OpenAI, Anthropic Announce Multiple Job Openings in India

Leading US-based AI companiesOpenAI and Anthropic have expanded their global hiring efforts with a slate of roles specifically targeting talent in India, reflecting the companies’ growing focus on the region as it builds out local operations.

OpenAI currently lists nine open positions with India locations (Delhi office and remote options) spanning sales, customer success, growth, partnerships, and technical roles.

Several of the roles are focused on sales and revenue growth. These include Account Director positions for Digital Natives, Large Enterprises and Startups. The roles involve managing the full sales cycle, working with engineering and product teams, and helping customers adopt OpenAI’s models and tools for business use cases.

On the customer success side, OpenAI is hiring an AI Deployment Manager in India. The role centres on supporting enterprise customers during implementation, ensuring AI systems are deployed responsibly and deliver measurable outcomes. The company is also hiring a Growth Lead for India, a role focused on driving adoption, usage, and engagement of OpenAI products through local growth strategies, partnerships, and market insights.

Notably, Pragya Misra, public policy and partnership lead, was the company’s first Indian hire. Earlier this year, OpenAI hired Raghav Gupta, former Asia-Pacific MD at Coursera, to lead its education division in India and the APAC region.

The company also appointed Sheeladitya Mohanty as marketing lead and Akash Iyer as social lead for India.

OpenAI is also expanding its partnerships and technical teams in the country. The Product Partnerships Lead role will focus on building and managing strategic partnerships to support product distribution and adoption in India.

Meanwhile, technical roles such as Solutions Architect, Solutions Architect for Startups, and Solutions Engineer are aimed at helping customers and developers design, deploy, and scale applications using OpenAI’s models, while addressing reliability, safety, and performance requirements.

Anthropic is also hiring for roles in India. The company is hiring for two sales-focused positions–Enterprise Account Executive and Industries and Startup Account Executive, in Bangalore.

This recruitment push comes alongside announcements from both OpenAI and Anthropic about opening offices in India. The country has already emerged as one of the most active markets globally for both AI startups, reflecting India’s growing role in their expansion strategies and long-term plans.

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Lovable Raises $330 Mn in Series B Funding at $6.6 Bn Valuation

Vibe coding platform Lovable has raised $330 million in a Series B funding round at a valuation of $6.6 billion, the company said. The round was led by CapitalG and Menlo Ventures’ Anthology fund, with participation from new and existing investors.

The funding round included investments from NVentures, Salesforce Ventures, Databricks Ventures, T.Capital, Atlassian Ventures and HubSpot Ventures, along with Khosla Ventures, DST Global, EQT Growth, Kinship Ventures, and returning investors such as Accel and Creandum.

Lovable said the capital will be used to deepen integrations with enterprise software tools, expand collaboration and governance features for teams, and strengthen infrastructure that supports moving products from prototype to production.

“Lovable has done something rare: built a product that enterprises and founders both love,” said Laela Sturdy, managing partner at CapitalG. “The demand we’re seeing from Fortune 500 companies signals a fundamental shift in how software gets built,” she said.

The company said more than 100,000 projects are created on its platform each day, with over 25 million projects built in its first year. Websites and applications built using Lovable recorded more than 500 million visits in the past six months, it added.

Lovable said its platform is being used by enterprises such as Deutsche Telekom, Klarna and Zendesk to build prototypes and internal tools.

Jorge Luthe, senior director of product at Zendesk, said, “What once took six weeks — from idea to working prototype — now takes just three hours.”

The company said founders are also using the platform to build commercial products, with several startups reaching revenue milestones within months of launch.

Lovable said the latest funding will support broader adoption across teams and organisations as more non-technical users build and ship software products.

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With $125 Mn haul, Mythic Wants to Take on NVIDIA GPUs with 100x Energy-Efficient AI Chips

Mythic, a Palo Alto-based AI chip company, has raised $125 million in a funding round to develop analog processing units designed to cut AI energy use by up to 100x compared with GPUs.

