Will you always automate it?

No. The engagement uses the lowest reliable layer—often a better method or configuration is enough. Custom building is a last resort.

Is the automation safe?

Automation is supervised, reviewable, and used only where permissions and platform rules allow. Human approval is required before external or irreversible actions.

What if the workflow is not well understood yet?

Then a Readiness Review is usually the better first step, so the workflow and its value are clear before implementation.

Workflow Upgrade

Make one recurring workflow faster, clearer, and reviewable.

Configure or automate one proven workflow using existing systems, AI tools, integrations, voice, or supervised browser automation—with human approval at the appropriate points.

Scoped per workflow, based on complexity and integration

Bring one recurring workflow Check if your workflow qualifies

MIT education · Former Amazon product leader · Longtime CTO · You work directly with Jason

A tangled manual process on the left flowing through an orange human-approval checkpoint into a clean sequence of connected, reviewable workflow steps on the right

What qualifies as a good workflow

The best workflows to upgrade share a shape.

This engagement works best on a process that is already understood and worth improving.

Repeats often
Has recognizable inputs and outputs
Has a human owner
Creates a measurable delay, cost, or error burden
Can be reviewed before an external or irreversible action
Has enough volume to justify improvement

Examples by business function

Recurring workflows worth upgrading.

Sales

Lead response, sourced briefings, and proposal drafting with approval before outreach.

Operations

Document extraction, exception routing, and voice-to-task from meetings or the field.

Client service

Intake, standardized response drafting, and status updates with human approval.

Finance and admin

Invoice and AR follow-up prioritization and recurring report assembly.

Reporting

Pull from existing systems and produce a plain-language summary of what changed.

Research

Supervised browser research across approved sites, assembled into a reviewed report.

Implementation layers

Use the lowest layer that solves the problem reliably.

The engagement is not biased toward building. It uses the simplest approach that works and holds up.

1
Better method in an existing tool
Improve how a person uses ChatGPT, Claude, voice, or a suite feature on the task.
2
Shared team process and templates
Standardize the method with instructions, examples, and review rules the team shares.
3
Configuration or integration
Configure assistants or connect AI outputs to CRM, task, document, or reporting systems.
4
Selective custom build
Build a specialized component only when existing tools and light integration are inadequate.

What is included

A configured, tested, documented workflow.

One proven workflow configured or automated
Existing-system and data integration where useful
Voice or supervised browser automation where appropriate
Human review and escalation points
Acceptance testing against agreed criteria
Baseline and new-performance comparison
Documentation and staff enablement

What you provide

The upgrade works when the workflow is accessible.

A human owner for the workflow
Representative inputs and outputs
Access or permissions for the relevant systems
Existing constraints on data and tool use
Staff time for acceptance testing
A decision-maker to approve the acceptance criteria

Acceptance testing

Done means it works on real cases.

Required inputs are recognized
Output format is usable
Exceptions are routed correctly
Human approval occurs before external action
Failures are visible
Staff can operate the workflow
Baseline and new performance can be compared
Documentation is delivered

Data, permissions, and failure handling

Supervised by design.

Automation is supervised, reviewable, and used only where permissions and platform rules allow
Human approval is required before external or irreversible actions
Failure modes are made visible rather than hidden
Sensitive workflows may require approved vendors, agreements, or additional controls
The engagement covers one workflow; additional workflows are separately scoped
It does not guarantee a specific return on investment

A reliable, reviewable workflow beats an impressive demo that no one can trust in production.

Scope drivers

Scoped to the workflow.

Scope, deliverables, and a fixed price are defined in writing before work begins.

Price is affected by

Complexity of the workflow
Number of systems and integrations
Whether supervised automation is involved
Sensitive-data requirements
Volume and exception handling
Depth of acceptance testing and documentation

Case evidence

Examples of implementation work.

Outcomes are anonymized and estimated or observed where exact client metrics cannot be disclosed.

Call review automation

Voice summarization and task creation with human review cut call-review time by an estimated 60%.

Executive reporting

An automated weekly report reduced a two-day cycle to under two hours of review.

Intake and paperwork

Document extraction and pre-filled forms roughly halved intake prep time, with staff confirmation.

Why The Tomorrow Machine

Enough engineering depth to know when not to build.

You work directly with Jason Merkoski. Jason combines an MIT education, early Amazon product leadership, long CTO experience, and current hands-on work across AI tools, integrations, voice AI, supervised browser automation, and production systems.

That means the upgrade uses the lowest reliable layer—method, configuration, integration, or a build—rather than reaching for custom software by default.

Human review at the right points
Acceptance criteria before delivery
Documentation your staff can operate

FAQ

Questions buyers ask first.

The best candidates repeat often, have recognizable inputs and outputs, a human owner, a measurable burden, a review point before external action, and enough volume to matter.

Around the Workflow Upgrade

Where this fits in the ladder.

AI Productivity & Readiness Review

When the workflow is not yet well understood or prioritized.

See the Readiness Review

30-Day AI Productivity Program

When several roles need repeatable methods, not just one workflow.

See the 30-Day Program

Fractional AI Operator

For ongoing ownership once workflows start compounding.

See the Fractional Operator

Bring one recurring workflow

Bring one recurring workflow worth improving.

Describe the workflow, its owner, and where it slows down. We will confirm fit, choose the right implementation layer, and define acceptance criteria.

Free AI Strategy Conversation · No sales team · You speak directly with Jason

Prefer email? Reach Jason directly at hello@tomorrowmachine.ai.

Based in Santa Fe, New Mexico. U.S. Mountain and Pacific working hours.

Book an AI strategy conversation

Pick a time for a free 30-minute AI Strategy Conversation. Bring the business problem on your mind—you will leave with an honest point of view on where AI can create the most value, and your best next move.

What happens on the conversation

1.You describe the business problem, recurring work, or competitive pressure on your mind.
2.We share an honest, specific point of view on where AI could create the most value—and where it should not.
3.You leave with a concrete sense of your best next move, whether or not you work with us.
4.You speak directly with Jason Merkoski, our founder and principal consultant—no sales team, no pitch deck.

Useful to bring

The business problem or recurring work you want to improve
The AI tools and software your team already uses
What a meaningful first step would make possible