AI agents become the universal brand front-end replacing apps/websites
Conversational agents will unify sales, support, and commerce into a single persistent interface with full user context, becoming the primary brand touchpoint.
Customer service is the killer enterprise AI use case today
Customer service offers quantifiable ROI (deflection rates), natural escalation paths for risk mitigation, and existing infrastructure — making it the fastest enterprise adoption vector.
AI agents will eat human labor spectrum from both ends
Agents will simultaneously augment highest-paid knowledge workers (coding) and replace lowest-cost repetitive labor (customer service), driven by ROI clarity at both extremes.
Voice-to-voice is the next frontier but hallucination rates 8x higher
Voice is the natural human UI, but voice-to-voice models currently suffer ~8x higher hallucination rates than text, requiring hybrid architectures for enterprise deployment.
Conversation data flywheels create compounding moats for agent companies
LLMs can ingest 100% of customer interactions to auto-generate evals, detect gaps, and improve agents continuously — creating a data advantage that compounds with tenure.
Fine-tuning small open models for specific tasks beats monolithic large models
Mature applications can decompose agent workflows and fine-tune smaller models for routing, classification, and guardrails — improving latency, cost, and reliability.
Application layer captures most value; model APIs face commoditization
Solving the end-user business problem allows application companies to command pricing power, while model providers face low switching costs and intense competition.