Building What Matters: Sushant & Soneshwar on Solving Real Problems with AI and Blockchain

Two school friends with a shared dream, Sushant and Soneshwar set out to “build something big” long before they knew what that something would be. In this conversation, they trace the road from tinkering teenagers to co-founders of The Wasserstoff, a tech company that incubates founders by shipping high-quality software at breakneck speed—and only when it solves a real problem.

From classmates to co-founders

The pair’s entrepreneurial spark lit up in grade nine. A formative computer science teacher nudged them toward code, and they never really looked back. There were early stumbles—custom gaming rigs, hyperlocal commerce experiments—followed by a stint in operations for a fast-growing hospitality startup that taught them how to scale systems in the real world.

Those detours crystallized a core belief: ideas deserve a shot at the market. If the bottleneck is execution, remove it. If the founder brings deep domain insight but not an engineering team, provide it.

What The Wasserstoff actually does

Think of The Wasserstoff as a tech-first incubator for “vertically deep” founders—operators who understand a specific industry cold but need a product team that can move from concept to live MVP in weeks, not quarters.

• Model: selective incubation, building end-to-end MVPs and first versions at speed; sometimes for equity, sometimes with a light one-time fee to keep everyone invested.

• Edge: ruthless focus on cycle time. Ship quickly, learn quickly, improve quickly.

• Goal: remove the tech burden so founders can focus on distribution, customer discovery, and traction.

“Build tech faster so you can try faster and fail faster,” they put it simply.

Beyond the buzzwords: value over hype

Both founders are clear-eyed about AI and blockchain: the tools are powerful, but business fundamentals don’t change.

• AI, used right, kills drudgery. They’re building assistants that automate research, sourcing, screening, and other repetitive workflows so humans can spend time on creativity and judgment. Their north star: a 10–100x convenience delta for the end user.

• Blockchain, used quietly, builds trust. Rather than leading with jargon, they embed decentralized rails where transparency, security, and finality matter—think anti-scalping ticketing, verifiable community engagement, and tamper-evident records. It’s infrastructure, not a headline.

In short, they ship utility, not hype. If a feature doesn’t make a daily task meaningfully easier, it doesn’t make the cut.

How they choose what to build

A simple rubric guides the roadmap:

1. Is there a real, persistent problem? Preferably one they or their portfolio teams feel viscerally (e.g., hiring ops, legal research, market monitoring).

2. Can technology create a step-change in ease, speed, or accuracy? If yes, prototype now.

3. Will people use it weekly—or better, daily? The closer to “everyday habit,” the better.

That’s why you’ll see tools that:

• streamline legal and compliance workflows by surfacing authoritative sources in context;

• automate first-pass recruitment (discover, screen, and shortlist);

• deliver targeted, auto-compiled industry updates to your messaging apps;

• enable transparent, tamper-evident participation for events and communities—without forcing users to learn crypto.

Tech trends they’re betting on

• Agentic AI: Not just chat, but autonomous, tool-using agents that carry out multi-step tasks and hand back results. Long term, they imagine “universal basic compute”—small, on-device models assisting every role in a company, from HR to ops to engineering.

• Augmented reality (AR): Especially transparent, lightweight displays that bring instructions, training, and safety guidance into the flow of real-world work—think first-aid prompts at home, skill training on factory floors, or turn-by-turn clarity where maps fall short.

• Robotics (longer horizon): As models get better and hardware cheaper, expect useful, domain-specific robots to enter daily life.

The common thread: human-in-the-loop systems where AI handles the tedious and humans make the calls.

Why India—and what’s changing

The Wasserstoff is unapologetically bullish on India:

• Scale + diversity: Enormous market, with micro-cultures even across neighborhoods. Products must localize deeply—and those who do can build very large businesses.

• Talent flywheel: Self-taught developers, student founders, and increasingly tech-savvy investors are accelerating the ecosystem. The team cites a 22-year-old CTO as one example of the new pipeline.

• Access unlocks: Ubiquitous internet lowered the barrier to learn, ship, and sell. The next unlock? Affordable, high-quality education in local languages, delivered digitally—and they want to help build it.

They’re also experimenting with rural talent initiatives: training and employing people where they live to widen opportunity and reduce costs for early teams.

What’s next

Expect a steady cadence of pragmatic tools rather than splashy moonshots. On deck:

• AI assistants that take on research, recruiting, and content monitoring for teams that need leverage, not headcount.

• Infrastructure kits that let developers plug transparency and verifiability into their own products—without exposing end users to technical complexity.

• A passion project for social good: a gamified, digitally verifiable way to support street-animal care via trusted shelters and vets, complete with updates and shared responsibility among families and communities.

And yes, there are partnerships brewing with major institutions to take some of these ideas to scale.

The takeaway

Sushant and Soneshwar aren’t chasing trends; they’re compounding craft. Their philosophy is disarmingly simple:

• Ship fast.

• Solve real problems.

• Hide the complexity.

• Make everyday life meaningfully easier.

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In an era of loud buzzwords, The Wasserstoff’s quiet insistence on usefulness feels like exactly the kind of signal founders—and users—need.