AT&T’s Bold Bet on Workforce Upskilling in India - Related to real, is, cursor, workforce, upskilling

AT&T’s Bold Bet on Workforce Upskilling in India

Given that AI skills are no longer optional, there remains a pertinent challenge for corporates as most workforces are not yet fully equipped to meet this skyrocketing demand. For global capability centres (GCCs) like AT&T, it’s a double-edged sword, presenting both opportunities and challenges in talent management and hiring.

In an , Santosh Bijur, CEO of AT&T Communication Services India, recounted the MNC’s journey in India, which began nearly 40 years ago, making history as the first foreign telecom carrier to secure International Long Distance (ILD) and National Long Distance (NLD) licenses.

Over the past 10-15 years, the company has expanded its footprint, establishing the IDC, a key pillar of AT&T’s global innovation strategy. “The team here in India has almost 3,300 employees. Out of that, our GCC, which we call the India Development Center, has over 2,000 people,” Bijur said.

Having a strong presence in Hyderabad, Bengaluru and Chennai, AT&T has successfully tapped into a rich telecom talent pool. However, as AI and automation reshape the industry, upskilling has become a priority.

Bijur explained that one of AT&T’s key enablers in this transformation has been its partnerships with leading Indian educational institutions.

Many of the institutions the organization collaborates with—such as Chennai Institute of Technology and KL University in Hyderabad—have proactively introduced AI electives into their curriculum.

“The colleges have already incorporated AI into their programs by providing electives to the students, so they come almost AI-ready when they join us,” Bijur stated.

This, in turn, reduces the learning curve for the employees, allowing them to contribute effectively from day one. For experienced professionals, Bijur explained, AT&T has introduced continuous learning programs that help them adapt to AI-driven workflows.

Through its Personalised Learning Environment (PLE) platform, employees can access a wide range of upskilling courses, making learning both accessible and self-driven.

AT&T doesn’t see this as a Herculean task. It believes learning is a shared responsibility, where employees are encouraged to take ownership of their AI journey.

Bijur said the company’s AI transformation began in early 2024 with the launch of ‘Ask AT&T’.

“We created a private tenant for the OpenAI chat app and wrapped it around Ask AT&T, which basically created a secure area for us. We didn’t necessarily want to use the public domain, so that was the beginning of it,” Bijur said.

Another key area where AI is making an impact is software development. Bijur explained that AT&T has adopted GitHub Copilot, an AI-powered coding assistant that helps developers write code more efficiently, automate testing, and reduce defects. While industry reports suggest 30-40% efficiency gains from GitHub Copilot, AT&T’s real-world experience places this improvement at a more realistic 15-20%.

Beyond development, Bijur explained that AI plays a crucial role in fraud detection at AT&T. With the rise of online phone orders and returns, fraud risks have increased significantly.

To combat this, AT&T’s AI-powered fraud-detection system continuously monitors transactions, identifying and flagging suspicious activities in real time. Transactions that appear fraudulent are escalated for manual review.

AT&T is also transforming customer experience with AI-driven chatbots. Its NDVA chatbot, powered by generative AI, has transformed how customers interact with My AT&T app, enhancing both mobile and web-based services.

AT&T’s Balanced Growth Strategy Across India.

Unlike many GCCs that establish a single command centre, AT&T has adopted a balanced, multi-location strategy. “I wouldn’t necessarily say Hyderabad is the headquarters. It’s one of our larger locations, but Bengaluru and Hyderabad are fairly head-to-head in terms of the team size,” Bijur added.

Chennai plays a vital role in supporting AT&T’s India operations. This decentralised approach ensures that decision-making is distributed, allowing for greater agility and access to top-tier talent across cities.

Talent availability—not location—dictates AT&T’s expansion strategy.

“When a GCC is established, the focus is on volumes—how many employees we’re hiring, how fast is the expansion happening, etc. But now, we’re entering a new phase. It’s no longer just about the numbers; it’s about the value each employee brings to AT&T,” Bijur explained.

The company’s focus has shifted from simply building a workforce to deeply integrating employees into AT&T’s culture and global operations. Since AT&T’s core business—5G, fibre, and residential services—is US-centric, it is essential that India-based employees understand the challenges faced by American customers.

“For many employees, especially those coming from IT service providers, the mindset is often service-oriented,” Bijur explained, “But we want them to think like they’re part of AT&T—not just working for AT&T. That cultural shift takes time, but it’s crucial for long-term success.”.

In order to attain that, AT&T has implemented a multi-pronged approach that includes senior leaders frequently travelling between India and the US, fostering cross-border collaboration and alignment.

Furthermore, digital telemetry allows employees to use real-time analytics to track customer interactions, app usage, and web behaviour, enabling them to understand US customer experiences without being physically present.

