Caleb Schmitz

The method is repeatable: start from a screenshot of the manual process that already exists, write a prompt that names the fields, colour rules, layout and saved searches in detail, iterate on the layout, then ask for the result to be converted into a Suitelet. Privacy gets handled before anything is shown publicly.

The Pipeline Allocation Manager, or PAM.

• Sales and resource management used to spend weekly effort on an Excel sheet that lined up delivery staff against the active pipeline.
• Caleb Schmitz gave Sonar a screenshot of that sheet plus a prompt specifying rows grouped by "Type of Work," customers placed by "Expected Close Month," names coloured red, yellow or green from "Subjective Probability," multi-select placeholders for planned project managers, two saved searches and a toggle for recently inactive opportunities.
• The instruction "Convert to Suitelet" produced a tool reading directly from NetSuite.
• A human developer then ran final testing, code review, repository updates and deployment, and real customer names were replaced with fictional ones before recording.

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Large, mission-critical builds such as custom Suitelet applications still need a developer involved, because a critical process that breaks has to be maintainable and quickly fixable — that work becomes AI-assisted rather than AI-replaced.

• The new opportunity sits in small process-polish projects that never cleared a cost-versus-value bar and are now worth doing, because the business impact of one going down for a few weeks is limited.
• Clients still need people who understand custom fields, custom records and script deployment, because someone has to direct the agents and judge what they produce.

Caleb Schmitz contrasts custom Suitelet applications, which can run into hundreds of hours and were only ever approved for a handful of mission-critical projects, with low-risk efficiency work that admins can now build with AI.

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The suggested method is a reverse demo, in which key stakeholder groups walk through their day-to-day work every two months — operations, accounts payable, accounts receivable, warehouse management — capped at one to two hours of client time a week. Communication matters as much as tooling: across Caleb Schmitz's customer base, roughly 70% of the client experience is communication, which is why sharpening soft skills is named as the first place to start.

The reverse demo itself: a scheduled walkthrough of each team's daily routine, used to surface the next operational problem while it is still cheap to solve.

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The reasoning is about credibility: an explanation pasted into an email is easy to doubt, while a filtered report with sensible defaults lets the person who asked the question confirm the finding on their own terms.

A CEO asked for analysis of a KPI that appeared to show a lead dip.

• Caleb Schmitz had launched a NetSuite CRM update on the same day, which created a new lead status separating marketing-qualified from sales-qualified leads and made new web leads default to that status.
• Sonar explained that records with the new status only existed from April onward, so the dip was largely an artifact of the new staging.
• Caleb Schmitz then had Sonar build an interactive graph with filters, and the CEO received a link to the report with defaults set to the correct criteria.

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The CRM update tracked marketing key events, web inquiries and a website form integration, and introduced a new lead status separating marketing-qualified from sales-qualified leads. Because leads were now categorised differently, a drop appeared in the numbers that was not a drop in demand — a reminder that whoever owns the reporting definitions shapes what leadership believes is happening.

The apparent April dip in leads, later shown to reflect the new MQL/SQL staging rather than fewer prospects.

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That shows up as an intent to meet as many other NetSuite partners as possible at SuiteWorld, to open lines of communication and bring what is described as a "Midwest nice" attitude to the event, and as willingness to point an audience toward a session on freight and LTL shipping for NetSuite and SuiteCommerce rather than only toward their own work.

A short post about connecting with other NetSuite partners in Las Vegas, and a separate pointer to a SuiteWorld session covering shipping built inside NetSuite.

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One short post jokes about an AI-generated advertisement for children's sensory bins that showed a grown man with a beard playing with the toys, offered as an example of AI missing the product marketing intent. It signals a conversational register and a general interest in where AI goes wrong, without committing to the subject as a work topic.

The sensory-bin advertisement joke, using a clearly mismatched AI-generated image as the punchline.

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It answers what Caleb Schmitz does with NetSuite AI in day-to-day operations.

Caleb Schmitz describes a specific internal build: PAM, or Pipeline Allocation Manager.

