In January, Ars Technica published a sharp piece, “Amid a flurry of hype, Microsoft reorganizes entire dev team around AI.” It described how Microsoft is combining its developer division, AI platform teams, and core engineering functions into a single group called CoreAI – Platform and Tools.

“We are creating a new engineering organization: CoreAI – Platform and Tools.”

Microsoft’s own announcement framed the move as a platform reset, not a feature add-on.

“2025 will be about model-forward applications that reshape all application categories… More so than any previous platform shift, every layer of the application stack will be impacted… Thirty years of change is being compressed into three years!”

That’s not about efficiency. It’s a declaration of intent to rebuild the foundation of the developer ecosystem around AI. (The “30 years into three” line appears across coverage of Nadella’s memo.)

Why It Matters

This isn’t a normal reorg. It’s a public acknowledgment that software itself is changing form. Applications are evolving from static bundles of code into adaptive systems that learn, iterate, and interact. If history teaches anything, it’s that platform shifts reward speed over size. Incremental thinking simply can’t keep up with exponential technology.

AI compounds on itself: better models yield better tools; better tools yield better models; each cycle tightens the loop. Microsoft is signaling that this feedback loop is the new battleground.

Three Signals Worth Noticing

• The baseline is shifting. AI isn’t a feature anymore—it’s the platform. Build for AI, not just with it.
• Velocity is now strategy. “Thirty years in three” isn’t a slogan; it’s a timetable.
• Boldness wins. Every major inflection point—from the web to mobile to cloud—rewards early, learning-centric bets.

Patterns We’ve Seen Before

Two prior essays connect directly:

• Building a Recommendation Culture (2014): clarity and decisiveness as competitive advantages.
• Wait for It (2020): impatience as a design principle—fast response feels like quality.

Those dynamics now apply at the organizational level. The teams that can decide, adapt, and ship in days—not quarters—will separate from the pack.

Three Concrete Action-Steps

This shift isn’t academic. It’s operational. Based on Microsoft’s reorganization and broader AI trends, here are three moves to make now—whether you’re in engineering, product, marketing, or strategy.

1) Audit Your Stack for “AI-First” Readiness

• Map your current architecture, tooling, and ecosystem. Are you still assuming long release cycles, feature kits, and monolithic updates—or continuous iteration, model deployment, and human–agent interactions?
• Identify legacy assumptions to retire: “code is written once,” “features ship quarterly,” “models are static.”
• Choose one project this quarter to re-architect for agentic behavior (memory, context, action space). Microsoft’s benchmark: “We will build agentic applications with memory, entitlements, and action space.”

2) Shift the Team Mindset: From “Add AI” to “Rethink the Stack”

• Run a workshop with dev, product, and design: “If we built our stack from scratch today, knowing what we know about AI, what would we do differently?”
• Encourage one bold scenario per team—the kind that feels a little uncomfortable because it’s truly transformative.
• Measure progress by speed and agility (feedback-loop time, model refresh cadence, agent capabilities). As Microsoft’s Bay Area post put it: “Speed and iteration are key… Teams that stay on their toes will have the most success.”

3) Position Your Business for the Emerging AI Platform Ecosystem

• Vendors/partners: Microsoft is unifying developer tools, AI platforms, Azure infrastructure, and GitHub into one operating model—new opportunities (and risks) for ISVs and integrators. Where do you fit in the new baseline?
• Enterprise buyers: Treat AI-platform readiness as strategic. The stack you select now will shape competitiveness for the next decade.
• Messaging: Don’t say “we added AI.” Say “we’re building on the new stack.” Align language to platform, agents, and continuous change.

Five Predictions for 2026–27: The Age of Seismic Software

The Microsoft announcement is a tremor in a larger continental drift—the moment when AI stops being an add-on and becomes the substrate of software.

1) Developers Become Orchestrators

By 2026, much “net new” code and refactoring is executed by AI systems. Humans set goals, constraints, and brand voice—more creative director than coder.

2) Every App Will Have Memory and Personality

Software will remember context, adapt tone, and build rapport. Differentiation shifts from interface polish to continuity and care.

3) Software Experience Management (SXM) Reaches the Boardroom

Boards will demand continuous experience metrics: retention drivers, silent failure points, churn risk—surfaced by agents. SXM becomes executive oxygen.

4) The AI Economy Polarizes

First movers compound advantage via tighter learning loops; late adopters manage decline on an outdated architecture.

5) The Human Renaissance

As AI absorbs routine reasoning, creativity surges. The barrier between concept and artifact shrinks. For a skills refresh, revisit This Reading List Will Make You a Better Marketer—curiosity compounds faster than capital.

The Constant: Seismic Change

Every era starts as a reckless bet and ends as the new normal. This one will be no different.

Boldness is the new competence.
Seismic change is the new stability.

We only get one run at this—one life, one arc, one chance to build something extraordinary. Let’s make it exciting.