LevrAge.Innovation Studios

Applied AI. Human judgment.

AI capability is
engineered,
not installed.

Use AI for worthwhile work, with understanding and control you can demonstrate.

Pilot learning sessions, workflow setup and focused builds for founders, operators and small teams.

Taking inquiries for the first Foundations pilot. One senior builder.
No published learner outcomes yet.

The control loopIllustrative model
Human controlBounded capability04 / 05
3D view of the illustrative model. Drag horizontally or use arrow keys to rotate. Home or Escape resets the view. Stage buttons below explain the control loop.

Make the output answer to a source.

Inspect the evidence, test the result and make uncertainty visible before anyone relies on it.

Evidence before confidenceTry verification
Learn the method. Build with intent.Explore the studio

01 / Inside the lab

A polished answer.
A reason to look closer.

Before you trust an AI summary, put it beside its source. Try a small piece of the method for yourself.

Free to try / No sign-up / Fictional material

ai-summary.md
Looks finished

Practice drill · Unit 4 · Verify every claim

An AI summarised a supplier contract. Tap every sentence you would not sign off on.

source · linen-supply-agreement.pdfFictional
  1. 4.1This agreement renews automatically on 30 June for a further 12 months.
  2. 4.2Either party may terminate by written notice given at least 60 days before the renewal date.
  3. 7.1From the renewal date, unit prices increase by 3% on all orders.
  4. 7.2Orders above 500 units in a single delivery receive a 2% volume discount.

0 flagged

0 flagged · fictional contract, errors seeded by us

02 / Learning & practice

Learn the method

Foundations is taking inquiries for its first pilot sessions. Operating Layer and Practitioner are not yet scheduled; register interest and you will hear when they open. Sessions use fictional cases, artifacts you keep and a reasoning check with the AI switched off. The paths are not a sequence: choose by the work you want to do.

Start with something you’ve noticed.

An answer that sounds certain. A conversation that drifts. An assistant with too much access. Our free field guide connects these experiences to useful concepts and short practice.

Explore the field guide →

Two questions

Explore learning paths

These questions identify your interests, not your capability. Answers stay on this page; only a path you choose to discuss is copied into the inquiry form.

1Who is this for?
2What do you want next?

A path to discuss

What this guide can and cannot tell you

Useful outputs and confidence do not establish understanding or control. Each pilot path includes practice with fictional material and a check of the reasoning behind a decision. These checks do not certify organizational readiness.

Choose who this is for and what you want to work on. You can also browse every path below without answering.
Path 1Taking pilot inquiries

Foundations

Practice framing useful work, setting data boundaries and checking AI output.

Responsibility in the exercise

AI drafts. You decide every step.

Practice check

Catch the seeded errors in a polished draft, then explain the fix with the AI switched off.

Takeaways, formats and who it's for

Planned takeaways

  • A task-brief habit
  • A data rule you can say out loud: internal, personal, public, and what never leaves
  • A verification checklist where check is not done
  • One worked case in your own domain, on fictional data

For: Founders and operators; Association and back-office staff; Anyone who drafts, reviews or sends work; Dictation-first and mouse-first users.

Formats: 90-minute session · Half-day · 1:1 concierge, including dictation-and-mouse workflows

Optional follow-on support: Signal Scan, Foundations for a team

Path 2Not yet scheduled

Operating Layer

Plan and test controls for one fictional team workflow: routing, memory, approval points and handoffs.

Responsibility in the exercise

You name the owner, define what AI may do and test when a person must intervene.

Practice check

Demonstrate when the approval point should stop a fictional workflow during a failure drill.

Takeaways, formats and who it's for

Planned takeaways

  • A routing card: cheap default, escalate by decision class, never by outage
  • A memory and handoff structure
  • One defined approval point
  • A first runbook

For: Founders and team leads putting AI into one repeated workflow; Small teams with a named owner.

Formats: Half-day team workshop · 60-minute executive working session

Optional follow-on support: AI Operating System Setup

Path 3Not yet scheduled

Practitioner

Practice one agent-assisted code change under a human review gate.

Responsibility in the exercise

You inspect and test changes before approving a write. The exercise separates private data, untrusted content and outbound actions.

Practice check

Reproduce one gated change end to end, then run the failure drill against a fictional practice repo.

Takeaways, formats and who it's for

Planned takeaways

  • A write-gate workbook
  • One gated change reproduced end to end
  • A project-state and inspection pattern
  • A failure drill against a fictional practice repo

For: Developers and technical leads working with coding agents; Teams receiving a codebase handoff.

Formats: Half-day practitioner workshop · Handoff session

Optional follow-on support: Advisory, Custom build, Developer handoff

How we check and improve the method
Run the workRecord thefailureRatify a ruleShip aversionThe methodIMPROVEMENT LOOP

What's current

Every failure becomes a rule. Here are the latest two.

Rules ship in dated versions. This panel shows dates, not promises.

Latest field notes

  • 2026-10-26 · v0.1

    Failed A draft hero line promised to rerun the test battery every time the models change, before any run existed.

    Rule The surface shows dates, never a cadence.

  • 2026-10-26 · v0.1

    Failed Two claims inherited from an earlier working session, a scored model ladder and a twelve-week module, did not exist on disk.

    Rule Verify every asset before citing it. Check is not done.

