(PDF) The Future of Education: Integrating AI in the Classroom

We Are Entering A New Era Of Coding With Natural Language: Google's Demis Hassabis

More and more tech leaders are saying that coding is set to be dramatically different in the AI era.

Demis Hassabis, CEO of Google DeepMind, recently shared his perspective on the future of coding, suggesting a paradigm shift towards natural language programming. His vision paints a picture where coding becomes accessible to a much broader audience, including creatives and designers, unlocking unprecedented levels of innovation.

"I think we are entering a new era of coding which is going to be very interesting. I think we're going to move into a world where – sometimes it's called 'vibe coding' – where you're basically coding with natural language," Hassabis said.

"We've seen this before with computers. I remember when I first started programming in the 80s, we were doing assembler. Of course, that seems crazy now. Why would you do machine code? You just, you know, you start with C and then you get Python, and so on."

"Really, one could see this as the natural evolution of going higher and higher up the abstraction stack of programming languages, leaving more of the lower-level implementation details to the compiler."

"Now one could just view this as the natural sort of final step: we just use natural language. Then everything is a high-level program, a super high-level programming language."

"I think eventually that's what we may get to. The exciting thing there is that, of course, it makes coding accessible to a whole new range of people – creatives who normally would not have been able to implement their ideas without the help of teams of programmers – designers, game designers, writers. So that's going to be pretty exciting, I think, from the creativity point of view," Hassabis said.

Hassabis isn't the only tech leader who's said that programming will soon look very different. OpenAI CEO Sam Altman has said that the world's best coder will be an AI by the end of the year. Microsoft CTO Kevin Scott has said that 95% of code will be written by AI in the next five years, and Anthropic CEO Dario Amodei feels that we'll get there much sooner. All this means that humans will likely simply give instructions in English of what they want to accomplish, while the actual coding will be done by computers.

This could democratize coding to previously unthinkable levels. The learning curve of being able to program could become substantially smaller, opening up coding to all kinds of non-technical people. This could negatively impact some coders, but others, who can create products and market them, could find themselves being several times more effective than they were previously. It's a time of great change in coding, and coders and non-coders would do well to keep an eye on the rapidly changing landscape.

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Google Adds Natural Language Query Capabilities To AlloyDB

At its Cloud Next conference, Google is showing off a new AI engine for AlloyDB that enables developers to embed natural language questions in SQL queries.

Google is enhancing AlloyDB, its fully managed database-as-a-service (DBaaS), to help developers build applications underpinned by generative AI.

Announced at Google's annual Cloud Next conference, the updates could give the PostreSQL-compatible AlloyDB an edge over PostgreSQL itself or other compatible offerings such as Amazon Aurora.

[ Related: Google Cloud Next '25: News and insights ]

Among the additions, a new AlloyDB AI query engine enables developers to use natural language expressions inside SQL queries.

When Google launched AlloyDB in May 2022 the open-source PostgreSQL was rising in popularity due to its transactional and analytical capabilities, extended support for spatial data, broader SQL support, enhanced security and governance, and expanded support for programming languages. Google saw an opportunity to offer a cloud-based alternative as a service — but it's an opportunity that also attracted the attention of rival Amazon Aurora and Microsoft Azure's Database for PostgreSQL. Now the challenge for Google is to make its offering stand out.

Support for natural language in SQL queries

The arrival of the AlloyDB AI query engine means that developers can now embed free text questions inside SQL queries, even if those depend on less-structured data such as images and descriptions, said Bradley Shimmin, lead of data and analytics practice at The Futurum Group.

This, said ISG Software Research's executive director David Menninger, will ease the burden on developers as they need to be very precise when writing SQL statements.

By way of example, Menninger said, instead of writing "SELECT customer_name FROM customer_table WHERE city in ('Boston', 'Cambridge')", a developer using AI Query could give a narrative description of what they were looking for, such as "list all the customers near the Charles River."

With its new query engine, said Futurum Group's Shimmin, Google is following the trend of database providers converging database operations with semantic and relational query methodologies to expand capabilities of traditional SQL use cases.

Alongside the query engine, Google is adding the next-generation of AlloyDB natural language capability that is expected to allow developers to query structured data inside AlloyDB, thereby helping them build applications that understands an end user's natural language input better.

ISG's Menninger sees the natural language capability as a productivity tool for developers.

"It's often easier to write a natural language query than to write out a SQL statement. It may not be the final SQL statement, but what's generated can be edited so it moves the development process along more quickly," Menninger said.

For the enterprises, the analyst sees the natural language ability making data more accessible for end users.

"You don't necessarily need an analytics tool. You can simply ask the database some questions and get responses. And developers can embed these capabilities in the applications they create benefitting end users," Menninger explained.

Google Agentspace can now search structured data in AlloyDB

As part of the updates to AlloyDB, Google said that enterprises that subscribe to its Agentspace service will now be able to search structured data inside AlloyDB.

The Agentspace service, launched in December, is intended to help enterprises build agents, which in turn can be used to search data stored across various sources.

These agents can also be programmed to take actions based on the data held at different sources within an enterprise, the company said.

dbInsights' chief analyst Tony Baer said the extension of Agentspace to AlloyDB is a logical move as Google expects that enterprises will use agents to work or interact with their data in the future.

More support for migrations and other updates

Other database updates announced at Cloud Next this year includes updated support for migrations, added support for running Oracle's Base Database service, and Model Context Protocol (MCP) support for Gen AI Toolbox for Databases.

The update to migrations comes in the form of the Google Database Migration Service (DMS) now supporting SQL Server to PostgreSQL migrations for Cloud SQL and AlloyDB.

"These new capabilities support the migration of both self-managed and cloud-managed SQL Server offerings, and a range of SQL Server editions and versions," Google said in a statement.

In April last year, Google added Gemini support to the DMS to make migrations faster by supporting conversion of database-resident code.

The Toolbox is an open-source server designed to streamline the creation, deployment, and management of AI agents capable of querying databases.

With industry support for MCP rising, it was inevitable that Google would add support for the protocol to its GenAI Toolbox for Databases, analysts said.

Anthropic introduced MCP last year to make it easier to bring data to LLMs. Since then, it has become a standard means of linking up models, tools, and data resources in support of agentic processes, Shimmin said.

For Menninger, MCP is the emerging standard that enterprises are starting to use to provide context to agents in order to enhance their performance.

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