Events

Free, in person, and small on purpose.

We do not run webinars. We run one Trailhead beat in a room with people who ship real work, and one evening where employers score a real artifact. Both are free. Both fill. The next dates go to the list first.

El Segundo and the South Bay first; online sessions announced as they are scheduled.

For working teams

The AI-Ready Team master class

Half a day · free · 24 seats

In person, hosted by a partner organization; one session online

Four hours, one workflow. You bring a real deliverable your team ships with AI in the loop. We run one full Trailhead beat on it, with Scout, in the room: compare two versions that differ on one thing that matters, invent the rule, defend it against the counter-case, then teach it to the AI and watch where it fails. You leave with a rule your team wrote and a checklist that runs in a minute.

You leave with

· The 60-second number check, on your own numbers

· A first-draft edit rule your team invented

· A clear read on whether a Trailhead cohort fits

For local employers and district staff

Employer Panel Night

One evening · free · per district

At the district, with the school and two or three employer partners

What a portfolio review actually is, shown rather than described. Guests score one anonymized student artifact against the rubric the way a panelist would, with the process trace beside it, then hear a ten-minute oral defense. Two guests score the same work and we show the agreement live. Districts use it to bring employers in; employers use it to decide whether reviewing is an hour they want to give.

You leave with

· A scored artifact and the reasoning behind your score

· How a brief is written, on one page

· The month-by-month partner timeline

The one-page guide

The 60-second number check.

This is the checklist learners write for themselves in the second module of both tracks, after they have caught a confident, cited, wrong number with their own hands. Here is the version we hand out at the door. Print it. Tape it next to the screen.

An AI writes the wrong line with exactly the same confidence as the right one, so formatting tells you nothing. A number earns its place with a check, never with its phrasing.

Trailhead · module S2 / T2

Before any AI number goes in your work

Expected magnitude, before you look.

Guess the size first. One newton-metre is roughly three-quarters of a pound-foot, so 10 N·m has to land near 7, not near 90. If the number on the page is far from your guess, one of you is wrong, and it is worth a minute to find out which.

The unit chain, written out.

Write the conversion as a chain (N·m → lb·ft × 0.7376; °C → °F × 1.8 + 32) and see whether the number actually went through it. A shifted decimal or a swapped factor shows up here and nowhere else.

One independent source you can open.

Not the AI’s own citation. A table, a datasheet, a colleague’s spreadsheet. A cited source you did not open is a decoration, not evidence.

Worked, in three lines

Claim. “A cyclist averages 25 km/h for 90 minutes: 37.5 km.”
Calculate. 25 km/h × 1.5 h = 37.5 km.
Sanity. A fast recreational ride covers 30 to 40 km in an hour and a half. Plausible. Ship it.

Try one. “Fastener torque: 10 N·m (approximately 89 lb·ft). Source: manufacturer datasheet, table 3.” Which check catches it, and what is the right value?

The answer is in the master class, and in your head already if you did step 1. The full module runs the same check on a six-line spec sheet with three wrong values, then has you teach the check to Scout and fix what your rules let through.