What could be a company’s worst AI nightmare? An autonomous AI agent going out of control and wrecking core business systems. That scenario reportedly became reality for a US-based startup when its AI coding agent erased the company’s entire database in just nine seconds. Jer Crane, founder of the SaaS platform PocketOS, shared the incident on X. He stated that an AI coding agent—Cursor powered by Anthropic’s Claude Opus 4.6—accidentally deleted their production database along with all volume-level backups in a single API request to their infrastructure provider Railway. The entire incident reportedly took only nine seconds.

PocketOS develops software used by rental businesses, especially car rental operators, to manage operations such as bookings, payments, customer data, and vehicle tracking. Crane emphasized that some customers had been using the platform for years and depended on it completely for their day-to-day operations.

Explaining how the data loss happened, Crane said the AI agent was performing a routine task when it encountered a credential mismatch. Instead of seeking help or verification, the agent attempted to resolve the issue independently and ended up deleting a Railway volume. He added that the AI then searched for an API token and found one stored in a file unrelated to its current task. That token was originally meant for managing custom domains through the Railway CLI. According to Crane, the deletion process did not include any safety checks or confirmation prompts—no warnings, no verification steps, and no environment restrictions.

When questioned, the AI reportedly admitted it acted without proper caution, acknowledging it should have verified the action instead of proceeding with a destructive operation. Crane also clarified that the company was using a fully capable enterprise-grade model, not a limited or experimental version. This is not an isolated case. Similar incidents have been reported before, including one where Cursor AI deleted tracked files and shut down processes despite explicit instructions not to, and another where an AI agent at Replit reportedly wiped an entire production database of a startup.
Disclaimer: This image is taken from Business Standard.

India and Germany are set to jointly develop a 5‑tonne unmanned aerial vehicle (UAV) platform called AeroForce X, marking a significant step in their defence‑technology cooperation. The project will pair German sensor and mission‑systems expertise with Indian engineering and manufacturing capabilities to create a high‑endurance, long‑range surveillance drone tailored to Indian operational needs.

The collaboration is being led by German firm Aerodata and Indian aerospace startup Dynauton, which have formalized a German‑Indian partnership for the unmanned air vehicle platform. The AeroForce X is being designed as a medium‑altitude, long‑endurance (MALE) UAV weighing around 5 tonnes, capable of flying for up to 40 hours in a single mission.

This endurance makes it suitable for extended intelligence, surveillance and reconnaissance (ISR) sorties over land and sea, including difficult terrain such as the Himalayas and vast maritime zones in the Indian Ocean region. The platform will be scalable to carry different sensor suites, including radar, electro‑optical/infrared systems, and electronic‑intelligence (ELINT) packages, depending on the mission.

The AeroForce X initiative comes on the heels of a broader defence industrial cooperation roadmap signed between India and Germany in early 2026. That agreement promotes joint development and co‑production of platforms such as submarines and armed UAVs, shifting the relationship from a traditional buyer–seller model toward deeper industrial and technology integration. The project offers faster access to advanced sensor and mission‑system integration know‑how, while giving German firms like Aerodata a foothold in India’s rapidly growing defence‑electronics and UAV ecosystem. It also opens potential export avenues for the platform into other emerging‑market armed forces that need cost‑effective, long‑endurance ISR assets.

A 5‑tonne UAV with 40‑hour endurance can cover large stretches of India’s northern and western borders, as well as key maritime approaches, reducing the need for frequent aircraft rotations and refuelling. Such a platform can support border surveillance, maritime domain awareness, anti‑piracy operations, and other security missions where persistent coverage is critical.

The AeroForce X could evolve into a multi‑role system by integrating electronic‑warfare payloads or even limited strike capabilities, aligning with India’s broader push to field armed UAVs and networked digital‑battlefield architectures. The project also dovetails with India’s “atmanirbhar” (self‑reliant) defence manufacturing push, where foreign partnerships act as technology enablers rather than permanent dependencies.

Beyond the immediate hardware, the collaboration is expected to strengthen India’s domestic UAV supply chain. Dynauton brings engineering and manufacturing experience in unmanned systems, while Aerodata contributes deep expertise in airborne surveillance and reconnaissance integration. The partnership could accelerate local production of airframes, avionics, and ground‑control infrastructure, while nurturing design, testing, and systems‑engineering capabilities for future indigenous platforms.

As India invests heavily in AI‑driven drone swarms and networked command structures, a capable MALE‑class UAV like AeroForce X can serve both as a sensor node and a communications relay, feeding real‑time data into joint operational headquarters. Seen together, the Indo‑German UAV project is not just about building another drone—it is about shaping how India monitors its borders, projects power, and integrates its growing unmanned fleet into the future battlefield.
Disclaimer: This image is taken from Indian Defence Research Wing.

