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Hodl Advisory

AI workflow advisory

Complex AI workflows are expensive to learn through trial and error.

Before you build, while you’re building, or after launch, I help you decide what should use AI, what should stay software, where people stay in control, and what to do next.

Free Fit Call ↗ View packages →

When this helps

The work is real. The right system is not yet obvious.

Before you buildYou know the workflow you want to improve, but not what should be AI, software, or human.
Internal teamYour team can build, but this kind of AI workflow is new territory.
Already liveIt works, but needs too much supervision, repair, or manual checking.
Implementation companyClients are asking for AI workflows that are harder to scope than ordinary software.

Ways to work together

Choose the help the decision needs.

Start with a diagnosis, a target design, or ongoing support as the work changes.

Architecture Review

Find what needs attention and what to do next.

From €2,000 ?→

Deliverable / 01Architecture Review
F-01Role boundariesClarify ownership
F-02Evidence lineageClose the gap
F-03Approval pathMake explicit
Report findings · priorities · next actions

An independent diagnosis of one defined current or planned workflow, with prioritized findings and practical next actions.

Architecture Blueprint

Give the team an architecture to build from.

From €7,500 ?→

A target design for how the workflow, systems, AI, and human decisions should work together.

Ongoing Advisory

Keep difficult decisions moving.

From €2,500/month ?→

Engagement / 03Ongoing Advisory
01Decision loggedowner · why · next check
02Design reviewchallenge · resolve
03Direction resetkeep · revise · stop
Decision log · review cadence

Flexible architecture review and decision support as the work evolves. Cadence and scope follow the fit call.

Compare all packages →

Why outside judgment helps

Small ambiguities become expensive when the workflow can act.

An approval exists.Nobody can prove exactly which operation it authorized.
A provider times out.The system retries, and nobody knows whether the first action actually happened.
Someone disables execution.Queued work can still cross the external boundary.

Hodl / perspective

The architecture lens predates AI.

For more than three decades, I have worked on problems that crossed software, infrastructure, operations, unfamiliar domains, markets and business. The recurring job was the same: understand where the layers meet and find what actually determines the outcome.

01 / Whole systemsSee the whole system

Software → infrastructure → people → operations

02 / Learn the domainLearn unfamiliar domains quickly

Domain → operating model → architecture

03 / ConsequenceDesign for real consequences

Decision → execution → state → infrastructure

AI is the newest environment for that work, not its origin.Why this matters → About

Open standard / PROOFI authored PROOF as an open working method for testing what a system assumes, who may act, what may happen, how outcomes are checked, and how failures should be contained and handled.
Read PROOF ↗

AI as leverage

A serious multi-agent system behind my own work.

Clawblins is my personal AI crew: specialist roles with the context and tools they need, backed by software controls, review boundaries, and human authority. The names and personalities are the interface. The control system sits underneath.

Next step

Bring me the workflow.

Tell me what you are trying to improve, where it stands, and what feels difficult or unclear. We’ll use the Free Fit Call to decide whether I can help and what the next step should be.

  1. 01The workflow
  2. 02Where it stands
  3. 03What feels difficult
  4. 04What you need next
Free Fit Call ↗