content.

They interact with the operating system, understand complex file structures, manage permissions, and perform tasks that require deep technical knowledge.

AI can make these tools easier to use.

It doesn’t replace the engineering behind them.

In many ways, AI may make specialized software even more valuable because intelligent assistants still need trusted software to carry out complex actions safely.

The better AI becomes at understanding what users want, the more important great software becomes at delivering the result.

The takeaway

The AI era isn’t the end of software.

It’s the beginning of a different relationship between people and software.

We’re moving from clicking to asking.

From interfaces to intentions.

From manual workflows to intelligent assistance.

But underneath those experiences, the fundamentals haven’t changed.

Great software still requires engineering.

It still requires product judgment.

It still requires trust.

And it still requires teams willing to spend years refining products long after the excitement of version 1.0 has faded.

AI may become the front door to software.

But great software is still the house.

And that’s why, even in the AI era, it matters more than ever.

Read also:

• Inside Setapp: How MacPaw Reinvents App Discovery and Usage
• Is CleanMyMac Still Worth It in the Age of AI-Built Mac Utilities?
• Eney: Is MacPaw’s new AI companion truly ready to run your Mac?
• Has AI Killed Software Moats? The Team Behind Bartender Doesn’t Think So

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