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From multimodal models to autonomous agents, the AI landscape has matured significantly — but so have the complications. A look at where things actually stand.

After years of over-investment and rapid expansion, the startup landscape is recalibrating. Capital is more selective and the bar for growth has shifted.

Three years on, the tech industry has settled into something messier and more interesting than either side of the debate predicted.

Antitrust scrutiny, data protection rules, and AI governance frameworks are converging. The era of building first and sorting out the rules later is winding down.

The software stacks running the world's largest companies increasingly depend on projects maintained by volunteers. That's a structural shift, not a vulnerability.

Attackers are leveraging AI to move faster and target more precisely. The industry knows it and is responding — but the gap remains significant.

As AI systems become more capable and embedded in decision-making, the question of who is accountable — and for what — has moved from theory to operations.

The tooling developers rely on every day is undergoing a fundamental rethink. AI-assisted coding is only part of the story — the bigger shift is about time allocation.