Richard Schut on testing AI tools beyond the sales pitch
Smartrepl is an independent research and review platform that evaluates AI tools, workflow automation and software infrastructure for business teams. Richard Schut explains how hands-on testing informs the platform’s reviews, where AI helps with lead intake, and why its core analysis remains human-led.
Start with one or two important workflows and make sure the AI tools connect reliably to systems such as a CRM and calendar. Use AI where it handles routine work well, but keep human researchers responsible for nuanced analysis and editorial judgment.
What’s the quick origin story of your business, and what makes what you do genuinely different from the other options your customers are looking at?
SmartRepl was born out of sheer frustration with overhyped software marketing. Every week, a new ‘revolutionary’ AI tool launches promising to automate sales or customer service completely, but when business operators actually buy them, half the features fail or require weeks of custom dev work.
What makes us fundamentally different is our hands-on, operator-first approach. We don’t just summarize landing pages or write generic feature lists; we actually stress-test platforms in real-world scenarios—evaluating latency, CRM sync reliability, calendar booking logic, and true operational ROI. We cut through the fluff so business leaders can build a stack that actually works on Day 1.
Where does most of your new business come from today, and where do you wish it came from?
Today, the majority of our audience and site traffic comes from organic search and direct referrals—founders, agencies, and operations managers specifically looking for honest tool comparisons, reviews, and setup guides before making a purchase.
If I could shift it slightly, I’d love to see even more direct engagement from B2B software decision-makers bringing us into their architecture planning phase early on. Too often, teams spend months forcing a tool to work before discovering a much better-suited platform already existed.
What’s one thing you’ve actually handed over to AI in the last year, and one thing you tried it on and went back to doing the human way?
The biggest win we’ve handed over to AI is first-line lead qualification and call answering via AI receptionists and smart voice agents. Letting an AI handle initial intake, answer routine operational FAQs, and book meetings directly into live calendars has saved hundreds of hours.
On the flip side, we tried using AI for end-to-end long-form analysis and technical opinion pieces—and quickly abandoned it. AI can aggregate facts, but it lacks genuine nuance, industry context, and critical edge. Readers instantly spot ‘templated AI content.’ We went right back to human-driven research and hands-on testing for all our core editorial insights.
Have you noticed a change in how customers find you or what they already know before they reach out? Is anyone arriving through AI assistants like ChatGPT yet?
Absolutely. The buyer’s journey has evolved dramatically. Prospective clients and readers arrive much higher up the knowledge curve than they did two years ago—they already know the technical jargon and have tried a few basic prompt tools.
We are definitely seeing an influx of traffic originating from AI assistants like ChatGPT, Perplexity, and Claude. People now ask LLMs, ‘What are the best AI receptionist tools with Calendly integration in 2026?’—and when AI engines summarize our comparative research, users click through to read our deep-dive audits.
If you were advising someone in your industry on all of this for the next 12 months, what would you tell them to actually do, and what would you tell them to ignore?
What to do: Focus obsessively on operational execution and dynamic data sync. Pick 1 or 2 high-impact workflows—like inbound call answering or post-sale follow-ups—and make sure your AI tools talk natively to your CRM and calendar. Speed-to-lead and automated execution win every single time.
What to ignore: Ignore the shiny-object syndrome and ‘all-in-one AI’ platforms claiming to replace your entire team overnight. Most monolithic ‘do-everything’ AI tools do five things poorly instead of one thing exceptionally well. Build a modular stack with best-in-class, specialized tools instead.
Thank you to Richard Schut and the team at Smartrepl for sharing what actually worked with Leaders Perception readers.
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