June 19, 2025
Artificial Intelligence, Phase 2 Labs, UI/UX

[vc_row full_screen_section_height="no"][vc_column offset="vc_hidden-sm vc_hidden-xs"][vc_column_text css=""] AI introduces new interaction patterns—and with them, new uncertainties. These systems are non-deterministic. That means even when a user asks the same question twice, the answers might not match. So what does it look like to design for that kind of unpredictability?   How do we help users spot AI mistakes—without tanking their trust? One of the biggest UX challenges right now is figuring out how to acknowledge that AI gets things wrong—sometimes confidently wrong—without undermining the entire experience. Some...

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June 17, 2025
Enterprise AI, Phase 2 Labs

Parsing, Matching, and Acting with Context: A Foundation for the Future of AI Labor Unlocking New Possibilities with Multi-Modal AI The Resume Sizzler, developed by P2 Labs, is more than a resume builder—it's a glimpse into the future of applied intelligence. A few years ago, extracting meaningful insights from unstructured data at scale was nearly impossible. Built on advanced multi-modal AI, this system transforms unstructured data into actionable insights, enabling businesses to automate complex workflows, extract meaning from documents, and make smarter...

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May 23, 2025
Engineering, Phase 2 Labs

What is the Sequential Thinking MCP Server from Anthropic? The Sequential Thinking MCP Server is one of many Reference MCP Servers released by Anthropic to demonstrate the capabilities of their MCP protocol. This server in particular serves the purpose of providing structure to help augment a given AI’s thinking process. The Sequential Thinking server does not do any of it’s own “thinking” or decomposing of a problem. Instead it deterministically receives structured input from an AI, validates the data in the...

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May 22, 2025
Artificial Intelligence, Phase 2 Labs

Office Manager Magic, Powered by Multi-Modal AI Introduction AI isn’t a futuristic concept, it’s practical labor, available today. Not just for call centers or simple tasks, but for real, dynamic work that used to require a person. This isn’t about replacing people; it’s about helping teams do more with less. The following example highlights how a LangGraph-powered system is already handling quoting and scheduling—tasks that apply to nearly any business. The bigger point: AI agents are here, and they’re ready to do...

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May 12, 2025
Phase 2 Labs

In a recent exploration by Braxton Nunnally from Phase 2 Labs, it was examined how Zep—a memory management tool—can help AI systems retain and recall important information over time. This kind of “organizational memory” allows AI to move beyond one-off interactions and instead offer consistent, informed responses that build on past context. Common Business Pain Point: "Our AI tools don’t retain context or past interactions—users repeat themselves, teams lose knowledge, and we miss opportunities to respond more intelligently." What the Team Learned: AI Needs...

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