Live · 11d Thu · May 14 · 17:00 UTC Lightning Lesson · Live org-readiness scan: 30 minutes inside a Series-B fintech Save my seat →
the five questions your board will ask most orgs cannot answer YES to any of them

Translate your organization into something agents can work inside.

AI strategy without an inventory is theater. Raising Agents is the publication, the live Lightning Lessons, and the cohort that deploys the Agent Trust Control Plane on your real organization — so by the end you can answer your board's five questions about agent governance with evidence, not slides.

Bi-weekly. One case file. One working artifact. No round-ups, no roadmaps, no AI takes.

readiness · sanitized client · 2026-04
before / after
Board Readiness Questions
The five questions every CTO is being asked. Right now.
"Errors at scale. Unlogged failures. Shadow agents reaching production. Governance cannot be optional anymore."
questions · 5 of 5 today: 0/5
Q1
Complete inventory of agents and their owners
Q2
Autonomy strictly tiered by risk level
Q3
Verified identities + least-privileged access
Q4
End-to-end decision reconstruction
Q5
Real, enforceable rollback plan
by Week 5 of the cohort: 5/5 YES with evidence How →

/L Lightning Lessons · live · free

The work, performed live.

Once a month, sixty minutes, free. Adrian runs an actual scan, builds an actual harness, or breaks an actual eval — on real org context, in front of you. No slides. No theory.

Hosted on Maven. ~50% of attendees join the cohort waitlist. Recording mailed to subscribers.

Lightning Lesson · 03 Thursday May 14 17:00 UTC · 60 min
Live · free · on Maven

Live org-readiness scan: 30 minutes inside a Series-B fintech

org-readiness-scan-v1.sh on real org context (anonymized) 287 signed up capped at 500 recording for subscribers
Past lessons · replays All Lightning Lessons →
LL · 02
Live influence-conflict scan on a 60-engineer org

Replay + written companion issue + the artifact Adrian built on stage.

312 attended 2026-04-10
LL · 01
AI strategy without an inventory is theater — live demo

Replay + written companion issue + the artifact Adrian built on stage.

248 attended 2026-03-13


about · operator zero

Adrian Sanchez de la Sierra. Deprecated.

Head of AI at Zartis. Through that role, he sees roughly thirty client AI transformations a year, at the partner tier closest to Anthropic in Europe.

The publication is the residue. Not advice. Field notes — anonymized, evidence-bound, paired with the working artifact each finding produced.

Read the long version →

On the credential: Zartis is Anthropic's #1 European partner by client engagement volume. It's mentioned because it explains the access. It's not the product.

excerpted · first person · field notes
"AI strategy without an inventory is theater. Three quarters of the rooms I walk into don't have a list of what's already running."

— Deprecated, field note 041

"I'm not transforming anyone's organization. I'm translating organizations into something agents can work inside. The translation is the work."

— Deprecated, field note 029

What 30 transformations a year looks like 2025–2026
orgs~30 / yr
size40 → 4,000 engineers
sectorsfintech · health · gov · b2b SaaS
artifacts14 shipped · all in archive

/LAB Trust Lab · the substrate, public
live · real LLM calls no slides · run it yourself

The Agent Trust Control Plane has a substrate. Open it.

Trust Lab is a working instrument from inside ATCP: call a real LLM, inspect the trust signals on the answer, tune release thresholds, run a capped repeatability audit, see whether the same prompt gives the same result, and watch the gate decide release, review, or block.

This is what the cohort installs on your real organization. Run the public version first. Then read the publication. Then deploy ATCP on your org via the cohort.

Open Trust Lab
Trust run · preview score · 0.71
Decision
Review

Confidence is the weak layer. The answer may be right, but the release gate holds it until a human checks the uncertain claim.

GRAIN0.82
GRIP0.58
KNOT0.79
VEIN0.74

/C Cohort course · paid · quarterly · on Maven

Claude Code for AI Transformation Leads.

Five weeks. Stand up the Agent Trust Control Plane on your real organization. Ship one governed agent inside it. Walk in Monday with a Board Readiness Report that answers the five questions YES with evidence — not a deck.

For senior engineers, staff engineers, AI leads, and Heads of AI at non-FAANG companies who have been told "lead our AI adoption" and don't have a playbook beyond a chatbot.

Course details + waitlist
Beta · cohort 0 By invitation €1,495 May 2026 · 25 seats closed
Public · cohort 1 Open waitlist €1,995 June 2026 · 40 seats waitlist · 247
Cohort 2 Open €2,495 Sep 2026 · 50 seats waitlist opens June
Cohort 3 + Certification track €2,995 Q1 2027 · 60 seats
5
McKinsey questions
answered YES
5
ATCP planes
installed
1
governed agent
shipped to a team
1:1
scan review
with Adrian

/A Free artifact · no signup

The org-readiness scan Adrian runs in Lightning Lesson 01.

A short bash script that walks an org's repos and produces an inventory of what's already running with Claude Code: instructions, agents, hooks, MCP servers, version drift, conflicts.

Local-first. No telemetry. MIT. Works on macOS and Linux. Read it before you run it.

Download artifact
org-readiness-scan-v1.sh bash · 312 lines

Inventories CLAUDE.md hierarchy, agents, slash commands, hooks, and MCP configuration across a target directory tree. Reports drift, conflicts, and undocumented trust surfaces.

requires
bash 4+, ripgrep, jq
runs in
~6s on a 50-repo monorepo
license
MIT · attribution welcome
updated
2026-04-22 · v1.0.3
README → Source 1,847 downloads

Bi-weekly · free 3,217 engineers subscribed · 0% open-rate optimization

One case file, every other Wednesday. With the artifact that came out of it.

You'll also get an invite to the next Lightning Lesson, the moment the cohort waitlist opens, and the occasional one-line note when something interesting comes out of a client engagement. Trust Lab is open the whole time — run it whenever.

Bi-weekly. One case file. One working artifact. No round-ups, no roadmaps, no AI takes.