Big Tech is powering the age of agentic AI innovation
Sep 2, 2025
Big Tech is accelerating the uptake of agentic AI by equipping developers to serve as co-architects of next-generation AI agents. That’s the main takeaway from a new article from Yahoo Finance.
Big Tech focuses on the role of developers
The article, citing a report from GlobalData, points out how Big Tech companies are launching developer-oriented platforms and frameworks in recognition of the developer community as a co-architect of agentic AI. Among the initiatives highlighted are Microsoft’s Magnetic-One multi-agent architecture, its AutoGen open-source framework for building AI agents, the Semantic Kernel software development kit, and the AI Workbench development environment.
Google’s contributions include Project Astra, Vertex AI Agent Builder, and Gemini 2.0 Flash, all of which expand the company’s AI agent ecosystem. Its Agentspace offering provides multi-model search for enterprises, blended retrieval-augmented generation, first-party ingest, and third-party connectors. Google has also announced Memory Bank for the Vertex AI Agent Engine, a persistent-memory feature designed to help AI agents remember long-term context and user preferences across sessions.
Agentic AI startups are also driving innovation. Ada focuses on customer service, creating agents that resolve customer queries; Ema builds agents that augment the employee experience; and AIQ develops solutions for the oil and gas sector, applying agentic AI to drilling performance, reservoir management, and quality control.
At the center of this transformation is the role of the developer. Big Tech firms are investing in tools that go beyond passive code suggestions or search assistance. Instead, they enable developers to collaborate with AI systems that can anticipate needs, propose solutions, and act with independence.
By positioning developers as co-architects, Big Tech companies are acknowledging that the real breakthroughs will not come from AI replacing human talent, but from AI and humans working side by side. Developers define goals, shape workflows, and set parameters, while AI agents increasingly manage execution, adaptation, and scale.
Why it matters: the agentic leap
Agentic AI represents a leap beyond assistive tools, empowering systems to take initiative, evaluate context, and act with independence. In some coding environments, AI already generates up to 30% of a codebase, which frees up developers to focus on design, logic, and strategy.
Yet, the promise comes with challenges. While enterprise tools show early promise, consumer-facing use cases often remain buggy or unreliable. Experts warn the technology is nascent, with strength in specific domains, like coding, while broader applications remain fragile.
Beyond tooling, what’s emerging is a shapeshifting Agentic Web, a network of AI agents communicating, collaborating, and orchestrating complex workflows across the internet. According to Gartner, by 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024.
Growing pains and strategic stakes
While optimism runs high, enterprises still wrestle with core challenges: reliability, trust, oversight, and integration into existing systems.
Some veteran tech commentators stress that while agentic AI promises transformative potential, we are not yet at a plug and play level for everyday users. The agents work in select scenarios, but broader adoption still requires robust foundational infrastructure, especially in realtime data handling, monitoring, and governance.
Centific powers the foundation of agentic AI
True scalability of agentic AI demands solid infrastructure that keeps agents working, trustworthy, and adaptable.
An AI data foundry platform provides exactly that. Centific’s AI Data Foundry enables businesses to:
Unify fragmented data into clean, contextualized formats ready for agent consumption.
Annotate data with expert input to ensure high-quality model training.
Stream data in real time to keep agents current with evolving contexts.
Simulate rare or edge cases using synthetic data to build resilience.
Monitor performance and update agent behavior over time.
Develop and orchestrate multiple agents efficiently and safely to deliver real business impact.
With this infrastructure, agents evolve with the real world, maintaining reliability, adaptability, and value.
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Big Tech
Microsoft
Agentic AI
AI innovation
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