• The problem was a weekly manual process in which sales reps updated an Excel sheet from saved searches so resource management could pencil in delivery team members before deals closed.
• Caleb Schmitz gave Sonar a screenshot of the Excel file and a detailed prompt for an HTML report: group rows by the customer field "Type of Work," place customers in columns by "Expected Close Month," format names as "[Customer Name] – {Estimated Hours (PM) + Estimated Hours (Dev)}", color names red, yellow, or green from "Subjective Probability," show "{Customer Name} – Estimate Forecast Pending" when no hours are set, add multi-select placeholders for planned project managers, pull from the saved searches "Active Pipeline" and "Recently Inactive," and give recently inactive opportunities a toggle and a #FF6600 background at 33% opacity.
• After layout tuning, the prompt "Convert to Suitelet" produced a working Suitelet tied to NetSuite.
• A human developer then handled final testing, code review, repository updates, and deployment.
• Caleb Schmitz also notes that real customer names were swapped for fictional ones before recording.

For brands planning a campaign

This is the strongest case-study anchor for a NetSuite consulting or ERP software brand: it shows an AI-assisted internal tool from prompt to deployment, names the business process, preserves the human review step, and addresses privacy. A campaign can use it to illustrate practical AI workflow expertise rather than generic AI enthusiasm.

It answers the question of whether AI replaces NetSuite consultants or changes what they do.

This post is a field report and argument.

• Caleb Schmitz says they are just back from SuiteWorld and AI was everywhere.
• At Anchor Group, AI has been used for parts of the work where it makes sense and where a client allows it.
• NetSuite consulting demand has gone up over the last 10 months, but delivery is changing.
• Mission-critical development still needs a human: big custom Suitelet applications can run into hundreds of hours, only a handful of mission-critical projects ever got approved, and critical code must be maintainable and quickly fixable by a NetSuite developer.
• That work is AI-assisted, not AI-replaced.
• Work that never got approved is finally getting done: process polish and small efficiency wins where admins are starting to build with AI, and where a tool going down for a few weeks has limited business impact.
• Clients still need fundamentals such as custom fields, custom records, and script deployment so they can direct agents and judge what those agents build.
• Agents also need detailed requirements.
• Caleb Schmitz argues there is always another constraint and AI helps businesses get through each one faster.
• Advice includes sharpening soft skills, noting communication accounts for about 70% of client experience across their customer base, and helping clients find the next constraint using no more than 1–2 hours a week, such as reverse demos every two months.

For brands planning a campaign

This positions Caleb Schmitz as a practical commentator on AI adoption boundaries in ERP consulting: where AI belongs, where human developers remain necessary, and how consultants can help clients find the next constraint. It can support a campaign module on the changing role of consultants or on internal admin-led AI work.

It answers how NetSuite AI can support analysis, verification, and stakeholder communication.

Caleb Schmitz describes a CEO asking for analysis of a KPI that appeared to show a concerning lead dip.

• On April 1, Caleb Schmitz had gone live with a large NetSuite CRM update tracking marketing key events, web inquiries, a website form integration, and related data.
• The update created a new lead status to separate marketing-qualified leads from sales-qualified leads, and new web leads defaulted to that status.
• Caleb Schmitz asked Sonar: "Here is the KPI.
• Analyze why it appears the leads are low.
• It should show all the customer records created that month.
• I want to see why it shows a dip in the results starting in April."
• Sonar explained that records with a new lead status appeared from April 2026 onward and none existed before, so the dip was largely an artifact of the new MQL/SQL staging.
• Caleb Schmitz then asked Sonar to build an interactive graph with filters so the CEO could dig into the numbers and verify the findings.
• The CEO received a detailed email with a link to the interactive CRM report and defaults set to the relevant criteria.
• Caleb Schmitz concludes that leads were up all year and that Sonar is a powerful tool, then points to NetSuite help and the free Sonar tool.

For brands planning a campaign

This shows AI as an executive reporting and analysis assistant, not only a build tool. A campaign can use it to demonstrate internal admin judgment: diagnosing a reporting artifact, asking for a verifiable deliverable, and communicating the result to leadership.

A short post says that this year Caleb Schmitz is trying to connect with as many other NetSuite partners as possible, mostly to say hello, open a line of communication, and bring a "Midwest nice" attitude to Vegas. Caleb Schmitz says they enjoy meeting NetSuite consulting professionals in the ecosystem.

