Why most AI assistants fail in the first month after launch
The problem isn't the technology — it's everything that happens after you ship.
Insights on building AI assistants that actually work.
Practical thinking on workflows, AI design, and what it really takes to build assistants that teams use every day.
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From inbox chaos to clarity: how we built our own support assistant
A behind-the-scenes look at the assistant we built for ourselves — and what we learned along the way.
The difference between a chatbot and an AI assistant
A lot of teams think they want a chatbot. What they actually need is something else entirely.
How to scope an AI assistant project efficiently
Discovery is the most underrated phase of any AI project. Here's how we approach it.
What 36 years of engineering taught us about building with AI
AI changes fast. Good software principles don't.
The AI assistant use case hiding in plain sight in your company
Most teams have one workflow that's perfectly suited for an AI assistant. Here's how to find it.
Why we always say no to the first brief
What clients ask for and what they actually need are rarely the same thing.
The build-vs-buy question for AI assistants: how we help clients decide
Off-the-shelf AI tools are getting better. Custom assistants still win in specific situations. Here's the honest framework.
Why "we'll figure it out as we go" kills AI projects
Flexibility sounds good. In practice, undefined scope is the biggest predictor of failed AI deployments.
What makes a good AI assistant prompt — and why most companies get it wrong
The quality of your assistant's outputs is directly tied to how well it's instructed.
The hidden cost of a generic AI tool
Licensing a general-purpose AI tool feels cheaper than building something custom. Here's what the real cost looks like.
How we designed the conversation flow for our support assistant
Building a chat interface is easy. Designing a conversation that feels natural under pressure is hard.
How we handle hallucinations in production AI assistants
Every AI assistant will occasionally say something wrong. Here's how we design around it.
From blueprint to build: what our internal project handoff actually looks like
The handoff between design and engineering is the most important meeting in any project. Here's what happens in it.
Why we built our own demo instead of using someone else's
We could have pointed clients at a third-party tool. Instead we built something from scratch, on our own inbox. Here's why.
A practical checklist for evaluating an AI assistant vendor
Before you sign anything, here are the questions worth asking — and the answers that should give you pause.
How to write a brief for an AI assistant project
Most briefs focus on what you want built. The ones that lead to great outcomes focus on something else entirely.
How to measure whether your AI assistant is actually working
Deployment is not success. Here are the metrics that tell you whether your assistant is delivering real value.
How to get your team to actually use the AI assistant you just built
Adoption is a people problem, not a technology problem. Here's the onboarding approach we use.
What to do when your AI assistant gives a wrong answer
It will happen. The question isn't whether — it's whether you've designed for it.