AT&T also introduces employees to its ‘How We Connect’ framework, adapting it to the Indian work environment to create a sense of belonging and purpose.

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Cursor is the ‘Fastest Growing SaaS’ in History

When OpenAI released its frontier AI models, the industry discourse quickly shifted to AI ‘eating’ startups, particularly SaaS companies. Despite these concerns, one of the startups to have thrived in an AI-first landscape was Cursor.

, the AI-enabled coding platform reached $100 million in annual recurring revenue (ARR) within 21 months of its inception. It took Cursor only 12 months to reach this figure from $1 million ARR, making it the fastest-growing SaaS corporation of all time. The investigation added that Cursor reached these figures with roughly 360,000 individual developers who paid $20 – $40 monthly.

Anysphere, its parent firm, was founded in 2022 by MIT students and friends Michael Truell, Sualeg Asif, Arvid Lunnemark, and Aman Sanger. Their vision was to build an integrated development environment (IDE) that was “AI native”, and they launched Cursor in January 2023 on top of Microsoft’s Visual Studio Code.

Founders ‘Obsessed with the Problem of advanced AI Coding’.

Cursor began with the ambition to take over the competition. While Microsoft had launched a GitHub Copilot tool for AI-assisted coding in 2021, Cursor wanted to differentiate itself by integrating the latest available AI models, providing a superior user experience, and regularly implementing new functions and capabilities.

In September 2023, the corporation raised an initial $8 million in funding from OpenAI’s startup fund. In August 2024, Anysphere raised $60 million funding in Series A from Andreessen Horowitz (a16z), Thrive Capital, and other investors.

“Our belief is that Cursor, distinctly among AI coding tools, has simply gotten it right,” noted a16z in a blog post. “They [Cursor’s founders] are obsessed with the problem of superior AI coding, and are laser-focused on building a great developer experience,” the VC firm added.

The enterprise also in recent times raised $105 million in Series B funding led by Thrive Capital, a16z, and other existing investors.

A significant win for Anysphere was that its people turned into Cursor evangelists in no time. The product was predominantly aimed at individual developers, unlike traditional SaaS makers that prioritised enterprise sales. Cursor also offered a free tier to try out the platform, besides a $20/month Pro subscription and $40/month/user for Enterprise.

Besides individual individuals, AI experts, like former OpenAI researcher Andrej Karpathy, have been vocal about their love for Cursor.

Cursor was also clear on understanding all the problems with existing AI-enabled coding solutions, and the team, on multiple occasions, .

Initially, Cursor functioned as an AI-powered autocomplete tool. However, its capabilities quickly expanded to include more autonomous functions capable of handling complex coding problems with the launch of Composer, an AI agent mode. Besides, developers could chat with the code database, retrieve real-time information from the web, and use AI models to understand the code base.

Eventually, the platform got ahead of the competition.

Cursor also positions itself as an extension of the human engineer, but not to merely replace one. “Using a combination of AI and human ingenuity, they [the hybrid engineers] will out-smart and out-engineer the best pure-AI system,” the enterprise points to. This strategy resonated with people, who preferred Cursor’s workflow over Devin’s (an end-to-end autonomous software development tool).

Comparing it to Devin, Will Brown, an AI researcher at Morgan Stanley, mentioned on X, “I think I slightly prefer the ‘pair programming’ workflow of Cursor agent, which is way more hands-on. You’re reviewing the code in real-time, plus [you] can give suggestions more easily.”.

This isn’t to say Cursor is free from competition. Microsoft’s GitHub Copilot is estimated to earn more than $300 million in revenue annually. Sacra also noted that GitHub Copilot has an “enormous advantage”, thanks to its tight-knit integration in Microsoft’s ecosystem, as well as its existing enterprise relationships and security compliances.

Other tools like Vercel’s v0, [website], and Coedium’s Windsurf competed directly against Cursor. Carl Rannaberg, a software engineer, stated in his review that Cursor “remains the go-to tool for day-to-day coding tasks” thanks to its familiar code editor environment. On the other hand, v0 excels in rapid interface prototyping, and [website] “shines in full stack prototyping and quick project setups”.

However, Coedium’s Windsurf has emerged as the biggest threat to Cursor. in the recent past, several developers have been reportedly transitioning to Windsurf.

“Windsurf outperforms Cursor when working within an existing large-scale codebase. Cursor struggles to maintain context as projects grow,” noted Corey Sutton, an engineer in a blog post comparing both platforms. He also noted that Windsurf was improved at managing API modifications, while Cursor struggles to maintain consistency in TypeScript-heavy environments.

At the end of 2024, Sacra estimates Codeium to have earned $12 million in revenue.

