twimco.Let’s talk ↗︎
Menu

The TWIMCO notebook

Field notes.

Useful observations from inside the work.
For people building a better way.

A specialist selects evidence from an archive while an assistant carries a vetted folio to a colleague

Is this workflow ready for AI?

Before adding AI to a process, score it on handoffs, exceptions, visible state, recovery and who may approve changes. A readiness checklist you can use as a worksheet.

Read the note ↗︎
Hands working together over an architectural model and a sketched workflow

What ongoing partnership should mean in a software contract.

After launch, decide who owns incidents, upkeep and change—and what evidence shows that coverage is real, not just promised.

Read the note ↗︎
A human conductor coordinates workshop mechanisms that carry documents through the work

Scope the automation before you buy the tool.

Map the handoff, owners and exception path first. Tool choice is easier once the job is clear—and riskier when it is not.

Read the note ↗︎
An operator and an engineer inspect a parcel exception beside a moving packing line

Name the exception before you automate the happy path.

The work that breaks automation is usually the exception someone already handles by judgment. Design that path before you wire the clean one.

Read the note ↗︎
An illustrator compares jacket details on model-image proofs with the original garment using a magnifying glass and correction marks.

How to review AI-generated product imagery before it goes live

A polished image can still misrepresent the product. Build a review process around product fidelity, intended use and a clear approval decision.

Read the note ↗︎
An engineer guides a new operator through a working mechanism using its matching illustrated manual, access key and spare parts.

What a useful software handover should include

Source code is one part of ownership. A useful handover lets the next team deploy, diagnose, recover and change the system with confidence.

Read the note ↗︎
An analog sorting instrument with bounded trays and a human approval lever

What it takes to let AI agents operate a real business system

Natural language is the interface. Useful agent operation also needs bounded actions, permissions, visible state, recovery and a way to judge whether the work succeeded.

Read the note ↗︎
Engineers and operators inside a connected fulfillment business, joined by a red thread

AI app builder or engineering partner: how to choose

Choose around the work your system must do, the consequences of mistakes, and who will operate it after launch. A practical guide for founders and operations teams.

Read the note ↗︎
A phone, field notebook and rolled service plan sit beside a worn tool bag

The work between the screens.

The real requirements often appear when someone shows you how they get through an ordinary day.

Read the note ↗︎
An open delivery crate protects a ceramic bowl alongside a return envelope

Checkout is not the finish line.

Your customer experiences one promise. Your systems need to carry it all the way through.

Read the note ↗︎
A brass compass rests on an open task folder bounded by a red thread

An agent needs a job, not a personality.

Start with a responsibility, a boundary, and a way to tell whether the work was done well.

Read the note ↗︎
Hands relay a work order between different work surfaces

Start with the handoff.

The most useful place to automate may be the space between two perfectly good tools.

Read the note ↗︎
A good place to begin.

A familiar problem? Let’s look closer.

Tell us where you want to go. We’ll find the first thing worth changing.

Tell us about it ↗︎