Gadi Shamia

Most contact center AI projects never leave pilot. Here's why. Companies aren't struggling to build one bot. They're struggling to operationalize AI across 150+ intents, policies, and edge cases — without creating another silo. After automating 1B+ minutes on the phone, we built something different: AI that builds itself from your best agents' calls. AAA went from 23% → 75% automation success with @Replicant_AI. Watch how we do it 👇 [video] 📢

Someone asked me today if UX is important in the era of LLMs. It is. A conversation is an interface, and how you run it matters. This is something @AnthropicAI is usually better at than @OpenAI. As another example, it took ChatGPT about a year to catch up with this feature, which makes editing a prompt possible again.

Sometimes a product earns your loyalty all over again. My @googlenest alerted me that my AC had failed — hours before I would have noticed on my own. By the time I would have walked into a hot house, the tech was already done fixing it. I liked Nest before; now I love it (It was the capacitor, if anyone's curious.)

Welcome back to "What's wrong with your customer service?" — Episode: @EufyOfficial Someone waiting at my door. I'm miles away. No remote access to my smart lock. Eufy support? Email only. Marked URGENT. In the next day, 1,258 words of copy-paste troubleshooting that ignored everything I said. 🔑 "I'm out of the house" — said twice. Ignored. 🔑 "Both locks affected" — said three times. Kept asking "which one?" 🔑 "Not an internet issue" — said clearly. Still got router/WiFi reset suggestions. This wasn't AI. Humans on templates... somehow worse than a 2020 chatbot. It resolved itself after 24 hours, exactly the system outage I flagged in my FIRST email. In 2026, companies still skipping proper AI front-ends + empowered humans? It's a solved problem. Fix it. 20+ smart lock brands exist. Why choose the one that leaves guests (or family) stranded outside? Share your stories — let's learn the patterns.

My father's people philosophy at work: ↑ Kick upward → Respect your peers ↓ Be kind to everyone below you I've turned this into my favorite reference check question for executive candidates: "In one sentence, describe how [candidate] treats their peers, their reports, and their leaders." I learn more from this question than almost any other.

@Eric_M_Stevens Exactly. Same problem lazy product managers create :)

@gadishamia 100%. the spec problem is the same one creative agencies have dealt with forever. a bad brief produces bad work no matter how talented the team is. AI just makes that feedback loop faster and more expensive

The real problem with AI “vibe coding” isn’t the coding. It’s the spec. In customer service, we see agents built from outdated knowledge bases, partial system data, and agent interviews. That’s a bad spec. Garbage in, garbage out. The real spec already exists: millions of successful agent calls. 📽️ how @Replicant_AI does it vimeo.com/1172267291

@gadishamia 90% of contact center AI pilots never reach production. Not due to bad tech — but because scaling is tough. @Replicant_AI is fixing that. 🚀

@harshitagu72595 @Replicant_AI This is a correct stat :)

Most contact center AI projects never leave pilot. Here's why. Companies aren't struggling to build one bot. They're struggling to operationalize AI across 150+ intents, policies, and edge cases — without creating another silo. After automating 1B+ minutes on the phone, we built something different: AI that builds itself from your best agents' calls. AAA went from 23% → 75% automation success with @Replicant_AI. Watch how we do it 👇 [video] 📢

@Betsythomass This will be the way everyone will build AI soon

@gadishamia That’s a powerful shift—learning directly from top agent calls makes AI far more practical. Scaling intelligence, not just bots, is where the real value lies.

@FlokiBull_ what do you have in mind?

@gadishamia @gadishamia shall we collab?

@Tech_Xelina yes!

@gadishamia Operational AI > experimental AI.

@Hey_elizaera this is how they will

@gadishamia This is how contact center AI should scale.💡

@filodyprincess 100%. It will be the standard in a year

@gadishamia Turning real agent calls into self-improving AI is a game changer for contact centers. Huge step toward scalable automation.

@Sumit_AI_Tech Thanks

@gadishamia This approach makes a lot of sense.

@pushkersoni72 100%

@gadishamia Impressive turnaround! Real-world results matter.

@elora_khatun Solves the garbage in/garbage out

@gadishamia Fascinating workflow — combining real agent expertise with AI to hit 75% automation is impressive.

🔒 While SOC 2 remains a foundational security standard, its static, point-in-time nature is often ill-equipped to address the non-deterministic risks inherent to LLMs. Moving beyond traditional compliance requires a multi-pronged approach—integrating frameworks that secure non-deterministic AI in the enterprise: replicant.com/blog/iso-42001…

@aibytekat We usually start with fewer, but it is possible

@gadishamia 50 agents in two weeks is crazy fast