Lawrence Jones

We’ve been working on a project called Extensions: customers can now connect their MCPs into our platform then load skills that tell us how to use them, with both skills and connectors (our word for a connected MCP or API) woven into all our agent surface…

Every weekday morning, someone on the AI team at incident.io kicks off our spend report skill.

Last year I wrote this from an empty office on New Year’s Eve.

We’ve just launched an AI Engineer role, and Pete’s written a post explaining why we’ve created the role which goes nicely with our blog series “Building with AI” that the team released the other week.

I’m currently building an AI-powered incident investigation product that automatically debugs and triages production issues when incidents are declared.

“If you want to build AI products, you need to use Python.”

Most companies building AI products today are stuck in the experimental phase, lacking the basic tooling and infrastructure needed to build reliable systems.

I’m determined to make a tradition of this, which is why I find myself in an empty office on New Years Eve trying to remember what’s gone by these last twelve months.

It was the week before pandemic lockdowns began.

Of the mental models and rules I use in my life, by far the most useful is to learn only one thing at any given time.

Last year I wrote “Looking back at 2022” and found it valuable to reflect and celebrate a year of work, even if just as a reminder of the things that happened before going into the next.

Recently, I’ve needed to add concurrency protections to several HTTP APIs.

Most people are familiar with state machines and know their value.

From the moment you learn programming people tell you “don’t repeat yourself!”

For the last three months I’ve been working on a team building the incident.io Catalog: read the announcement post here.