Education & Training

Teen Who Questioned CBSE Tender Now Opens 1.66 Crore Government Contracts to Public

Published

5 days ago

June 24, 2026

Jon Tru

A Class 12 student who recently gained attention for analysing the Central Board of Secondary Education (CBSE) digital evaluation tender has launched a large-scale public data portal featuring approximately 1.66 crore government procurement records sourced from India’s Central Public Procurement (CPP) system.

The initiative is designed to make government contract data more accessible, enabling citizens, journalists, researchers, and policy analysts to independently examine public spending and procurement patterns.

From Exam Paper Analysis to National Procurement Data Project

The student, Sarthak Sidhant, first came into public attention after reviewing publicly available CBSE documents related to the On-Screen Marking (OSM) system used in digital evaluation of answer sheets.

His analysis of tender documents reportedly highlighted changes in eligibility criteria and evaluation conditions across different versions of procurement notices, prompting wider discussion on transparency in education-related contracting.

Following that work, he has now expanded his focus beyond the education sector by building a searchable database that aggregates government procurement records from multiple departments.

1.66 Crore Records Made Searchable for Public Use

According to the developer, the newly launched platform compiles and structures millions of procurement entries available on the government’s Central Public Procurement Portal.

The system is designed to allow users to search, filter, and analyse contracts issued by various government bodies, potentially making it easier to track expenditure trends and vendor participation.

The initiative aims to simplify access to complex datasets that are otherwise difficult for the public to navigate in their raw form.

Push for Greater Transparency in Public Spending

Sidhant said the goal of the project is to encourage independent scrutiny of government procurement and promote data-driven discussions on public accountability.

He has encouraged users to explore the dataset, conduct their own analysis, and identify patterns in procurement decisions across sectors.

Supporters of such initiatives argue that improved access to structured government data can strengthen transparency and civic oversight, especially in large-scale public procurement systems.

Growing Role of Citizen Data Analysis

The project has sparked wider discussion about the increasing involvement of young researchers and independent developers in analysing publicly available government information.

Observers say such efforts reflect a broader shift toward open-data-driven governance, where citizens play a more active role in examining public systems and expenditure.

The portal currently focuses on procurement data from the CPP system, and further expansions may be developed as part of ongoing transparency-focused work.

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AI & Technology

As AI Coding Tools Spread, GitHub Copilot And LLMs Begin Shift In Software Engineering

Published

4 months ago

March 10, 2026

Jon Tru

Artificial intelligence is rapidly reshaping software development, with AI-powered tools like GitHub Copilot and advanced large language models (LLMs) increasingly automating routine coding tasks. Industry experts say this shift is transforming the role of software engineers, moving their focus from writing code to designing and reasoning about complex systems.

AI Streamlines Routine Programming

Large language models, integrated into modern developer tools, can now write functions, suggest code improvements, and assist with tasks that traditionally required manual effort. Studies show these tools significantly accelerate the coding process.

A 2023 Microsoft experiment revealed that programmers using GitHub Copilot completed tasks approximately 55.8% faster than those coding without AI assistance. Similarly, Anthropic’s “AI Exposure Index” suggests that LLMs could handle roughly 75% of standard programming tasks—higher than any other profession tracked—underscoring AI’s potential to reshape the software industry.

Dario Amodei, CEO of Anthropic, noted that some engineers already spend minimal time coding directly, relying on AI outputs. Executives at platforms like Replit predict that the traditional definition of a software engineer may gradually evolve as AI tools take on more of the coding workload.

From Syntax to System Thinking

While AI automates much of the mechanical coding work, engineers emphasize that the profession is not disappearing—it is evolving. Developers increasingly act as reviewers, testers, and system designers, focusing on scalability, reliability, and architectural trade-offs rather than individual lines of code.

This shift means the skill set for software engineering is becoming more analytical. Understanding system behavior, identifying failure points, and optimizing performance require reasoning similar to mathematics or physics rather than repetitive coding.

The Debate on Automation Limits

Despite the rapid adoption of AI, many experts caution against overestimating automation’s capabilities. LLMs can struggle with highly complex or novel programming challenges and may introduce errors that require careful human review. Experienced engineers remain critical for maintaining system reliability and making strategic decisions about architecture and design.

Some analysts also note that AI’s rapid takeover mainly applies to routine coding tasks, while groundbreaking software innovation will still rely heavily on human creativity and expertise.

Reimagining Programming Education

The rise of AI in software development is prompting educators to reconsider the future of programming training. Experts suggest that computer science education may need to emphasize problem-solving, system design, and computational reasoning rather than rote mastery of syntax.

Hadi Partovi, founder of Code.org, stated, “Coding is dead… long live coding,” reflecting the sentiment that while AI may handle much of the coding mechanics, understanding and building complex software systems remains central to the profession.

As AI tools like GitHub Copilot become ubiquitous, the software engineering landscape is evolving toward a hybrid model: machines handle repetitive tasks, while human engineers focus on critical thinking, system design, and oversight.