Writing
Practical, evergreen guides on building with AI agents and GTM harnesses — pulled from the field notes we've found worth keeping around.
What is a GTM harness, and why use one instead of ChatGPT?
A GTM harness wraps an LLM in guided workflows and structured outputs built for one job — here's how that differs from prompting ChatGPT or Claude directly, and when it's worth the switch.
The AI enablement role companies are quietly hiring for
Samsara, Sonar, GitLab, and others are hiring a role that doesn't have a settled name yet — someone to build a shared AI context layer, wire up existing tools, and keep the stack current. Here's what the job actually involves.
Skill, agent, or app — which form should you build your expertise into?
Bottled expertise now takes one of three forms — a skill, an agent, or a vibe-coded app. Here's what each is for, who it's for, and how to pick.
Custom GPTs vs. AI agents — what's the difference, and when do you use each?
A Custom GPT is on-demand conversational help you steer with context and instructions. An AI agent is an automated, multi-step workflow that runs without you. Here's when each one fits.
Agent orchestration, explained simply — build capabilities like building blocks
"Agent orchestration" sounds complicated. In practice it means codifying one solved capability into an agent, then building the next capability on top of it — here's what that looks like in a real product.
Stop generating AI images — ask for editable HTML instead
Asking AI to regenerate an image for one small edit breaks the whole picture, because it's not editing — it's redrawing from scratch. Ask for a self-contained, editable HTML file instead. Includes a copy-paste prompt.
Why build in Cursor even if you're not writing code
The advantage of a coding agent like Cursor over ChatGPT isn't the model — it's that you can see and control exactly what context the AI is working with. Here's why that matters even for non-technical builders.
What I learned building 10+ AI agents used 14,000+ times
Lessons from building and shipping more than 10 AI agents, including one used 14,000+ times: agent building is product management more than prompting, and specialists — not developers — are often the best people to build them.
How to use AI deep research to quantify compliance risk in your messaging
A four-step framework for using ChatGPT's Deep Research to map a regulated buyer's compliance risk, quantify it in dollars, and turn it into specific, credible messaging — with copy-paste prompts.
Plan before you build — the loop framework for building with AI
Building well with AI is mostly planning, not prompting. The "loop" framework — objective, metric, boundary — turns one-off prompts into a system that runs itself until it checks back in with you.
How to turn your expertise into an AI audit agent — a case study
A one-person design studio cut homepage audits from an hour to 13 minutes by training an AI agent on her own framework. Here's how the agent was built, and how the case study itself was produced as an editable HTML file.
If your users live in Claude or ChatGPT, an MCP server matters more than your website
If people spend their day inside Claude or ChatGPT instead of your website, the way to reach them is an MCP server — not a better landing page. Here's what that looked like for one founder who built exactly that.