Good, Better, Best — small AI gains, daily, that compound
Most "I'm behind on AI" anxiety is solved by a different question — not "how do I overhaul this," but "how do I make this 10% better today, and then again tomorrow." The cumulative shift is what changes the work.
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Most people approaching AI run one of two scripts in their head: "I'm already behind and I need to overhaul everything," or "I don't even know where to start, so I'll start never." Both end in the same place — nowhere.
The Good-Better-Best play is the alternative. Pick one workflow you do today, and find the version of it that's 10% better with AI in the loop. Use it. Tomorrow, do the same with another workflow.
This compounds. The AI high performers in McKinsey's 2025 data — the ~6% attributing 5%+ EBIT impact to AI — didn't get there by overhauling everything in a quarter. They got there by being nearly 3x as likely to fundamentally redesign individual workflows over time, one at a time.
The biggest gains in mid-market AI adoption aren't from people using AI in flashy new ways. They're from people using AI for 5 more minutes a day than they did last week.
The play
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From "good" to "better" — keep a personal prompt library
Write down 5–10 prompts you actually use. Reuse them. Tweak them. Save them where you can find them. The time saved from not re-inventing prompts compounds faster than any flashy new use case.
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From "good" to "better" — paste more context than feels reasonable
If you're asking AI to help with an email, paste the last three emails in the thread, not just your draft. Context is the cheat code.
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From "good" to "better" — name the audience
"Rewrite this for a skeptical CFO" produces wildly different output than "make this better." Tell the tool who it's for.
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From "better" to "best" — use AI to think, not just to type
The shift from "do this task for me" to "help me decide / pressure-test / reflect" is where the real value opens up.
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From "better" to "best" — let it disagree with you
"Argue the opposite side of this." "What am I missing?" "What would a skeptical reader push back on?" Produces sharper thinking than any yes-machine pattern.
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From "better" to "best" — debrief the week, not just plan it
Most people only use AI looking forward. Looking backward is where the pattern recognition lives. Ask what you spent too much time on, what you avoided.
What changes at 30 / 60 / 90 days
One person on the team has adopted Good-Better moves and visibly saved time. The team has noticed. Prompt library exists for at least one role.
Three to five team members are running daily Good-Better practices. A team-shared prompt library exists.
Team workflow has shifted from individual experimentation to shared practice. The next workflow redesign — moving toward Best — is actively in scope.
When this play applies
- Is this just glorified prompt engineering?
- Some of the early steps are. The full play is about a posture shift — from AI as typing aid to AI as thinking partner. Prompt engineering gets you to 'better.' The thinking-partner shift is what gets you to 'best.'
- Why does this work better than a top-down rollout?
- Because it doesn't require permission, infrastructure, or a planning cycle to start. McKinsey's data shows two-thirds of organizations haven't begun scaling AI — most because they're waiting for the perfect plan.
- Does this work for whole teams or just individuals?
- Both. The pattern that works at team level: leaders use AI openly and casually in front of their team.
- What about senior leaders? Different dynamic?
- Yes. SHRM 2026 found 73% of directors and above report creativity improvements from AI vs. 65% of individual contributors. The Good-Better-Best play is how individual contributors close that gap.
- When should we move from individual practice to coordinated rollout?
- When 25–40% of the team is fluently using AI on daily work. Earlier than that, a coordinated rollout fails for lack of internal advocates.
Sources
- AI high performers are nearly 3x as likely as others to say their organizations have fundamentally redesigned individual workflows — The state of AI in 2025: Agents, innovation, and transformation, McKinsey & Company (QuantumBlack, AI by McKinsey), 2025
- About 6% of organizations qualify as 'AI high performers' — those attributing 5%+ EBIT impact to AI — The state of AI in 2025: Agents, innovation, and transformation, McKinsey & Company (QuantumBlack, AI by McKinsey), 2025
- Roughly two-thirds of organizations have not yet begun scaling AI across the enterprise — The state of AI in 2025: Agents, innovation, and transformation, McKinsey & Company (QuantumBlack, AI by McKinsey), 2025
- Access to GenAI is largely limited to fewer than 40% of the workforce; among workers with access, fewer than 60% use it daily — Now decides next: Generating a new future — State of Generative AI in the Enterprise Quarter four, Deloitte AI Institute, 2025
- 73% of directors and above report creativity improvements from AI vs. 65% of individual contributors — The State of AI in HR 2026, SHRM (Society for Human Resource Management), 2026
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