ForgeCode CEO Tushar Mathur stated AI has shifted the software development bottleneck from writing code to review and deployment. Individual engineer productivity gains from AI aren't translating into faster software delivery, creating a chasm in the SDLC. For engineering leaders, scaling delivery now means managing thousands of lines of AI-generated code, not just generating it.
How We Got Here
At TechSparks 2026, Mathur unveiled ForgeCode, pitching an AI-native software factory as the solution. This directly counters the traditional approach where more engineers and resources directly correlated to higher output.
The Numbers
- ForgeCode's platform deploys AI agents to manage the entire SDLC, from specifications through deployment.
- Human involvement focuses on oversight, directional decisions, and detailed feedback, moving away from manual task coordination.
- The system leverages continuous feedback loops from CXOs, product managers, and production monitoring, directly feeding into the dev backlog.
- AI agents operate 24/7, enabling feature development and bug identification even when human engineering teams are offline.
What Happens Next
🇮🇳 Why This Matters for India
For the thousands of engineering teams in Hyderabad and Pune scaling complex SaaS products, this promises a potential path to grow output without linear headcount additions.
The Take
Mathur is right: the bottleneck shifted. But ForgeCode's real challenge lies in getting senior engineers in Delhi and Mumbai to hand over critical review and deployment decisions to AI agents.
Source:
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