The round was led by deep tech-focused venture capital firm DCVC and will support Mythic’s product development, software, and commercial scale-up efforts.

NEA, Atreides, Future Ventures, Softbank KR, S3 Ventures, Linse Capital, One Madison Group, and Catapult, along with Honda Motor and Lockheed Martin, also joined the round.

The company said the raise follows a restructuring under chief executive officer Taner Ozcelik (former NVIDIA VP and GM), and focuses on addressing power constraints in AI computing. “Energy efficiency will define the future of AI computing everywhere,” Ozcelik said in a statement.

Mythic plans to deploy its chips across data centres, automotive systems, robotics, and defence. The 13-year-old company will also use the funding to rebuild its architecture, software stack, and strategy.

The company also introduced Starlight, a sub-one-watt sensing platform that integrates its chips into image sensors. Mythic said the system improves signal extraction in low-light conditions and targets defence, automotive, and robotics use cases.

Mythic’s chips are manufactured in the United States and allied countries using standard semiconductor processes. The company plans to use the new capital to expand production, mature its software development kit, and pursue commercial deployments in AI inference markets.

Mythic’s chips use analog in-memory computing, which combines memory and processing in a single plane. The company said this design reduces energy loss during data movement, which it claims accounts for most of the power consumption in current AI systems.

According to Mythic, its current architecture delivers 120 trillion operations per second per watt.

Ozcelik said the company aims to complement GPUs rather than replace them. “Much as GPUs became the accelerated computer of choice next to CPUs, our APUs will become the accelerated computer of choice next to GPUs,” he said.

Mythic said its chips can run large language models with up to one trillion parameters without requiring high-speed interconnects used by GPU clusters. Internal benchmarks cited by the company show higher tokens per second per watt compared with current high-end GPUs.

Aaron Jacobson, partner at NEA, said the platform “collapses today’s limits on energy and cost” and gives the company scope to scale. Steve Jurvetson of Future Ventures said Mythic’s approach unifies computation and memory “as in the brain,” improving efficiency.

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11 Times Coding Died in 2025

In 2025, declaring the death of software engineering became a recurring sport in Silicon Valley. Founders, CEOs, and AI researchers lined up to announce that code was about to write itself, and engineers were about to become optional. None of it quite played out that way. But, the declarations themselves defined the year.

Mark Zuckerberg and the Mid-Level Engineer Apocalypse

In January 2025, Meta CEO Mark Zuckerberg told the Joe Rogan Experience that AI would soon replace mid-level engineers across the industry. He framed it as an economic inevitability rather than a moral choice. “A lot of the code we have in our apps will be built by AI engineers instead of people engineers.”

The comment landed hard because it came from a company that employs thousands of developers. For many engineers, this was the moment casual anxiety turned into something sharper.

Dario Amodei’s Three to Six Month Countdown

Anthropic CEO Dario Amodei delivered one of the boldest timelines of the year while speaking at the Council on Foreign Relations. “I think we will be there in three to six months, where AI is writing 90% of the code. And then, in 12 months, we may be in a world where AI is writing essentially all of the code.”

The quote ricocheted through tech Twitter and VC decks alike. It became shorthand for how fast things were supposedly moving.

Marc Benioff Puts Engineering Hiring on Ice

Salesforce CEO Marc Benioff moved from prediction to policy. In January, he publicly said the company was debating whether to hire any engineers at all in 2025.

Benioff said they are seriously debating if they need to hire anybody this year. He cited 30% productivity gains from AI agents. This isn’t a future scenario, but a real hiring conversation at a $200 billion company.

Sam Altman and the Race to the World’s Best Coder

In February, OpenAI CEO Sam Altman said the quiet part out loud. He predicted that by the end of 2025, an AI system would be the best programmer in the world. He pointed to internal benchmarks showing OpenAI’s reasoning model climbing competitive programming leaderboards and said they would “hit number one by the end of this year.”

Software engineering, in this framing, was just another leaderboard waiting to be topped.

