In our latest episode of What the Tech, we sat down with Anuj Rastogi, Managing Director at Backstretch, to discuss how AI is fundamentally reshaping product development, intellectual property creation, and staffing strategies across Canada's innovation ecosystem. 

After two decades in the digital agency world, Anuj made a complete pivot into talent acquisition and executive search. He's become a familiar face across Canada's startup community (attending 38 events in 2025 alone), giving him a front-row seat to how AI is changing everything about how companies build products, create defensible IP, and staff their R&D teams; insights that matter deeply to businesses maximizing access to government funding like SR&ED tax credits. 

The Perfect Storm for Innovation 

Anuj's decision to go from "barely attending events to hitting 38 last year" revealed an entire ecosystem of innovation he didn't know existed, from EV infrastructure software at Charge Lab to AI-driven drug discovery protocols to bridge-sized appliances growing 60 kilograms of produce monthly. 

But he emphasizes critical context: AI didn't emerge in a vacuum. ChatGPT launched in November 2022 during a post-pandemic moment when people were remote, searching for meaning, often having lost jobs. 

"In that silence, I think there was an entire generation of founders born. People who for the first time realized, 'I've had this idea for a long time. I think I wanna do this now.'" 

Tools like Figma had already made prototyping easier. Then gen AI coding solutions "closed the gap between ideas being in someone's mind and out in the world." 

AI's Impact: Lower Barriers, Higher Clarity Requirements 

Anuj's perspective on how AI changes product development is refreshingly grounded. 

What AI enables: "It's reduced the cost of building the first go at something. It's faster to prototype, faster to get something that feels real-ish." 

Out of 100 people with amazing ideas, maybe only 15 used to have means to code something real enough to show investors. "Now it might be 80 people who can get something closer to feeling real." 

The catch: "When it's really easy to prototype, you just go about doing it more—which is why clarity really comes in here." 

More prototypes mean more noise. But the discipline remains: Are you solving a real problem in the market for a customer? Is there identifiable pain they'll pay to resolve? How are competitors addressing it? 

"Start narrow with laser focus on solving one specific problem comprehensively. If that pain is true and real and persistent and you're solving it, you have a starting point for a defensible moat." 

Rethinking IP and Defensible Moats 

Anuj challenges traditional thinking about intellectual property. 

Old constructs: Patents, trademarks, proprietary technology 

New realities of defensible moats: Customer relationships, distribution channels, brand strength, operating processes, service blueprints—the organism as a whole. 

"If it's easier to build, it's more likely that 10 other people came up with the same idea. The moat is more than just a feature or patent. It's actually the organism as a whole of the business." 

That means technology + processes + customer relationships + operating model + distribution + people. AI makes features easier to replicate—holistic businesses are still hard to copy. 

The Human Side: Staffing for the AI Era 

This is where Anuj's insights become especially valuable for companies pursuing R&D tax credits; because successful innovation requires the right people making strategic decisions. 

Skills that matter more than ever: 

  • Human judgment and discernment 
  • Critical thinking 
  • The ability to ask "why" 

"You can spin up a new app just by prompting Claude or some other tool. You get the idea out there—but you have to stop and ask yourself the why. So far, there is no other system out there other than human judgment that's gonna say the why and whether this is really valuable." 

The shift from specialists to generalists: 

Instead of 100 deep specialists, startups might have 10-20 generalists with a few specialists mixed in. One person might be "partly a CFO, partly a product manager, partly a solutions architect" in a single day. 

"As a species, we're multivariate and multidisciplinary. It gives people who have different aptitudes a new opportunity." 

The "Founding BDR" Example 

Anuj shared a powerful example tying directly to R&D tax credit strategy: the concept of a "founding BDR" (business development representative). 

Traditional BDR: Hit phones, send emails, generate leads. 

Founding BDR in 2026: Listens deeply to customers, drafts messaging, runs experiments, writes code, and—critically—brings market intelligence back to the product team. 

"Maybe they had 10 calls and on four of them, customers said 'My actual problem is blah blah blah.' That's useful intel that directly influences the product roadmap and what you choose to develop." 

The R&D connection: "Now we're building something that customers told us there is no other solution for. That meets the eligibility criteria of SR&ED, for example." 

It's not just a once-a-year filing—government tax credits become part of your capital strategy and infuse into how you operate as a business. 

Listening vs. Hearing: The Critical Difference 

One of Anuj's most powerful points: Listening is very different than note-taking. 

"So many of us use AI note takers that transcribe audio. That text is not listening. Listening is being in the moment with another human being, understanding the thing in between the lines that's unsaid. You could read the transcript and completely miss the insight. AI isn't listening as much as it's hearing. Only people can listen." 

This distinction matters for R&D teams, customer discovery, and product development; that is, everything that drives genuine innovation. 

Capital Strategy: Changed Unit Economics 

The funding landscape has fundamentally shifted because of AI's impact on unit economics. 

The old model: Maybe you needed 17 people to run an operation generating $17M in revenue. 

The 2026 model: You might do the same with 5 people; different tooling, different GTM stacks, different channels. 

What this means for founders: 

  • Longer runway with lower dilution 
  • More time to prove product-market fit 
  • More leverage in investment conversations 

Anuj sees more founders delaying VC rounds. "If before they needed $10 million, they might get by on $2.5 million now. That gives runway to build customer base and create more leverage—making Series A less dilutive." 

From investor perspective: If companies need half the capital, investors can make twice as many bets. "Instead of placing five bets, now I can place 10." 

The talent de-risking opportunity: If significant investment goes to hiring but the company treats hiring as a "side activity," you've de-risked capital through due diligence but introduced risk through talent acquisition. 

"Making sure hiring excellence is in play—that founders have the right tools and partners to hire effectively—is actually a risk mitigation tool for the investment." 

Why R&D Tax Credits Matter More Than Ever 

Throughout our conversation, Anuj emphasized how government funding programs like SR&ED intersect with innovation strategy. 

It's not just about non-dilutive capital; it's about: 

  • Validation that your work meets genuine technological advancement thresholds 
  • Proof to investors you're tackling real technological uncertainty 
  • Strategic integration into how you operate and make product decisions 
  • De-risking talent investments by reinvesting credits into the right people 

Companies succeeding in 2026 aren't treating R&D tax credits as afterthoughts. They're building them into capital strategy, talent strategy, and product roadmap decisions from day one. 

Key Takeaways

Think bigger about roles – A BDR isn't just sales—they're market research, product feedback, and R&D validation. Build that thinking into every role. 

Listening beats hearing – AI transcribes. Only humans listen for what's unsaid and understand patterns that drive innovation. 

Moats are organisms, not features – Defensible IP is technology + processes + relationships + operating model + people. AI makes features easy to replicate; holistic businesses are still hard. 

Unit economics changed everything – Smaller teams do more with AI tools. This changes capital strategy, hiring strategy, dilution, and runway. 

Generalists create outsized value – In lean startups, people who think across CFO + product + tech domains matter most. Hire for breadth and curiosity. 

Government funding is strategic – R&D tax credits should infuse into operations, not just be year-end filings. They validate innovation and de-risk talent investments. 

Clarity matters when barriers are lower – AI makes building easier, creating more noise. Discipline to focus on real customer pain separates signal from noise.