Public Example ยท Go2 Pilot

Operator Mode Audit

A two-week secure workflow audit for one person inside a team. This is a mode report, not a time tracker: it shows where work actually goes, what pressure it creates, and which automations should get installed first.

Mode report, not surveillance Private by default Role-specific insights Automation recommendations Edited for confidentiality
What the buyer should feel. "If you ran this on me or one of my people, I would finally see why the week feels overloaded, what is creating drag, and which two or three installs would make an immediate difference."
What this is not. It is not surveillance theater, not a generic dashboard, and not a dump of private internals. It is a tightly scoped operator mirror with recommendations, quick wins, and implementation-ready automation ideas.
2 weeks
Pilot window
Short enough to start fast, long enough to see real patterns.
61.4%
Build-stack share
Non-ambient work that stayed in build surfaces across the full pilot.
90.4%
Cleanest build day
The strongest single-mode day in the window.
2,805
AI handoff load
Useful output, but also a sign that context is still moving manually.
10.2h
Meeting footprint
Enough to shape the role. Too much to leave under-automated.
219m
Peak admin pull
A full-day signal that comms, search, and cleanup can swallow the role.
Executive Summary

The real drag is mode collision, not motivation.

This pilot surfaced a high-agency operator who behaves more like a system conductor than a single-threaded maker. The strongest output appeared when one mode stayed dominant long enough to compound: build, prep, synthesis, or decision-making. The biggest drag showed up when build, comms, publishing, revenue work, and admin all shared the same operating surface.

The second major pattern was rubric drift. Once this person knows what "good" looks like, they move extremely fast. When evaluation criteria live only in their head, time gets burned across models, tabs, and revisions. That makes rubric capture, decision capture, and follow-through support more valuable than another dashboard or more raw prompt volume.

High-level read. This person is already building the system they need. The job of the audit is to name the pattern, show where it breaks down, and install the first few pieces that let judgment compound instead of restarting every day.
What This Pilot Surfaces

Useful insights, not vanity metrics

Mode Mix

How much of the week was real creation, meetings, admin, sales motion, follow-up, and context recovery. The goal is to see whether the role stayed true to its intended mode, not to count hours like a bossware product.

Pressure Map

Where the role is carrying load that should be shared or systematized: repeated prep, fragmented knowledge lookup, meeting carryover, inbox debt, approval lag, and mode-switching friction.

Rubric Drift

Where quality criteria are implicit instead of reusable. This is often the hidden tax in AI-heavy teams: the person can judge good work, but the standard is not captured well enough to reuse across tools or teammates.

Automation-Ready Loops

The repeatable loops that are good candidates for AI assistance or automation: meeting prep, follow-up drafting, knowledge retrieval, exception handling, queue triage, recurring summaries, and decision capture.

Automation Table

What we would recommend first

These are the kinds of automations this pilot is meant to surface. They are specific enough to feel real, but written in a public-safe way that does not expose any one customer's internal setup.

Automation What It Fixes What The Customer Gets Estimated Lift Confidence
Rubric Capture and Reuse Good judgment exists, but evaluation criteria are living in one person's head and getting rebuilt across tools. Reusable criteria, example-backed review prompts, auto-suggested briefs, and a shared definition of "good" for recurring work. 3-6 hours/week plus faster convergence. 95%
Meeting Brief and Decision Capture Too much time spent reloading context before calls, then losing decisions after the call. Auto-generated pre-read, live note structure, extracted decisions, assigned next steps, and a clean follow-up draft. 3-5 hours/week plus fewer dropped decisions. 93%
Mode Guardrails and Admin Sweeps Creation work and admin work are happening in the same surface, which makes the day look busy but feel scattered. Named work modes, cleaner start-of-day rhythm, scheduled admin sweeps, and less random pull into comms during the core execution block. 4-6 hours/week of cleaner deep work. 91%
Canonical Brief and Context Router Heavy AI usage is productive, but continuity between tools and people is still too manual and brittle. Standard brief format, source-linked context cards, persistent handoff files, and less value trapped in manual handoff hops. 2-5 hours/week and less context loss. 90%
Follow-Through and Closure Layer Important replies, introductions, approvals, and next actions age quietly unless somebody remembers them. Daily open-loop sweep, aging alerts, meeting-to-task capture, and draft nudges for the highest-value stalled items. 2-4 hours/week plus better consistency. 92%
Role-Specific Queue Automation One-by-one handling, repeated explanations, and exception hunting are stealing time from higher-value judgment. Triage queues, approval layers, knowledge lookup, and exception feeds tailored to the person's actual role. 3-8 hours/week depending on role. 86%
Core Findings

The kind of things a customer should learn from this report

1. Mode collision is the real drag, not lack of effort. High confidence

What we saw. The same person repeatedly switched between creation, meetings, revenue work, admin, and coordination. The week was not short on output. It was expensive because multiple jobs were sharing the same operating surface.

