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What happens when AI writes code faster than your team can review it? Prashanth shares why Innostax deliberately limited how much code AI could produce at once, then shifted attention to the tools, context and checks around it. He explains what that means for team design: more emphasis on judgment, evaluation and accountability, rather than simply expecting fewer engineers to do the same work.

Knowing how to build an AI demo isn't the same as keeping a system reliable in production. Innostax founder and CEO Prashanth Tondapu explains why more hiring and training won't close that gap on their own. Engineers need to make architecture and product decisions, then see how those choices play out in production, rather than only follow someone else's specifications.

Why would AI companies call for a slowdown but keep racing ahead? Prashanth sees an arms-race problem: companies can recognise the danger and still fear being the first to slow down. He argues that regulation needs to address that risk without shutting out smaller competitors, so safety rules don't end up protecting the companies already in the lead.

If leading US AI labs slow down, Prashanth sees an opportunity for Indian engineers and startups to narrow the capability gap. He argues that India shouldn't automatically follow their pace: catching up calls for a different response from pushing the limits of the most advanced models. That means continuing to build India's AI capability responsibly, rather than treating safety as a reason to stop catching up.

Max Maxfield speaks with Innostax founder Prashanth Tondapu about why the engineering around an AI model, the agent harness, matters as much as the model. The feature also covers Innostax's Managed GCC model for building dedicated engineering teams in India for US companies.

Innostax founder and CEO Prashanth Tondapu writes in Industrial Economist about the widening gap between AI capability and the controls meant to govern it. He argues that enterprises deploying autonomous agents need scoped permissions, constrained execution environments, auditability and named human ownership, because an agent's ability to act should never automatically become permission to act.