AI by Outcome Equals Strategy
Express every AI initiative as one sentence connecting usage to an outcome
- Difficulty
- Easy
- Time to result
- ~days to results
- Steps
- 5
- Confidence
- 99%
AI by Outcome Equals Strategy is a compact test for determining whether AI usage has strategic purpose. Begin with the proposed activity, such as building a second brain or introducing AI into blog production. Identify its immediate effect, then repeatedly ask what that effect enables until the chain reaches a result that matters. A second brain saves retrieval time, faster retrieval enables faster responses and decisions, and faster decisions improve execution. Compress that causal chain into one clear sentence containing both the AI activity and the intended outcome. Add a baseline and target so the claim can eventually be tested. If the team cannot produce the sentence, it has usage without strategy and should clarify, redesign, or reject the initiative rather than assuming experimentation automatically creates value.
Origin
Extracted from Marketing Against The Grain, where Kieran proposed the formula “AI by outcome equals strategy” as a forcing function for AI users and teams.
Core principles
- 01AI usage becomes strategic only when it serves an explicit outcome
- 02A build is not an outcome
- 03Trace benefits through a causal chain to a meaningful result
- 04State the strategy clearly enough to fit in one sentence
- 05Reject usage pursued solely for its own sake
How to run it
- 1
Name the AI activity
Describe exactly what will be built, automated, or changed with AI. Keep the description concrete enough that another person could identify the workflow.
Pro tip Use a verb and an object, such as “reduce blog drafting time with AI.”
Watch out Do not disguise a broad aspiration such as innovation as an activity.
- 2
Identify the immediate effect
State the first observable consequence of the activity, such as saving time, reducing cost, improving response speed, or increasing output quality.
Pro tip Include a baseline and desired target where available.
Watch out The existence of the tool is not itself an effect.
- 3
Build the causal chain
Ask what each effect enables next until the chain reaches a meaningful operational, financial, or personal result.
Pro tip Use successive “because” statements to expose missing links.
Watch out Do not jump from a minor efficiency to revenue without explaining the intervening mechanism.
- 4
Write the strategy sentence
Combine the AI activity, immediate effect, and final outcome into one concise sentence. The sentence should make the reason for spending time and tokens understandable.
Pro tip If the sentence cannot be written clearly, narrow the project.
Watch out A sentence that merely promises to “improve productivity” is still too vague.
- 5
Test the connection
Measure the immediate effect and final outcome during use. Revise or discontinue the strategy if the predicted causal link does not appear.
Pro tip Track leading and lagging indicators separately.
Watch out Do not preserve the initiative solely because its immediate output increased.
In the wild
A content team states: “We will use AI to reduce average blog-production time from five hours to one hour, allowing the team to publish useful content faster without lowering quality.” The baseline, target, mechanism, and intended result are explicit, so the workflow can be tested rather than celebrated for AI usage alone.
→ The team gains a measurable strategy for shortening content-production time.
An individual wants to build a second brain. Instead of treating the system itself as success, the person traces its value: faster information retrieval enables quicker responses, quicker responses enable faster decisions, and faster decisions improve results. The build is then evaluated against response and decision speed.
→ A personal AI project becomes connected to observable execution benefits.
Common mistakes
Stopping at the artifact
Building an agent, app, or second brain describes what exists, not why its existence matters.
Skipping causal links
Claiming that a tool will drive revenue without tracing intermediate effects produces a slogan rather than a strategy.
Using an unmeasurable outcome
Vague goals such as becoming more innovative cannot confirm whether the AI workflow worked.
Is it for you?
Best for
It is best for individuals and teams deciding whether a proposed AI workflow deserves time, tokens, and organizational attention.
Not ideal for
It is not ideal for deliberately exploratory research where the agreed outcome is discovery rather than a predetermined operational improvement.
From the transcript
“We could give people a really simplistic formula here, which is like AI by outcome equals strategy.”
“But because you actually have a single sentence that explains the outcome, now you have a strategy.”
“You have to answer a couple of a series of questions to really connect the thing you're building to the outcome.”
From the episode
They Spent $150,000 on AI Tokens (And Got Nothing)