Trust, not tech, as dev tool edge—Responsive exec

Kunal Shrestha, VP of Product at Responsive, told developers at DevSparks Chennai 2026 that trust—not technical specs—will be the deciding factor in AI-era tool adoption. The comment lands as enterprise AI deployments grow more complex, with rogue agents and governance failures making headlines. Shrestha’s argument isn’t new, but it’s increasingly urgent: when every vendor can replicate features, the ability to guarantee safety, transparency, and alignment with human workflows becomes the real competitive moat.

This isn’t just founder rhetoric. When we covered AI adoption in small businesses on 1 September, the story was the same—success hinged less on what the tech could do and more on whether employees trusted it to stay within clear boundaries. That tension has only sharpened as AI moves from pilot projects to mission-critical systems. Some companies are now emphasizing governance as a key part of their offerings, suggesting that how AI tools are managed may become just as important as what they can do. For example, a UK startup recently raised funding to expand its enterprise AI governance tools, indicating growing interest in this area.

The timing of Shrestha’s remarks matters. DevSparks Chennai isn’t a marquee event like TC Disrupt, where Waabi and Shield AI executives will discuss high-stakes AI development later this month. But Chennai’s audience—mid-market developers and product leaders—is precisely the group feeling the squeeze between flashy AI demos and the mundane reality of integrating them into existing stacks. For these operators, trust isn’t abstract. It’s about avoiding the kind of reputational damage that comes from a misaligned agent or a hallucination that slips into production. It’s about knowing that when something goes wrong—and it will—the vendor will have a process, not just a press release.

Responsive hasn’t been in the headlines recently for major funding or product launches, which makes Shrestha’s comments stand out. They’re not tied to a funding announcement or a pivot; they’re a strategic read on where the market is headed. That suggests the company may be betting its roadmap on governance, reliability, and developer confidence as core differentiators. It’s a gamble, but one that aligns with where enterprise buyers might be looking next. Visko’s Orbis model, which we covered earlier this month, competes on real-time AI world generation—a technical feat. Responsive, by contrast, appears to be staking its claim on something less flashy but potentially stickier: being the vendor developers don’t regret choosing when the AI hype cycle turns.

The open question is whether trust scales as a business model. Features can be benchmarked, priced, and sold. Trust is harder to quantify, harder to monetize, and harder to maintain at scale. It’s also the one thing that can’t be copied by a well-funded competitor with a faster model or a slicker UI. If Shrestha is right, the next wave of AI tooling won’t be won by the companies with the most impressive demos, but by the ones that can prove—consistently—that their systems won’t betray their users. That’s a high bar, and one that will force vendors to think beyond product specs and into the messy, human realities of enterprise adoption.

For founders and investors, the takeaway is clear: the AI gold rush is over. The next phase may belong to the companies that can turn trust into a competitive advantage. Watch for Responsive’s next moves—not just what they build, but how they talk about it. If they double down on governance and reliability, it could signal a broader shift in how the industry sells AI tools. If they don’t, they’ll be just another vendor chasing the same features as everyone else.

Sources: yourstory.com