For brands planning a campaign

This is a community and partner-ecosystem signal. It can support event, partner, or co-marketing campaigns, but it is thin as primary work evidence because it does not show a client project or technical method.

Caleb Schmitz recommends checking out a SuiteWorld session if someone is looking at freight and LTL shipping options for NetSuite and SuiteCommerce. The session covers shipping as a whole with a shipping solution built inside NetSuite.

For brands planning a campaign

This shows awareness of NetSuite commerce and logistics workflows. It is relevant if a campaign targets shipping, fulfillment, or SuiteCommerce, but it is a pointer to a session rather than a deep example of Caleb Schmitz's own work.

The starting point was a weekly Excel sheet the sales and resource-management teams used to line up delivery staff against the active pipeline.

• Caleb Schmitz gave Sonar a screenshot of that sheet and a long written prompt covering the layout, colour rules tied to each opportunity's subjective probability, month-by-month columns, two saved searches (active pipeline and recently inactive), a show/hide toggle, and a placeholder field for planned project managers.
• After rounds of layout tweaks, the instruction "Convert to Suitelet" turned the mock-up into a working tool, which they call PAM (Pipeline Allocation Manager), reading directly from NetSuite.
• A human developer then ran testing, code review, repository updates, and deployment.
• Real customer names were swapped for fictional ones before it was shown publicly.
• The stated return was one to two hours of weekly manual work removed.

Start from a screenshot of the existing manual process, write an explicit prompt describing fields, layout, and saved searches, iterate on the layout, ask the agent to convert the result into a Suitelet, then route it through human testing, code review, and deployment.

For brands planning a campaign

A strong anchor for a practitioner-led case study: it shows the whole chain from a business process to a reviewed, deployed NetSuite tool, including the prompt text and the human review step.

Examples: Source 1

The split they draw: large mission-critical builds such as custom Suitelet applications still need a developer involved, because broken code in a critical process has to be maintainable and quickly fixable, so that work becomes AI-assisted rather than AI-replaced.

• Small process-polish projects that never cleared a cost-versus-value bar are now being built by admins with AI, because the business impact of a temporary outage is limited.
• They add that clients still need someone who understands custom fields, custom records, and script deployment to direct agents and judge what those agents produce.

For brands planning a campaign

Useful for an ERP vendor or consultancy framing responsible AI adoption: the post gives a ready-made distinction between high-risk work that stays human-led and low-risk work newly worth doing.

Examples: Source 1

The suggested method is a reverse demo, where key stakeholders walk through their day-to-day work every two months across operations, accounts payable, accounts receivable, and warehouse management, capped at one to two hours of client time per week. They also report that, across their customer base, communication accounts for roughly 70% of the client experience, and treat soft skills as the first place a consultant should improve.

A reverse demo: have each stakeholder group walk through its daily work on a roughly two-month cycle, using no more than one to two hours of client time per week.

For brands planning a campaign

Fits a campaign built around advisory method rather than tooling, for example a workshop or assessment offer framed as surfacing the client's next operational constraint.

Examples: Source 1

They asked Sonar to explain the apparent drop, got back an answer pointing to the new staging, and then went further: rather than forwarding the explanation, they had Sonar build an interactive graph with filters so the CEO could check the numbers directly.

• The result was an email with a link to the report, defaulted to the criteria the KPI should have used.
• The post closes with an offer of Anchor Group's NetSuite consulting help and a link to Sonar.

Ask the AI agent to explain the anomaly first, then convert the result into a filtered interactive report the stakeholder can verify themselves, rather than sending the raw explanation.

For brands planning a campaign

Demonstrates a repeatable pattern for internal reporting work: AI diagnosis plus a self-service report. A case study or webinar could follow the same arc from a leadership question to a verifiable answer.

Examples: Source 1

The detail matters because the report's apparent dip was a side effect of the status change rather than a drop in demand.

This is described inside a post whose main subject is the AI-assisted analysis, so the tracking design is context rather than a standalone guide.

For brands planning a campaign

Relevant for a campaign aimed at marketing operations or CRM administrators, where the hook is that tracking changes can look like performance changes unless the reporting keeps up.

