Where Should Engineering Teams Invest in 2025?

AI, platform engineering, or developer experience?

May 16, 2025

👋 Hi, this is Thomas. Welcome to a new edition of Beyond Runtime, where I dive into the messy, fascinating world of distributed systems, debugging, AI, and system design. All through the lens of a CTO with 20+ years in the backend trenches.

QUOTE OF THE WEEK:

“I’ve seen the biggest DX gains come from seemingly simple changes – clearer documentation, better internal tooling, more thoughtful onboarding. These aren’t always high-profile initiatives, but they’re the ones that eliminate friction engineers deal with every single day.” - Me.

AI. Platform engineering. Developer experience.

They’ve all become buzzy, high-stakes bets for engineering leaders. But deciding where to invest is hard. Budgets are limited, attention is fragmented, and not every shiny tool solves your team’s real problems.

Here’s a simple truth: most engineering pain points (e.g. technical debt, velocity issues, brittle systems) don’t have one-size-fits-all solutions. So the smart move is figuring out which investment actually maps to your team’s biggest bottlenecks.

Let’s break it down.

AI Coding Tools: Fast but Not a Fix-All

AI tools like GitHub Copilot promise to speed up development, and they often do. McKinsey claims devs can complete tasks twice as fast with generative AI. But most engineers know that writing the code is rarely the bottleneck.

The hard parts? Figuring out what to build. Understanding why it matters. Navigating a complex system to make sure you don’t break something else in the process.

AI helps with repetition and ramp-up. But if your system is chaotic or undocumented, you’re just shipping faster into the unknown.

Treat AI as an accelerator, not a strategy: the goal is to accelerate repetitive programming tasks and future-proof your org by building fluency in this rapidly evolving space.

BUT! Keep in mind that can’t just buy a tool, you’ll also need to invest in developer training, prompt engineer coaching, define clear use cases, and pair it with tools that bring system-level context.

Platform Engineering: Start Small, Stay Grounded

The rise of Internal Developer Platforms (IDPs) has made “platform engineering” one of the most sought-after bets in tech. Done right, it removes friction, unifies tools, and makes engineering more scalable.

But it’s easy to over-engineer. A full-blown platform doesn’t solve much if the real issues are unclear ownership, flaky CI/CD, or missing documentation.

Start with discovery. Where do your developers struggle? What repetitive pain could be solved with automation or better tooling? You can get big ROI from small wins, like simplifying environments or streamlining deployment paths, without building a whole platform team out of the gate.

If you’re looking for a deep dive into the differences between platform engineering and DevOps, I wrote more about it here: Platform Engineering: Tutorial & Examples

Developer Experience: The Long Game

DX isn’t just a feel-good initiative, it’s a broad investment in both culture and infrastructure.

It’s about eliminating blockers so developers can focus on actual problem-solving. That means cleaner onboarding, better feedback loops, clearer ownership, and fewer hours lost to digging through logs and half-written docs.

It’s also the foundation that makes other investments work. Want your AI tooling to pay off? Your devs need context. Want your platform adopted? Your devs need trust and clear value.

DX is a mindset you cultivate.

Final Thoughts

Investing in your engineering org isn’t about picking the trendiest acronym. It’s about understanding what’s slowing your team down, and choosing the lever that gives them leverage.

Sometimes that’s AI. Sometimes it’s platform engineering. Often, it’s DX.

Whatever path you choose, make sure it’s informed by your developers—not just your budget.

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I originally dived deep into API, Platform Engineering, and DX here:

AI, platform engineering, or DX? How to choose where to invest

📚 Interesting Articles & Resources

🔍 Struggling with outdated diagrams and scattered logs? You’re not alone.

Modern distributed systems are incredibly powerful, and very hard to document and debug. In this upcoming webinar I’ll explore:

❖ Why traditional debugging and documentation workflows drain your team’s time
❖ Where AI actually helps developers
❖ How to build resilient systems and tighter engineering collaboration