Over the past 25 years, Elon Musk has helped transform space travel, turning space exploration into successful commercial ventures. Now, SpaceX is shifting its focus toward an even larger opportunity: developing artificial intelligence for enterprise use. According to an S-1 filing reviewed by Reuters, SpaceX estimates its total addressable market could reach $28.5 trillion, a key figure that reflects the maximum possible revenue if it captured the entire market. The company expects over 90% of this opportunity—around $26.5 trillion—to come from the AI sector, with $22.7 trillion specifically linked to enterprise AI.

The filing also indicates that SpaceX is preparing for a potential IPO this summer, aiming for a valuation of about $1.75 trillion and planning to raise roughly $75 billion, which could make it the largest IPO ever. SpaceX described this opportunity as potentially the largest total addressable market in history. However, this contrasts sharply with its current revenue sources.

Although TAM is not a financial forecast or valuation, it is widely used by investors to assess long-term growth potential. Companies often present large TAM figures; for example, Uber estimated a $5.7 trillion opportunity at its 2019 IPO. The filing highlights Musk’s broader ambition to play a central role in artificial intelligence. The enterprise AI space is currently led by competitors such as OpenAI and Anthropic, both also preparing for public offerings.

SpaceX’s acquisition of xAI, founded by Musk in 2023, is still in its early stages and is currently operating at a significant loss. In 2025, xAI reported an operating loss of $6.4 billion, compared to $1.6 billion the previous year. These losses exceeded the $4.4 billion operating profit from Starlink, SpaceX’s satellite internet division, which generated $11.4 billion out of the company’s $18.7 billion total revenue. Overall, SpaceX reported a net loss of $4.9 billion.

Investment in AI has also driven heavy spending, with total capital expenditure reaching $20.7 billion in 2025, of which $12.7 billion was directed toward AI-related development—more than space and connectivity combined. SpaceX also outlined plans to invest in GPU manufacturing, expand its sales teams, and deploy engineers directly to client organizations to support AI adoption. Despite these ambitions, some observers remain skeptical, arguing that market valuations may be driven more by expectations than by currently visible business performance.
Disclaimer: This image is taken from Reuters.

India has become one of OpenAI’s fastest-growing AI markets, with weekly active users rising sharply and reportedly crossing 100 million. It is now the company’s second-largest market after the United States, with strong usage in areas like coding, reasoning, and data-heavy tasks. The key question is no longer just about adoption, but whether this large-scale usage in India can be converted into meaningful revenue. For OpenAI, India is emerging as a critical testing ground to understand whether AI can be monetised outside Western markets.

From an investor perspective, the outcome carries high stakes. If successful, India could become a model for expanding AI monetisation across other emerging economies. If not, AI revenue may remain largely dependent on developed markets. At present, India is still primarily a usage-driven market rather than a revenue-driven one. Experts note that while usage generates valuable data and helps improve AI systems, it does not automatically translate into strong monetisation.

OpenAI’s approach in India appears to be built on multiple fronts, including making services more affordable for consumers, focusing on enterprise clients where real revenue is expected, investing in local infrastructure to support performance and data needs, and building an ecosystem through developers and training initiatives.

Despite this strategy, monetisation challenges remain. India’s digital market has historically shown high adoption but lower willingness to pay, with businesses prioritising clear return on investment rather than access alone. While India offers massive scale and strategic value for AI development, turning that scale into consistent revenue remains uncertain and will likely depend on enterprise adoption and real-world business outcomes.

Disclaimer: This image is taken from Business Standard.

In 1998, tobacco companies in the United States were made responsible for the damage caused by the products they produced and sold through the Tobacco Settlement. Today, a similar question arises for Big Tech: it is not only about the content on their platforms but also whether these platforms were intentionally created to keep users addicted. Daniel Martin explores this issue with Rajesh Sreenivasan, Head of Technology, Media, and Telecommunications at Rajah and Tann Singapore.

Disclaimer: This podcast is taken from CNA.

In Singapore, mental health professionals are noticing a small but increasing number of patients showing delusions, paranoia, or emotional dependence seemingly connected to frequent AI chatbot use. Although “AI psychosis” is not an official medical diagnosis, clinicians acknowledge that the issue is genuine. How does extensive interaction with AI blur the boundaries between reality and reinforcement? Who is most vulnerable, and what signs should families be aware of? Andrea Heng and Hairianto Diman discuss these questions with Dr. Amelia Sim, Senior Consultant at the Department of Psychosis, Institute of Mental Health.

Disclaimer: This podcast is taken from CNA.

With decisions delegated, chatbots replacing friends, and nature sidelined, Silicon Valley is shaping a life stripped of real connection. Escape is possible—but it will require a united effort.

Disclaimer: This podcast is taken from The Guardian.

Google has revealed plans for a significant increase in its AI investments in Singapore, featuring the launch of Majulah AI – a collection of training and innovation initiatives aimed at developing an AI-ready workforce. Daniel Martin speaks with Ben King, Managing Director of Google Singapore, about how these efforts will help Singapore achieve its goal of becoming an AI leader and accelerate AI adoption across the nation.

Disclaimer: This podcast is taken from CNA.