Besides standalone products, Cursor also faces competition from frontier model makers. lately, Anthriopic released its coding agent, the Claude Code. A developer on Reddit compared the two, and expressed that the code quality of Claude Code “blows Cursor out of the water”.

As revealed by the founders in a podcast episode with Lex Fridman, Cursor faces significant challenges related to both infrastructure and model management. As usage grows, system components like caching and databases encounter unexpected issues.

Cursor processes code in the cloud, but it must also stay in sync with the local environment. “One of the technical challenges is always making sure that the local index, and the local code base state is the same as the state that is on the server,” noted Sualeh.

However, Cursor has grown exponentially over the past few months. The founders also noted that the ceiling is ‘incredibly’ high for innovation and that Cursor’s advantage comes not just from integrating newer models but also from the depth at which it’s integrated into the tool. “You don’t realise [how the AI models] are working for you in every facet of the product, as well as the really thoughtful UX with every single feature,” noted Sanger.

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Vibe Coding is Real

In recent weeks, the internet has been flooded with experiments from various people showcasing what is now being called ‘vibe coding’, a term coined by OpenAI co-founder Andrej Karpathy. In this, having an ‘idea’ is enough.

“There’s a new kind of coding I call ‘vibe coding’, where you fully give in to the vibes, embrace exponentials, and forget that the code even exists,” wrote Karpathy on X. “I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works.”.

While AI coding tools such as GitHub Copilot have been available for years assisting professionals by autocompleting code, newer tools like Cursor, Replit, Bolt, and Lovable are now making it easier for beginners to join this growing trend with more effective elements.

VC firm Andreessen Horowitz outlined some limitations for text-to-web app tools, despite their wide potential.

“They excel at simple builds. And if you can’t code otherwise, they can feel like magic. But there’s a limit to what they can reliably generate. Integrations are difficult, bugs persist, and code can get “too big” quickly,” noted Justine Moore, partner at a16z, on X.

Another user on X noted: “Vibe coding is all fun and games until you have to vibe debug.” One possible solution to this is prompting effectively.

On a larger level, how would the rise of ‘vibe coding’ impact the job of a junior or entry-level developer?

On NYT’s Hard Fork podcast, Anthropic CEO Dario Amodei spoke about the effect of AI on software development and coding. “I don’t think our hiring plans have changed yet, but I certainly could imagine over the next year or so that we might be able to do more with less [developers].”.

Anthropic in recent times released a new version of Claude, the [website] Sonnet, touted as the best coding model yet, with some calling it the best model to ‘vibe code’ with. AIM has covered in depth how to build apps easily using simple, yet effective prompts.

Vibe coding could prove to be one of the most consequential activities yet. In a lecture at UC Berkeley, Karpathy discussed the scalability of weekend projects to bigger companies.

For instance, the GPT series began as a Reddit chatbot project and evolved into GPT-4. GitHub Copilot started as an internal developer tool and became a global AI code completion platform, reshaping software development.

Likewise, Midjourney, initially a research project on AI image generation, is now a leading platform rivaling DALL-E. Hugging Face, once a chatbot app, is now a $2 billion hub for open-source AI models and datasets, widely used by AI researchers.

But what’s the secret to successful vibe coding? It all comes down to effective prompting. As AI models become more advanced, the ability to steer them correctly is turning into an essential skill.

in the recent past, OpenAI president Greg Brockman shared a guide on how to prompt effectively. “o1 is a different kind of model. Great performance requires using it in a new way relative to standard chat models,” he showcased. This was in the context of their o-series of models, which is different from the usual models, and requires different, contextual prompting.

“Think of prompting as the new user interface (UX) in the age of AI,” Unscript CEO Ritwika Chowdhury told AIM, emphasising that while just three years ago, one had to learn programming languages to instruct computers, today, prompting has become the essential skill for everyone to learn.

“AI models like GPT-4 or other large language models are trained on vast amounts of data but rely heavily on how they are prompted to produce meaningful, accurate, and contextually appropriate responses,” added Sudipta Biswas, co-founder at Floworks, part of Y Combinator’s Winter-2023 batch.

Prompt engineering is a real, growing profession. “Prompt engineering is a job today—that’s not something we could have predicted,” mentioned Thinking Machines Lab CEO Mira Murati in an interview.

Biswas added that in its early stages, prompt engineering was more of an experimental practice, with clients trying to figure out how to phrase their inputs to generate the most useful outputs. However, it has now matured into a profession owing to factors like complexity of AI models, industry demand, and optimisation for use cases.

“This reflects a broader trend where interdisciplinary skills, including those from the humanities, are increasingly valuable in the AI domain, highlighting the importance of understanding both technology and human communication,” concluded Chowdhury.

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