Method
v0.1 · 6 units · draftLast reviewed 2026-10-26. Not yet ratified.
Model checks
Pending first runNo model-specific claim appears on this site until a dated run exists.
Sessions
By requestPrivate sessions by request. No public date yet.
What the labels mean, with examples
Observed
Your answer met this exercise’s rule. It does not establish performance on other work.For example: You identified all of the planted errors in this case without flagging supported claims.
Gap
An answer missed something this exercise was designed to check.For example: A summary contradicted a supplied date and you did not flag it.
Unresolved
This exercise did not establish a clear result: it was skipped or the answers were mixed. The evidence line says which.For example: You caught the errors but also rejected supported claims.
Not assessed
This check has no task that can establish this part of your work.For example: A fictional quiz cannot show who approves changes in your team.
Supported
The available evidence justifies this specific claim.For example: An order lists four $20 boxes and includes delivery; the $80 total is supported.
Not established
The available evidence does not settle the claim. It may be true or false.For example: Finding one document does not establish that every relevant file was searched.
Catch
Stop and name the error, missing evidence or uncertainty before relying on an output.For example: Point to the source date that contradicts a summary, then correct the summary.
Operating layer
The permissions, checks, responsibilities and recovery steps around one workflow.For example: An assistant drafts; a named person checks the source and approves sending.
Control loop
A repeatable sequence for framing the task, limiting access, choosing tools, checking results and approving action.For example: Define the goal, draft with limited access, compare against the source, then decide whether to use it.
Demonstrated
Shown by a particular observation or test, within its limits.For example: Opening a file demonstrates access to that file; it does not demonstrate full folder coverage.

Interface definitions v0.1. These labels describe evidence in a task, not a person’s level or qualification.

All cases are fictional. We never run a session on a participant's live files.

Ask about a Foundations pilot

03 / Studio services

Choose the help
the work needs.

Each offer stands on its own. Pilot learning sessions are scoped and priced before booking; the ranges below cover setup and build work.

AI operating system setup

$500–$5K

For one person or a small team ready to put a workflow in order.

We set it up with you. This is different from the Operating Layer learning path, where a team practises planning and testing these controls itself.

A scoped setup in your own accounts, with routing, permissions, project memory and a runbook.

Scope and limits
  • Provider setup and routing by task and cost
  • Read-first tool connections and defined approval points
  • A runbook, handoff and a couple of weeks of check-ins

Scope is agreed first. Autonomous operations, security guarantees and long-term managed IT are outside this offer.

Discuss this offer

Knowledge Asset Recovery Signal Scan

$250 · beta

For a bounded folder of text-native notes, research or repo docs.

An inventory, source-linked findings and a now / next / later action map before you commit to a build.

Scope and limits
  • One approved text-native folder, with your files unchanged
  • Evidence-backed findings and an action map
  • A recommendation on whether further work is worthwhile

Excludes OCR, DOCX/PDF extraction, cloud ingestion and legal, health, finance or compliance review.

Discuss this offer

A focused first build

POC $2,500–$6,500

For founders with one core behavior to test with users.

Working software with a defined scope, a review gate and a handoff your team can use.

Scope and limits
  • One core flow with the auth, data and API it needs
  • Hosting in accounts you own and handoff documentation
  • MVP launch scopes: $8,500–$20,000

Prototype and launch scopes differ. Scale engineering, large-team features and open-ended maintenance are scoped separately.

Discuss this offer

Technical advisory

Scoped on request

For an architecture, tooling or project-state decision before implementation.

A clear recommendation, the tradeoffs behind it and a bounded next step.

Scope and limits
  • Architecture or project-state review
  • Tool selection, routing and budget sizing
  • Operating doctrine and implementation boundaries

Advisory does not include a full implementation, legal opinions or compliance certification.

Discuss this offer

A fixed scope, deliverables and quote are agreed before work begins. Discuss a task →

04 / Built at the studio

Work you can explore.

A community site, a public-data monitor and a studio product. These show build experience; learner outcomes are still to be established.

Full portfolio & experiments →

Community work

ZANC California

Built and deployed for the ZANC community — events, membership, and payments on a site the association owns and runs day to day.

Explore ZANC California

Public data monitor

ZambiaMacro

A public monitor of power stress in Zambia's Kariba hydrology channel, built from public data. Readings are labelled observed or estimated, with the model's confidence shown: a present-state reading, not a forecast.

Explore ZambiaMacro
LevrAge example card in the Prism edition: the sample name Alex Morgan beside a line-drawn holographic ring.
Example card · levrage.app

Studio product

LevrAge

The studio's own product. Make your card, share it with a scan, and let Levi help you remember the people you meet. Live, with open beta in preparation.

Explore LevrAge

From conversation to useful work

A clear next step, with you in control.

  1. 01

    Bring a task

    Tell us what you want to do, who owns the decision and what needs to stay under your control.

  2. 02

    Agree the scope

    Choose the useful next step. Confirm the preparation, deliverables, fee and limits before booking.

  3. 03

    Practice or build, then review

    Keep the artifacts and check the result. Learning uses fictional cases; setup and builds use separately agreed access.

05 / Start a conversation

Tell us about the work

Choose a learning session, help with a workflow, or a focused build. You can also start with a question.

Share enough detail to understand what you need, who it's for, your timeline, and what success looks like. If it's not a fit, you'll hear that quickly.

Describe the task, not the data. Please keep confidential, personal and client material out of this form. Your inquiry is emailed to the studio for a reply.

Your inquiry
What kind of help do you need? (required)