When AI Meets Code: A Candid Dialogue in Bengaluru
On January 22, 2026, Madhusudhan Rao, the Chief Technology Officer (CTO) of Swiggy, will convene with a cadre of esteemed engineering and technology leaders in Bengaluru.
This assembly will not merely represent India’s most audacious tech teams, but rather, it will herald a gathering of those pivotal in transforming Bengaluru into a formidable hub for the adoption of artificial intelligence (AI) within software engineering.
In these hallowed teams, AI code assistants diligently reside within editors, sprint plans accelerate precipitously, and the exhortation to “ship it” has become an instinctive reaction.
Rao’s initial inquiry may appear unassuming: If AI has revolutionized your teams’ coding and deployment methodologies, has your code review process truly evolved in tandem?
Set against a backdrop where Bengaluru now disseminates software globally, decision-makers from some of India’s premier tech organizations will convene for a concentrated Engineering Leadership Forum. This exclusive assembly is hosted by The Economic Times and CodeRabbit at the Conrad Bengaluru’s Junior Ballroom.
Disparity Between AI-Driven Agility and Human Review Capacity
Over a remarkably brief period, artificial intelligence has redefined what constitutes “normal” within the software delivery pipeline. AI coding tools have transitioned from nascent experimentation to an established norm among teams.
An initiative that began with a handful of developers exploring GitHub Copilot and Cursor for side projects has now permeated the fabric of entire engineering organizations.
Developers report a capacity to ship code two or three times more frequently than previously achieved; features traverse the backlog with unprecedented speed, while product roadmaps are condensed into timelines that would have seemed daunting just a few years prior.
What was once viewed as a distant goal has, for many organizations, morphed into standard operating procedure.
Nevertheless, beneath this veneer of success lies a troubling asymmetry. Human reviewers are now confronted with significantly larger and more intricate pull requests, often brimming with AI-generated code that appears sound upon initial inspection but may conceal obscure failures regarding edge cases, security vulnerabilities, performance issues, and integration challenges.
The stark reality is that while the velocity of shipping has surged, the efficacy of most teams’ code review processes has not kept pace. The true bottleneck has never resided in how swiftly developers can type; rather, it pertains to the meticulousness with which alterations can be scrutinized.
Conventional practices—ranging from manual reviews to rudimentary linters and scattered comments across extensive PR threads—were never engineered to accommodate this unprecedented volume or the novel coding paradigm, and the deficiencies are becoming increasingly apparent.
This conundrum encapsulates the purpose of CodeRabbit: to provide AI-enhanced code reviews that empower teams to navigate swiftly while preserving their crucial guardrails.
Rather than primarily viewing AI as a means to amplify code production, CodeRabbit integrates AI into the review workflow.
This integration allows for contextual understanding across repositories, adeptly identifying issues often overlooked by human reviewers and presenting only high-value insights. This ambition starkly contrasts with traditional methodologies: it seeks to expedite release cycles while simultaneously fortifying code quality.
Anticipated Agenda for the Engineering Leadership Forum
The morning event will commence with registrations and refreshments from 9:30 AM to 10:30 AM, offering participants an opportunity to reconnect with peers from other high-velocity engineering organizations and set an engaging tone for a collaborative format.
At 10:30 AM, an anchor from The Economic Times will inaugurate the proceedings, contextualizing how AI has propelled software delivery and elucidating why code review has emerged as both a leverage and a vulnerability for engineering leaders.
From 10:45 AM to 11:15 AM, Swiggy’s CTO, Madhusudhan Rao, will present the keynote, titled “How Swiggy Uses AI to Generate and Validate Code.”
He will delineate the integration of AI within Swiggy’s engineering workflows: how developers collaborate with AI tools, how their perceptions of code quality have evolved, and what safeguards have been implemented to ensure that speed does not compromise robustness.
Following this, between 11:15 AM and 11:45 AM, CodeRabbit will offer an overview and live demonstration entitled “Shipping Code with Guardrails in the AI Era.”
Featuring Michael Fox, VP – GTM, and Nithin Kunimmal, Country Manager – India & APJ, this segment will transition from theoretical discussions to practical applications, illustrating how AI-driven code review operates in real-world contexts: how systems can traverse repositories, uncover issues that evade human scrutiny, and provide succinct, impactful feedback that aligns seamlessly with existing workflows.
The morning will then transition into a multifaceted discourse. From 11:45 AM to 12:25 PM, a panel discussion on “AI-Driven Engineering: How India’s Top Tech Teams Are Rewriting Their Operating Models” will feature Sreedhar Gade, VP of Engineering at Freshworks, along with senior engineering leaders.
They will examine how AI is reshaping organizational structure, role definitions, ownership delineations, and the metrics being utilized. Attendees can expect discussions on determining what to automate, what should remain in human hands, and navigating the cultural shift from traditional pipelines to AI-accelerated models.
From 12:25 PM to 12:45 PM, a fireside chat titled “Systems That Think: The Future of Scalable, Self-Learning Platforms” will delve into what lies on the horizon.
Speakers will explore the implications of platforms capable of learning and adapting, as well as their participation in decision-making across the Software Development Life Cycle (SDLC).
This evolution will fundamentally redefine reliability, observability, and the very essence of “engineering excellence” as systems, rather than merely teams, engage in cognitive processes.
The formal agenda will conclude between 12:45 PM and 1:00 PM with a succinct address from the CodeRabbit leadership team, summarizing the key themes of the morning and outlining actionable next steps for organizations aspiring to modernize their review workflows without dismantling existing strengths.
From 1:00 PM onwards, discussions will continue over a networking lunch, providing attendees with a platform for exchanging insights, experimenting with ideas, and engaging in one-on-one dialogues with the teams from Swiggy and CodeRabbit.
Attendance is strictly by invitation, with limited spots available for senior engineering leaders who are either presently experimenting with AI in their systems or are on the cusp of doing so.
If your development efforts are firmly entrenched in the AI epoch but your review process remains analog, this is the forum where that disparity will be candidly addressed.
Source link: M.economictimes.com.
