AI Strategy Guide

Most companies approach their AI strategy backwards: models, agents, infrastructure, etc. They obsess with AI capabilities while missing the main question: "How does AI shift value in our industry?"

We wrote a brief AI strategy guide with focus on:

• Identifying disruptive changes caused by Gen AI

• Determining the direction of the value shifts

• Brainstorming for use cases that leverage the shifts to deliver new value

Built on proven frameworks: "Change Hits > Value Shifts > Money Follows" (CEO.works), Christensen's disruptive innovation theory, and Hal Gregersen's Question Burst method.

What value shifts are you seeing in your industry? Will the money follow?

Download AI Strategy Guide

Advanced Prompt Engineering for Multi-Agent AI Solution Development

Ready to move beyond simple chatbots and single-agent solutions? The future of AI lies in multi-agent systems where specialized AI agents collaborate to tackle complex challenges that would overwhelm traditional approaches.

Services as Software

OpenAI and Google Deep Research product launches signal a revolutionary shift in professional services. AI agents are transforming market research, legal, accounting, HR, and consulting. Firms must redefine their value and integrate AI agents to unlock new markets, cut costs, and stay competitive.

OpenAI vs DeepSeek Showdown. Judged by Claude.

Both OpenAI O1 and DeepSeek R1 are now available on AnyQuest. We compare their performance by asking the models to run an identical agentic workflow. The workflow uses popular business strategy frameworks to research a company, in this case, NVIDIA. O1 and OpenAI were represented by the o1-preview model. R1