Stack POV: Automation, AI, and Infrastructure

Amazon Web Services (AWS)Amazon

Cloud infrastructure for the custom applications and integrations that off-the-shelf tools do not cover.

AWS is where we deploy custom applications, internal tooling, and the integration infrastructure that goes past what Zapier or native connectors handle. The platform is genuinely deep, and using it well requires discipline. For the engagements that warrant custom infrastructure, AWS is the right default.

What feeds it

Application code, integration logic, and the operational data those applications generate.

What it feeds

Custom applications consumed by clients or internal teams, integration endpoints called by other systems, and the data infrastructure that supports advanced reporting.

Problems it solves

>Hosting custom applications that off-the-shelf platforms do not cover.
>Integration infrastructure for high-volume or complex API workflows.
>Data warehousing and analytics infrastructure for organizations operating past the limits of platform-native reporting.
>Identity and access management for custom internal tooling.

Why we like it

Where it earns the line item.

AWS rewards operational discipline. The platform's depth supports almost any infrastructure pattern, and the cost is genuinely competitive when used deliberately. We use it for the custom development work where it is the right shape.

Known limitations

What we have run into in real engagements.

!Cost without discipline accumulates fast. AWS billing surprises are a category of incident.
!Operational complexity is high; running AWS well requires real expertise.
!Service breadth is overwhelming; navigating to the right service for a use case takes deliberate experience.
!Other clouds (Google Cloud, Azure) are credible alternatives depending on the rest of the stack.

Framework fit

Where Amazon Web Services (AWS) fits in Define, Develop, Deliver.

Develop

Infrastructure layer for custom applications and integrations.

Adjacent tools

Other platforms that show up in the same conversations.

Google Sheets and Apps Script

The automation layer most marketing teams already have and consistently underuse.

Zapier

No-code workflow automation that earns its keep when the use case is reasonably standard.

AI Assistants (ChatGPT, Claude, Replit)

AI tooling applied to the specific operational tasks where it improves speed and accuracy, directed by senior judgment.

Related services and operations work

Custom App Development

Senior implementation, integration, or audit work involving Amazon Web Services (AWS).

Frequently asked questions

QDo you work in AWS for clients who already use it?+

Yes. Most engagements are inside instances that have been running for a year or more, where the original implementation has drifted and the current team needs senior judgment to repair and re-govern it.

QCan you help us decide whether AWS is the right tool for us?+

Selection conversations are part of the work. The right answer almost always comes down to the team that has to operate it, the integration depth required, and the cost trajectory three years out, not the feature comparison matrix.

Operate Amazon Web Services (AWS) with discipline

Need senior help with Amazon Web Services (AWS)?

Most Amazon Web Services (AWS) engagements we run are inside instances that have been operating for a while and have accumulated configuration drift. The work is to repair, re-govern, and make the platform behave the way the strategy assumes it does.

Talk with Phil Back to the stack overview