Why it matters. Customers usually describe this as "too many tabs" or "constant interruptions," but the deeper issue is over-mixing modes. This is partly a behavior fix and partly an automation fix: protect a pure execution block, then route admin into a named sweep.

2. This person is a system conductor, not a single-threaded maker. High confidence

What we saw. The person thinks by steering tools, models, and people in parallel. That is a real strength. It is also why generic productivity advice misses: the role is orchestration-heavy by design.

Why it matters. Orchestration can feel productive even when the real bottleneck is choosing and committing. The right recommendation is not "be less ambitious." It is "end exploration blocks with one explicit shipped decision."

3. Rubric drift is a bigger AI tax than prompt quality. High confidence

What we saw. Once this person knows what "good" looks like, they can use AI extremely well. When the rubric is fuzzy, time gets burned across multiple models, tabs, and drafts.

Why it matters. The highest-leverage install is usually rubric capture and reuse, not more prompt traffic. This is mostly an automation fix with a little operating discipline wrapped around it.

4. Fast interruption recovery hides how much context shifting is happening. High confidence

What we saw. The person can bounce out, collect signal, and snap back quickly. That resilience is real, but it can mask the cost of mode churn because re-entry feels easy.

Why it matters. Recovering fast is not the same as switching cheaply. This is a behavior fix and a reporting fix: track mode churn, not just total output.

5. Wide scanning becomes decision debt without a closing ritual. High confidence

What we saw. Broad scanning was often strategic, not random. The drag appeared when a wide scan did not collapse into one commit, one artifact, or one next step.

Why it matters. A broad scan budget without a closing ritual turns into low-grade decision debt. This is partly coaching and partly a closure-layer installation.

6. System-building can become safer than uncomfortable external loops. High confidence

What we saw. High-agency operators will sometimes keep improving systems when the harder move is sending the follow-up, asking for the decision, or closing the human loop.

Why it matters. The audit should never reward elegant avoidance. Good automation reduces friction around external execution; it should not become a prettier hiding place.

First Recommendations

How we would help this person move faster in the next 14 days

Capture three recurring rubrics

Pick the three judgments that repeat most often in the role, save the criteria, attach one or two good examples, and make those rubrics reusable across AI tools and teammates.

Protect one named build block

Keep the first serious execution block out of inboxes, search consoles, and chat surfaces. Admin still gets done, but it gets its own sweep and its own stop time.

Turn every meeting into decisions and owners

Install a simple pre-brief plus post-meeting extraction flow so prep, recap, and next-step assignment stop depending on memory and goodwill.

Add a ruthless closure sweep

Run one daily pass that surfaces stalled replies, open approvals, aging handoffs, and unresolved decisions. The point is fewer quiet drops, not more guilt.

Other Role Examples

Same pilot, different person

This is where the example starts feeling real to a prospect. The same audit format can adapt to different roles without changing the core promise.

Founder / Operator

Mode collision, rubric drift, and follow-through debt

Typical pressure: build, comms, sales, and admin all compete on the same surface; broad scanning outpaces closure; judgment is strong but not always captured.

Likely installs: mode guardrails, rubric memory, meeting-to-task capture, closure sweep.

Customer Service Agent

Queue pressure, lookup drag, and escalation lag

Typical pressure: one-at-a-time inbox handling, repeated policy or order lookups, manual approvals, and the same explanations written over and over.

Likely installs: triage and draft assistant, knowledge copilot, approval queue, escalation routing.

Sales Rep / AE

Prep-to-live-selling ratio, post-call lag, and CRM debt

Typical pressure: scattered account context, too much manual prep, delayed follow-up, and next steps that stall between inbox, notes, and CRM.

Likely installs: account brief generator, recap to follow-up to CRM workflow, next-step tracker.

Ops Manager

Status chasing, reconciliation, and exception hunting

Typical pressure: manual reporting between systems, spreadsheet hopping, hidden coverage gaps, and too much issue detection by search instead of queue.

Likely installs: KPI refresh, exception feed, action tracker, recurring workflow routing.

Customer Deliverables

What the pilot should hand back

Individual audit report

A clean read on mode mix, pressure points, behavioral adjustments, and automation opportunities for one role.

Automation shortlist

A prioritized list of the first 3-6 automations worth implementing, with enough specificity to feel actionable and enough restraint to stay public-safe.

Quick wins

Simple process changes that improve the week immediately even before any software gets built: better mode separation, better closing rituals, better follow-through hygiene.

Optional implementation path

If the customer wants it, we can move from audit to implementation support. If not, the report still stands on its own and still makes the week more understandable.

Privacy and Positioning

What stays private, and what this example leaves out on purpose

Public-safe framing. This example is intentionally written to be impressive without being reckless. It shows the value of the pilot, not the internals of how every part works.
Go2 Pilot Example - Operator Mode Audit
Public example edited for confidentiality