Carta CPO argues SaaS must add task-specific logic above MCP connections
Vrushali Paunikar, Carta’s chief product officer, warns that Model Context Protocol (MCP) alone won’t solve enterprise AI integration. MCP standardizes how AI models connect to software, but it doesn’t dictate how tasks should be executed—leaving users to manually refine prompts or risk errors in high-stakes workflows like finance.
Key points
- MCP standardizes AI-software connections but leaves task execution to models, risking errors in finance or audit-heavy workflows
- Google’s test showed task-specific instructions boosted accuracy to 96.3% while cutting token usage by 63%
- SaaS differentiation will shift from open MCP access to embedding deterministic logic or workflows
Paunikar highlights that probabilistic AI models excel at flexibility but fail in deterministic tasks where precision matters. She cites Google’s 96.3% success rate when combining MCP access with task-specific instructions—a 63% token savings over standard prompting. The next challenge for SaaS lies in building ‘plugins’ or ‘skills’ that embed workflows, calculations, or interfaces above MCP, shifting differentiation from connectivity to execution reliability.
The Next Battle in SaaS Starts Above MCP
Unite.AI · 27 October 2026
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This text was published by Unite.AI and written by Vrushali Paunikar, Chief Product Officer, Carta. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.
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