From Wrappers to Real Infrastructure

What happened
During an interview on Feb 21, Darren Mowry, who leads Google’s global startup organisation across Cloud, DeepMind and Alphabet, cautioned that startups that simply wrap large language models (LLMs) or aggregate multiple models are running out of runway. He said the industry has little patience for companies whose products are “very thin intellectual property wrapped around Gemini or GPT-5.” Investors now expect deep moats and differentiation, whether through horizontally differentiated platforms or highly specialised vertical solutions. LLM wrappers or aggregators no longer provide sustainable value.

Why it matters
The generative-AI startup landscape is maturing fast. Early traction from simple UI layers on top of foundation models is fading. As enterprises invest serious capital and clouds build their own orchestration layers, only startups with genuine IP or domain depth are likely to survive.

What’s next
Expect consolidation. Wrappers will pivot, merge, or shut down as investors push for defensible technology and vertical integration.

What happened
Samsung expanded its Galaxy AI platform with a multi-agent ecosystem operating at the system level. The company is integrating the Perplexity AI assistant as an additional on-device agent, accessible via a new “Hey Plex” wake phrase or the side button. Galaxy AI coordinates across Notes, Clock, Calendar and other services to reduce app-switching friction.

Why it matters
Smartphone makers are racing to differentiate AI experiences. Embedding multiple agents at the OS layer signals a shift toward orchestration — devices coordinating specialised services rather than relying on a single monolithic assistant.

What’s next
More vendor partnerships and competing multi-agent ecosystems are likely as handset makers escalate AI competition.

What happened
Delegates from 86 countries at the AI Impact Summit in New Delhi issued a statement calling for “secure, trustworthy and robust” AI. The declaration emphasised shared benefits and voluntary cooperation but contained no binding commitments or enforcement mechanisms.

Why it matters
Global recognition of AI’s risks is clear. Global agreement on enforceable rules is not. Voluntary principles may struggle to address misinformation, surveillance, or energy concerns without domestic regulatory follow-through.

What’s next
The UN’s new Independent International Scientific Panel on AI begins work ahead of the 2027 Geneva summit. Watch whether voluntary principles become binding national laws.

What happened
Securin’s 2025 Ransomware Report analysed more than 7,000 victims across 117 threat groups and found generative AI is accelerating ransomware operations. Attackers use AI to draft phishing messages, translate content, and debug scripts. Three groups — Qilin, Akira and CL0P — accounted for nearly 30% of victims.

Why it matters
AI is not fully autonomous in cybercrime — but it lowers friction at every stage. Faster campaign creation and broader scalability increase risk for commercial facilities, manufacturing, IT services, healthcare and government.

What’s next
Expect hybrid attacks blending AI-driven social engineering with infrastructure disruption — and rising investment in AI-powered defensive tools.

What happened
At ZohoDay 2026, Zoho unveiled AppOS, a unified semantic integration layer designed to support humans and AI agents across its business applications. CEO Mani Vembu said generative agents layered onto fragmented systems risk destabilising enterprise architecture. Zoho emphasised domain-specific small language models and energy-efficient infrastructure.

Why it matters
As agentic AI operationalises, fragmentation and governance challenges intensify. Zoho positions itself as a reliability layer — arguing agentic AI will consolidate SaaS rather than eliminate it.

What’s next
Zoho will roll out AppOS across 50+ apps and expand its Vertical Studio programme. Expect similar integration strategies from other SaaS vendors.

What happened
ChipAgents closed a $50M Series A1 round, bringing total funding to $74M. Its coordinated AI agents plan, reason, execute and validate chip design workflows. The company claims 15× faster specification reading, 240× faster assertion generation and 100% code coverage.

Why it matters
Semiconductor complexity is rising while experienced engineers remain scarce. Multi-agent design platforms could compress verification cycles and reshape chip development economics.

What’s next
ChipAgents will expand hiring and deployments with major chipmakers. Competitors may announce rival platforms.

What happened
An AFP report described an “onslaught” of AI agents capable of coding, advising and completing multi-step workflows. Stocks of enterprise software firms dropped sharply amid fears agents could replace collaboration and consulting products.

Why it matters
Agentic AI is shifting from novelty to perceived threat. Market volatility reflects uncertainty about which incumbents adapt — and which are displaced.

What’s next
Expect incumbents to accelerate integration of agentic features while investor sentiment recalibrates.

What happened
A PetaPixel opinion piece argued that generative AI features in cameras could provoke backlash. Early integrations sparked criticism that such tools degrade authenticity and blur the line between real and synthetic images.

Why it matters
Adoption of generative AI in creative tools depends on trust, transparency and artistic values. Technical capability alone will not determine success.

What’s next
Camera makers may experiment cautiously in prosumer lines, emphasising user control and transparency to avoid alienating core customers.

The generative AI market is entering its consolidation phase. Thin wrappers are fading, multi-agent ecosystems are becoming standard, governments are stepping into standards-setting, and investors are recalibrating around operational risk. Agentic AI is now embedded in infrastructure, markets and policy — and the shakeout has begun.