Welcome to Ferguson Analytics' Applied AI blog where we share insights highlighting how we apply AI tools & technology to help our clients thrive in the midst of AI innovation and disruption.
Traditional data advantages (volume, exclusivity, historical datasets) are rapidly eroding due to foundation models and synthetic data generation
Sustainable data moats now require four foundational pillars: proprietary data collection, feedback loop architecture, workflow integration, and domain expertise
Companies with real-time user interaction data and continuous learning systems maintain 5+ year defensibility, while static datasets face 12-18 month vulnerability windows
Organizations implementing ChatGPT Projects and Claude Projects typically reduce content creation time by 70% and proposal development from days to hours
The 200K token context window in Claude Projects (equivalent to 500 pages) transforms AI from one-off chat to persistent strategic partner with company knowledge
Companies using these project workspace features report 2-3x faster execution on strategic work product compared to traditional AI prompting approaches
I’ve now seen multiple Series A startups quietly pivot from building AI products to offering AI consulting. Why? Because OpenAI, Anthropic, and Google keep absorbing features faster than startups can differentiate. One day you're building a document AI platform; the next, your core value prop is a checkbox in ChatGPT.
We're even seeing foundation models absorb capabilities that used to be a key differentiator for another foundational model (e.g. reaseach, citations, voice, etc.). Lasting businesses need deep workflow integration, proprietary data, or other moats – AI features alone aren’t enough.
Here's how to spot it coming and what actually survives.
I've watched too many startups burn through their runway making the wrong AI bet. They either throw everything at ChatGPT because it's the hot thing, or convince themselves they need to build custom AI from scratch because they're "different." Both approaches can kill your company.
Here's the reality: choosing between foundational AI and specialized AI isn't about technology. It's about business survival.
The wonderful thing about living in a city as big as Houston is that there is almost always something interesting going on in the world of AI, Tech, Startups, and Data. Check the key resources below to find a broad array of upcoming events. Dig deeper once you find a group you like. Join us to network with fellow AI & tech enthusiasts, learn from industry experts, meet founders & funders, and simply stay updated on the latest trends and technologies.
You're staring at a blank slide, your designer is out, and your calendar is packed with back-to-back meetings. Sound familiar?
What if you could generate a professional, visual, on-brand presentation in under an hour — without touching PowerPoint formatting tools or scrambling for stock images?
If you're like most enterprise developers working away with a fixed toolset, you maybe haven't had a chance to work with many AI coding tools beyond Github Copilot. Danger! There's a growing, dynamic ecosystem of specialized AI tools that can dramatically empower you as a developer. You must see how quickly these tools are improving and make sure you can adapt them to be more productive.
As an executive, you're facing a pivotal moment. AI tools are transforming how we work, think, and lead. While the landscape of AI tools is overwhelming, the cost of staying on the sidelines is growing. This guide provides a structured path to building your AI capabilities, one tool at a time.
Capture your client's attention with a spiffy personal blog based on mkdocs and a material theme. We'll walk through forking & modifying Jason Liu's consulting-blog-template for a free github.io hosted website.