Why Your Company Needs a Custom AI Operating System
Most enterprises run hundreds of disconnected SaaS tools, and bolting AI features onto each one doesn't fix that. Here's why more companies are building a custom AI operating system instead, one layer that connects what you already have, built around how your business actually runs.
Your Business Card Should Live in Your Wallet. And It's Free: Wallet Cards Club
Paper cards get lost, go stale, and end up in the trash. Your contact information should live somewhere people actually look. WalletCards lets you create a free digital business card for Apple Wallet and Google Wallet in under two minutes. No app, no subscription, no expiration.
Why 88% of Companies Use AI and Only 6% See Results From It
Most Enterprise Teams Already Have AI. They Just Don't Have Anything to Show for It
Why Enterprise AI Adoption Fails in 2026 (And What the 8.6% Who Made It to Production Did Differently)
Vibe Coding Technical Debt: What Happens to Your Codebase at Month 6
How Much Does It Cost to Build an AI Product? A Real Breakdown for 2026
Most cost breakdowns for AI products are useless without context. A $50K project and a $500K project can both be called "an AI product", and both numbers can be accurate. Here's what actually determines where your build lands, and where companies typically lose budget before they know it.
Why Most AI Products Fail After Launch, And What Production-Ready Actually Means
80% of AI projects fail after the demo. Here's what separates products that survive production from prototypes that don't — and the specific decisions that make the difference.
How We Built an AI Sprint Planning Tool That Replaced Standups
How Imaginary Space built Flor.work, an AI sprint planning agent that generates sprint plans in seconds, assigns tasks by skill and capacity, and keeps engineering teams in sync through Slack. 40% less meeting time. 3x faster planning. Here's what we built, what we cut, and what we'd do differently.
How to Build an AI Product That Pulls From Multiple Data Sources (Without Breaking in Production)
Most AI products that aggregate external data don't fail because of the model. They fail because of the architecture decisions nobody made in week one. Here's what getting it right actually looks like.
Open Source LLM vs. API: How to Make the Build-vs-Buy Decision for Your AI Product
Open source LLMs now match frontier APIs on most benchmarks. Here's the framework for deciding which approach is right for your AI product and when the math changes.
Imaginary Space Hackathon #3: Build a Real AI MVP in One Day
On March 28 we're hosting our third hackathon at ACO Workspace. One day to build a working AI MVP, compete for prizes, and ship something real. 30 spots open.
AI Meeting Automation: Why Most Workflows Still Need a Human in the Middle
I built an agent last weekend that runs my entire post-meeting workflow without any input from me. No prompt. No copy-paste. No checking if it actually did the thing.
Vibe Coding Is Not an Enterprise Strategy. Here's What Is
Vibe coding ships demos fast. It doesn't ship enterprise software. Half of AI projects never reach production — not because the models fail, but because of decisions made (or skipped) in week one. Here's what actually separates prototypes from production.
How We Built CaseBench — A Digital Dentistry Workflow Platform Built for the Whole Case Lifecycle
The technology behind modern orthodontics is impressive. The infrastructure connecting it all is still WhatsApp and unlabelled STL files. Here's how we built CaseBench — a digital dentistry workflow platform architected around the case as the primary unit of work.
How We're Engineering the AI Brain Behind MeasureAI
Most software that claims to automate construction takeoffs is a better-looking spreadsheet with an OCR layer on top. You upload a PDF, it reads some numbers, you spend the next hour fixing what it missed. That's not AI construction takeoff software. That's digitized manual work.
Microsoft Silica: What 4.8TB in a Piece of Glass Actually Means for How We Build Systems
Microsoft stored 4.8TB in a piece of glass. Here's what the physics actually does, where it doesn't work yet, and what it means for architecture decisions today.