Your Team Has AI Access. That Is Not the Same as AI Capability.

Generic AI training teaches prompting. It does not teach your account manager how to cut research time on a competitive brief from four hours to forty minutes. It does not teach your operations lead how to generate onboarding documents three times faster. General training produces general results, which is to say no results you can point to.

Before I build any program I spend time understanding what each role on your team produces, how they produce it, and where they lose the most time. The training comes out of that. I measure output before the program starts and again 60 days after. That is what accountability looks like.

I look at what your team actually produces, how long it takes, and which tools they are already using. I find where AI saves the most time per role and I set a baseline we can measure against. This is always the first step before anything else gets built.

I design programs around what each person on your team does every day. Not a general AI overview. A specific workflow-by-workflow plan for each role, with prompts and tools they can use immediately and output Benchmarks we track over 90 days.

When AI is producing inconsistent output across your team it is usually a standards problem, not a tools problem. I build a shared prompt library and review framework that raises the floor on AI output quality across every role.

I build the before-and-after measurement system before the program starts. Time per deliverable, output volume, quality scores. At 60 days you have a report that shows exactly what changed and by how much.

Before any tool is introduced I measure how your team works today. Time per deliverable, output per role, what they are already using. This is not optional. Without a baseline the rest of the program has no way to prove it worked.

I map each role's workflows and identify where AI saves the most time. I select tools, build the prompt structures, and set output standards for each workflow before a single training session is scheduled.

Every session is built around a specific deliverable type. Your account managers work through competitive brief research. Your writers work through content production. Nobody sits through a general AI overview. They use the tools on their actual work the same day.

Weekly tracking for the first 60 days. Output volume, time per deliverable, quality scores, and adoption by role. Results go to leadership with the before numbers sitting right next to the after numbers.

Where output quality is inconsistent I rewrite the prompts. Where time savings are below target I redesign the workflow. The program does not end at training completion. It ends when the productivity targets are reached.

A professional services firm came to me with 18 consultants and a proposal problem. Every proposal took about 6 hours from research through first draft. They had three AI tools with licenses across the team and zero standardized workflows. Training completion was fine. Output had not changed at all.

I started by documenting exactly how proposals were built. Then I redesigned the workflow around their actual research and writing process and built the prompt structures to match. After 60 days billable output per consultant was up 40%. Proposal time dropped from 6 hours to under 90 minutes. Research time per brief dropped 58%. They added 11 new client engagements that quarter without adding a single person.

• 6 hours average per proposal (research through first draft)
• No AI-assisted workflows for any deliverable type
• Manual competitive research averaging 4 hours per brief
• Tools open in tabs with no embedded usage patterns

• Proposal creation time under 90 minutes end-to-end
• AI-assisted research reducing brief preparation by 58%
• Team operating at 40% higher billable output per consultant
• 11 additional client engagements added without headcount increase

Every engagement starts with a real conversation, not a sales call. Start free, or book a focused session when you're ready to move.

Free

Ebby is trained on Andre's consulting frameworks and business methodology. Describe your situation, answer a few structured questions, and get an immediate assessment of your highest-leverage opportunities.

✓ Answer structured questions about your business and operations

✓ Ebby analyzes your situation using Andre's consulting frameworks

✓ Get a diagnosis of your highest-leverage operational opportunity

✓ Andre reviews your intake and responds within 1 business day

1 Hour + Written Report

$150 one-time

A focused one-hour session on your specific challenge. You receive a written Tech Stack Report: a clear recommendation on what to build, what tools to use, and why. Research-based. No implementation required to get value.

✓ 1-hour deep-dive on your challenge

✓ Written Tech Stack Report delivered after session

✓ Tool recommendations with rationale

✓ No implementation required. Pure expertise

The 8-20x ROI range comes from measuring hours saved versus hours invested in enablement across six client engagements run over 18 months. The range is wide because the inputs vary significantly by team, by role type, and by how output-intensive the work is.

On the lower end of that range, one engagement involved a 5-person team at a marketing agency. The engagement ran 8 weeks, cost 40 hours of engagement time plus 20 hours from the team participating in sessions and implementing workflows. At 90 days their content production output had increased by roughly 30% and they measured 12 hours per week in recovered time across the team. At their billing rate, 12 recovered hours per week is 624 hours per year. Against the investment, that delivered an 8x return in the first year.

On the higher end, an engagement with 18 consultants at a professional services firm. Each consultant was spending 6 hours per proposal from research through first draft. A workflow was designed using AI research tools and structured prompting templates that cut that time to 90 minutes. The firm ran 3 to 4 proposals per consultant per month. At 18 consultants across 12 months, the time savings compounded into several hundred recovered work hours. The program paid back the engagement cost in under 8 weeks.

The 15-25 hours of staff time recovered weekly is a direct measurement. Time per deliverable is tracked before the program starts, at 30 days, and at 60 days. The 15-hour floor comes from the smallest-scope engagements. The 25-hour ceiling comes from larger teams with high-output roles where the leverage is significant.