Examples: Source 1

One flags a SuiteWorld session on freight and LTL shipping options for NetSuite and SuiteCommerce, framed as a way to learn about shipping as a whole with a shipping solution built inside NetSuite. The other is a networking note about meeting as many other NetSuite partners as possible in Las Vegas, opening lines of communication and bringing what they call a "Midwest nice" attitude to the event.

For brands planning a campaign

Shows willingness to promote third-party sessions and to invest in partner relationships, which suits ecosystem, event, or co-marketing work more than product-led campaigns.

Examples: Source 1 · Source 2

This is the least technical item in the set and carries no NetSuite or consulting content; treat it as a tone signal rather than a topic a brand can build a campaign on.

For brands planning a campaign

Useful only as evidence of a lighter, personal register. It should not be treated as a subject-area commitment.

Examples: Source 1

The posts also direct readers to contact Anchor Group's NetSuite consulting team for help.

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The posts do not disclose a sponsorship, affiliate, or client relationship with Oracle NetSuite.

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Brian Chess explains what customers ask Ask Oracle and launches a NetSuite Finance Analyst Skill for Claude and ChatGPT; Caleb Schmitz shows AI building and diagnosing NetSuite tools in practice.

Brian Chess writes from the NetSuite product side, explaining features, launches and customer question patterns. Caleb Schmitz writes from a consulting and administration side, showing internal builds and insisting on human testing, code review and deployment.

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Josh LaSov describes agents for bills of lading, payroll accruals, revenue analysis, order entry and cash application; Caleb Schmitz describes an AI-built pipeline allocation tool and an AI-assisted KPI investigation.

Josh LaSov presents productized agents for customer processes across several teams and systems. Caleb Schmitz more often shows a single internal tool built inside his own NetSuite instance, then ties the lesson back to consulting practice and how clients should direct AI work.

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The CISOExecNet posts make the case for listening before pitching, and the walkie-talkie example describes a sponsor who dropped prepared slides and answered what members had just raised. For a NetSuite consulting company running an event or a buyer-advisory programme, that is a usable, concrete message with an example attached.

The same campaign task changes shape: you get community and sales-conversation judgment, not a NetSuite build.

• The reviewed posts contain no ERP implementation, no AI tooling steps, no prompt, and no code-review or deployment detail, so the practitioner-led case study would have to be split, with a different subject carrying the technical half.
• The material also speaks from a community operator's point of view, which suits a channel-education angle better than a product or workflow demo.

Examples: Source 1 · Source 2

The two posts give a vendor-side read on how people actually talk to an ERP system — the overdue-invoice and cash-shortage questions, and the shift from learning which report to run to asking the business question directly — plus a named product launch in the NetSuite Finance Analyst Skill for Claude and ChatGPT. That is useful if the brief is to explain where AI in ERP is heading and to borrow the credibility of the platform making the change.

You lose the client-side story.

• The posts are product messaging about NetSuite's own AI features, so a case study built on them would describe capability being released rather than a problem solved inside a company, and would not show the messy parts the buyer's brief depends on: a manual spreadsheet being replaced, a prototype reviewed, a developer taking responsibility before deployment.
• Anything resembling Caleb Schmitz's PAM walkthrough would have to be sourced elsewhere.

Examples: Source 1 · Source 2

The posts list agents for bills of lading, payroll accruals across 18 subsidiaries and 50 states, revenue analysis, emailed order entry, and cash application, with times cut from six hours to five minutes and from eight hours to two. The revenue-analysis post is the strongest for a finance audience because it argues that an agent can keep searching where a person would have to stop, and that the CFO's time is better spent deciding what to do.

This is vendor marketing for a SuiteApp, so the platform is the subject rather than an independent practitioner, and every saving quoted comes from the company selling the agents.

• The reviewed posts do not show the human review, testing, or deployment step that gives Caleb Schmitz's build story its caution, so a buyer whose campaign leans on responsible AI-assisted delivery would need to add that evidence deliberately.
• Verifying the figures with the customer would also be the sponsoring company's job, not something the posts settle.

Examples: Source 1 · Source 2