Why AI pilots stall in 'pilot purgatory' and why failure is often the signal that teams are learning fast enough to make the next model jump count.
A practical look at the 30-day Implementation Launchpad approach for mapping workflows, shipping focused pilots, and building AI agents that actually work.
At CES, it was obvious how wide the gap still is between knowing about AI and actually running it inside everyday work. Even advanced audiences can describe the tools but very few are operating with autonomous agents or the workflows that make them worth it.
The companies pulling ahead are the ones that keep failing fast, redesigning team structures, and shrinking the human layer to make space for always-on execution partners. That shift is already here, and most organizations are not ready for it.
Anthropic built an AI-powered interview tool and used it to talk to 1,250 professionals about how they actually feel about AI at work. They spoke with the general workforce, scientists, and creatives.
The research validates a lot of what we're seeing. People tend to like AI, they use it frequently, and they're still uneasy about it.
With the launch of this new website, we're bringing our three divisions—Mostly Serious, Habitat, and MSAI—into one space. It's important to understand how this all came together.
Fifteen years ago, Mostly Serious started in a spare bedroom building websites. Along the way, we built a team and culture that actually works—and that foundation led to Habitat and MSAI. Three divisions, one team, solving connected problems.
As AI tools become part of everyday work, the model you choose—4o, o3, 4.5, o3-pro, or whatever comes next—has a huge impact on quality, speed, and how “smart” the assistant feels.
This article shares how we teach teams to think about model choice in AI Quest Foundations, including simple personas for today’s ChatGPT models and why learning to pick the right one is a skill that will only matter more over time.
Most companies try to bolt generative AI onto existing workflows instead of reimagining how work should run when AI is in the loop—and that choice quietly determines who gets real ROI from these tools.
Drawing on data from Wharton’s 2025 AI Adoption Report and lessons from more than 50 organizations in our AI Quest program, this piece explains why smaller, more flexible teams are seeing outsized gains and how any company can start redesigning work for generative AI.
OpenAI Pulse is a new ChatGPT experience that proactively does research and delivers personalized updates based on your ongoing conversations, feedback, and connected apps like your calendar—instead of waiting for you to ask.
For teams thinking seriously about AI, Pulse is an early glimpse of a future where off‑the‑shelf assistants predict what you need next, replace fragile custom workflows, and quietly meet you where you already work.
Neglected websites quietly turn into security liabilities, performance bottlenecks, and lost revenue as outdated CMS versions, vulnerable plugins, and poor builds pile up—and marketing teams are often stuck waiting on overloaded IT or agencies to clean up the mess.
This article unpacks the real costs of website neglect, explains why proactive maintenance and our Craft CMS Health Check are smarter long-term investments, and outlines how a structured audit can stabilize your site, protect customer trust, and create a foundation for growth.
Creativity is what makes brands feel truly distinct, but every bold idea asks leaders to accept real risk instead of staying safely on the well-worn path.
This article explores how to evaluate the return on creative risk, learn from your customers, iterate your way toward bolder ideas, and test and refine brand moves so you can stand out without tanking trust or results.
This Dot One 2024 workshop recaps how to move beyond AI hype and start using tools like ChatGPT, Claude, Perplexity, and NotebookLM as part of your everyday work—from learning new topics faster to researching clients and preparing for sales conversations.
Use this article as the interactive companion to the talk: you’ll find links to the tools we used, copy‑and‑pasteable prompts, and a practical FAQ you can share with teammates who are just getting started with AI.