GCP – How startups can help build — and benefit from — the AI revolution

Startups are at the forefront of generative AI development, pushing current capabilities and unlocking new potential. Building on our Future of AI: Perspectives for Startups 2025 report, several of the AI industry leaders featured in the report joined Jason Calacanis on the “This Week in Startups” podcast’s Startup Basics series, offering their perspective on what’s next for AI.

Memory, multi-agent systems, better UX

Harrison Chase, CEO and co-founder of LangChain, spoke to the impact memory will have on agent continuity, particularly when it comes to contextual knowledge. As memory becomes more common, agents will gain experience (rather than just instructions) on how companies and team members work through feedback, preferences, and more natural subsequent adaptations, enabling deeply personalized interactions. As Jia Li, president of LiveX AI noted, ‘What the users truly appreciate is when AI agents understand their needs and are thinking from their point of view”.

Another exciting prospect is multi-agent collaboration, Chase said, since most AI systems still work in isolation. As agents increasingly collaborate with each other, task management, information sharing, and even delegation of duties in accordance with agent specializations will allow agents to become more efficient and reduce cognitive load for their users. This vision goes beyond simple queries, Yoav Shoham, co-founder of AI21 Labs, explained: “Typically when we speak about agents, what we have in mind is a system that’s not a transactional call to an LLM. The agent can be proactive, it executes complicated flows using multiple tools.”

That’s why Google launched a new, open protocol called Agent2Agent (A2A) — to help AI agents communicate with each other, securely exchange information, and coordinate actions on top of various enterprise platforms or applications. The A2A effort signifies a shared vision of a future when AI agents, regardless of their underlying technologies, can collaborate to automate complex enterprise workflows, to drive new levels of efficiency and innovation. We believe the A2A framework will add significant value for customers, allowing AI agents to work across their entire application estates.

Building trust in a world of autonomous AI

On the topic of multi-agent collaboration, Saurabh Tiwary, VP and GM of Cloud AI at Google, discussed how AI agents are moving beyond simple chat interfaces. He explained that today’s AI agents are designed for indeterminate tasks, and are capable of taking actions, observing outputs, and dynamically determining subsequent steps. This advanced functionality paves the way for agents to manage complex workflows such as autonomously handling emails, identifying critical tasks, and even delegating responsibilities across teams. But for this future to become reality, Saurabh underscored the need for agents to deliver high-quality output, to foster user trust and encourage the delegation of important tasks. Echoing this, LiveX AI’s Jia Li said “we believe humanlike AI agents can create that empathy and trust between consumers and the AI agent.”

At Google, we’re addressing the need for agents to work across diverse environments by offering Agent Development Kit (ADK) and the A2A protocol as open-source.

We recently donated A2A to the Linux Foundation, establishing an open governance body for the protocol. This critical step will help A2A evolve as a universal standard, fostering interoperability between agents built on any platform or using any underlying technology — not just Google’s ADK. With support from over 120 partners, including major hyperscalers like Microsoft and Amazon, this standardization allows for a future where diverse, specialized AI agents can communicate, securely exchange information, and coordinate actions across a business’s entire application ecosystem. 

AI21 Lab’s Yoav Shoham pointed out that for agents to collaborate across different organizations, the fundamental hurdle of ‘semantics’ and ‘shared incentives’ must be overcome. This means that while A2A protocols may specify the syntax of communication, they do not guarantee a shared understanding of the meaning (semantics) of the information being exchanged, and agents from different organizations could have distinct or even conflicting goals, making for misaligned incentives. This presents an opportunity for startups to innovate by designing sophisticated game theory-based protocols, robust governance frameworks, and control mechanisms that ensure agents ‘play nice together’, even when their objectives differ.

Infrastructure performance is booming

At the same time, infrastructure performance is exploding at levels Amin Vahdat, Vice President for the AI and Infrastructure team at Google Cloud, has never seen before. “It’s not uncommon for us at Google to make things twice as fast in three months, and then we do it again three months later, and three months after that, and all of a sudden you have 10X or 20X performance improvements,” said Vahdat on the podcast.

“Twelve months ago, models sometimes struggled to count the number of ‘r’s’ in the word ‘strawberry,’ but today they are writing and executing code”, Vahdat said.

These improvements to model efficiency and performance have shifted the focus away from training and building models toward serving the models and maximizing their utility. Vahdat refers to 2025 as “the year of inference.” 

At Google Cloud Next this April, we introduced our new, seventh-generation Tensor Processing Unit (TPU) called Ironwood, our first TPU specifically designed for inference. Ironwood dramatically improved performance while also improving power efficiency, meaning lower costs and greater workload capacity — all necessities to fuel the age of inference. 

The growth of nimble startup teams

The way AI can augment and amplify human capabilities and efficiency extends well beyond the engineering team, touching every employee in a modern business. 

AI can improve “every job, every function, every workflow,” offering “incredible leverage,” said David Friedberg, CEO of Ohalo Genetics. For example, you can use AI to scan and score hundreds of job resumes in just a couple of hours, a task that previously took days, or to generate comprehensive project plans in hours instead of weeks or months. 

This efficiency means smaller, more nimble teams can achieve results that historically required much larger organizations. “We’ve really just shrunk the amount of time it takes to get from idea to testing and seeing if there’s value,” said Jill Chase, Partner at CapitalG. “That is the most powerful thing for startups.” This has grown startups’ addressable economic opportunities, allowing organizations with 100-200 people to pursue “deep tech” or technically difficult objectives that used to be the realm of thousand-plus-person companies. Companies leveraging AI gain significantly more “shots on goal.”

During Google I/O 2025 we highlighted major advancements in this area, emphasizing development with Gemini 2.5:

• Google AI Studio, powered by Gemini, offers the fastest way for developers to evaluate models and begin building with the Gemini API. It integrates Gemini 2.5 Pro directly into the native code editor, streamlining the prototyping process. Using the Gen AI SDK, developers can instantly generate web applications from simple text, image, or video prompts.

• Accessible via the Gemini API and new tools like URL Context, Gemini 2.5’s advanced reasoning capabilities allow the model to pull information from web pages, helping developers create agentic experiences. Furthermore, Gemini 2.5 Flash Native Audio, available in the Live API, can create agentic applications for speaking and listening in 24 languages with customizable voice and style. That means more natural back-and-forth conversations, with better flow and fewer extraneous sounds.

• Colab’s agent-first experience, powered by Gemini 2.5 Flash, can help developers with complex tasks like fine-tuning models and building UIs, significantly reducing coding time. These tools make building faster, easier, and more efficient, so developers can focus on bringing their ideas to life.

Empowering startups to innovate more with less

At Google Cloud, we’re deeply committed to fostering innovation, providing not only cutting-edge tools and infrastructure, but also essential resources and expertise to help startups leverage AI effectively. No matter where you are with AI adoption, we’re here to help: Book your generative AI consultation today, get up to $350,000 USD in cloud credits with the Google for Startups Cloud Program, or contact our Startup team.

For more comprehensive insights into the future of AI and how Google Cloud can accelerate your startup’s growth, download the Future of AI: Perspectives for Startups 2025 report today.