Sundar Pichai’s Ever-Rising Code Percentages

Google CEO Sundar Pichai did not declare engineers obsolete outright. He let the numbers do the talking. In October 2024, he said over 25% of Google’s new code was AI generated. By June 2025, that figure had crossed 30%. Each earnings call pushed the number higher and fed speculation about where it would stop. The implication was clear even if the word “replacement” was never used.

Jensen Huang Declares a New Programming Language

At London Tech Week in June, NVIDIA CEO Jensen Huang delivered one of the most quoted lines of the year. “There’s a new programming language. It is called ‘human’.” Traditional programming, he argued, was effectively dead. The future was about describing intent and letting machines do the rest.

It sounded liberating. It also sounded like a eulogy for hard technical skill.

Satya Nadella Quantifies the Shift Inside Microsoft

Microsoft CEO Satya Nadella revealed between April and June that 20% to 30% of Microsoft’s internal codebases were already written entirely by AI. He shared this casually, almost as a progress update. Coming from a company with tens of thousands of engineers, the message landed quietly but heavily. This was not a lab demo. This was production code.

Tobias Lütke Flips the Burden of Proof at Shopify

In April, a leaked internal memo from Shopify CEO Tobias Lütke made headlines across tech. AI use was now a “fundamental expectation.” Teams had to prove that AI could not do a task before asking for more people. The default assumption was no longer that work needed engineers. Engineers had to justify themselves.

Duolingo Goes “AI First”

Duolingo CEO Luis von Ahn announced an “AI First” strategy that same month. The company would “gradually stop using contractors to do work that AI can handle.” Managers were required to show that AI could not do a job before hiring humans. By August, 80% of Duolingo engineers were using AI tools daily. The message was not subtle. Adapt or get out of the way.

Bill Gates Says Humans Will Be “Unnecessary for Most Things”

Across interviews in 2025, Bill Gates delivered the widest version of the claim. He said AI would make humans “unnecessary for most things” within a decade. Software development was a central example. He added that if he were starting a company today, it would be “AI-first.” When one of the original architects of the software industry talks this way, people listen.

Arvind Krishna and IBM’s 30% White-Collar Shock

IBM CEO Arvind Krishna framed the threat more broadly, but software engineers were firmly in the blast radius. In multiple interviews through 2025, he said AI could replace up to 30% of white-collar jobs. He paired the warning with reassurance, arguing that total employment would still grow.

The contradiction did not go unnoticed. On one hand, mass displacement, and on the other, optimism. For engineers, the takeaway was simpler than the nuance. A third of roles were on the line, and no one was pretending software was exempt.

The Irony

By the end of 2025, none of these predictions had fully materialised. AI did not write 90% of the world’s code. Software engineers were not wiped out. Hiring freezes quietly softened. Teams still needed people who understood systems, trade-offs, and failure modes. What did survive were the quotes.

Together, they form a perfect time capsule of a year when confidence ran far ahead of reality.

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Oracle Brings Oracle Database@Google Cloud to India

Oracle has launched Oracle Database@Google Cloud in India, allowing customers to run Oracle database services directly within Google Cloud’s Mumbai region, as enterprises increase adoption of multicloud strategies and data residency requirements tighten.

The service gives Indian customers access to Oracle Exadata Database Service on Dedicated Infrastructure, Oracle Autonomous AI Database, and Oracle Autonomous AI Lakehouse via Google Cloud’s Asia-South 1 region, while ensuring data remains in-country to meet regulatory and compliance needs.

It also allows Oracle and Google Cloud partners to resell the service via the Google Cloud Marketplace.

“As enterprises in India increasingly adopt multicloud strategies, Oracle Database@Google Cloud provides the flexibility, performance, scale, and security they need,” said Shailender Kumar, senior vice president and regional managing director, Oracle India. “Customers in India can now integrate Oracle AI Database capabilities with Google Cloud’s AI and analytics tools and services.”

Google Cloud said the launch will support customers looking to modernise applications and migrate workloads. “Oracle Database@Google Cloud combines Google Cloud’s AI and analytics with Oracle’s database services to help organisations across India accelerate IT modernisation,” said Sashi Sreedharan, managing director, Google Cloud India.

The offering allows enterprises to combine data stored in Oracle databases with Google Cloud services such as BigQuery, Vertex AI and Gemini models, enabling analytics, AI-driven applications and workload migration across platforms.

As part of the rollout, Oracle and Google Cloud have also introduced a partner program in India that allows eligible partners from both ecosystems to purchase and resell Oracle Database@Google Cloud through private offers on the Google Cloud Marketplace.

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Google Launches Gemini 3 Flash, Promises Faster Performance and Lower Costs

Google has rolled out Gemini 3 Flash, a new AI model for developers that the company claims delivers faster performance and lowers costs while retaining advanced reasoning and multimodal capabilities.

The company is making the frontier intelligence model accessible through the Gemini API via Google AI Studio, Gemini CLI, Android Studio, agentic development platform Google Antigravity, and for enterprise customers through Vertex AI.

Gemini 3 Flash is priced at $0.50 per million input tokens and $3 per million output tokens, with additional cost reductions through context caching and batch processing.

“Today we’re introducing Gemini 3 Flash, our latest model with frontier intelligence built for speed at a fraction of the cost,” said Logan Kilpatrick, group product manager at Google DeepMind.

According to Google, Gemini 3 Flash builds on the capabilities of Gemini 3 Pro and outperforms Gemini 2.5 Pro across several benchmarks, while operating up to three times faster. It stated that the model supports multimodal reasoning, coding, agentic workflows, and visual understanding, including code execution for tasks such as counting, zooming, and editing visual inputs.

Google said the Flash series remains its most widely used model family, processing trillions of tokens across hundreds of thousands of applications. With Gemini 3 Flash, the company aims to support large-scale production use cases that require lower latency and higher rate limits.

Early users have already integrated the model into products spanning software development, gaming, document analysis, and deepfake detection. Google also recently introduced CC, an experimental AI productivity agent developed by Google Labs, to help users manage daily tasks and organise their workday more efficiently.

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Zuppa Geo Navigation, IISc Bengaluru Set Up Drone Centre of Excellence

Zuppa Geo Navigation Technologies has partnered with the Indian Institute of Science (IISc), Bengaluru, to establish a drone centre of excellence (CoE) at IISc’s department of mechanical engineering to advance indigenous unmanned aerial vehicle (UAV) technologies.

The centre will focus on research, design, and testing of drone systems, with an emphasis on autonomous platforms, aerial systems, and cyber-physical integration. The initiative aims to support India’s efforts to strengthen domestic UAV capabilities across sectors, including defence, agriculture, logistics, disaster management, and smart cities.

This comes after the company partnered with Chennai-based Garuda Aerospace in March this year.

The CoE will combine Zuppa’s cyber-physical technology stack with IISc’s research expertise in aerodynamics, robotics, control systems, and systems engineering. According to the partners, this collaboration is intended to accelerate the development of homegrown drone technologies suited to Indian operational and environmental conditions.

“At Zuppa, our mission has always been to spearhead indigenous innovation in UAV and navigation systems,” said Sai Pattabiram, founder and managing director of Zuppa. “The establishment of this centre of excellence at IISc represents a milestone in our journey, as it brings together academic excellence with industry-driven technological leadership.”

He added that the partnership aims to create solutions that can scale beyond domestic applications and meet global benchmarks.

A senior representative from IISc’s department of mechanical engineering said the collaboration would help bridge the gap between academic research and industry deployment.

“By establishing this CoE in collaboration with Zuppa, we aim to advance UAV research that integrates deep scientific insights with practical industry applications,” the representative said. “This partnership will create a strong foundation for innovations in drone design, autonomy, and performance.”

The drone CoE will also support training and research programmes for students and engineers, with a focus on building long-term capabilities in UAV design, autonomy, and system performance.

The initiative aligns with broader national efforts to promote self-reliance in critical technologies and strengthen India’s drone ecosystem through industry–academia collaboration.

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