Before You Commit, Decide How You Could Change Course
· By Michel Valenzuela, Founder of Daryl
You are considering a promising idea.
You could begin with a small trial, learn from the result, and adjust. Or you could commit months of work before discovering whether the direction suits you.
Both approaches move the idea forward. They ask you to accept different consequences if you change your mind.
That is a useful question to bring into an AI conversation:
How difficult would this decision be to reverse?
The answer can shape how you begin.
Examine the commitment behind the choice
Some decisions leave you room to adjust.
Trying a new writing process for a week may cost a few hours. Testing a prototype with a small group may reveal problems before you make wider promises.
Other choices create dependencies.
You might commit a team to a platform, sign a long agreement, or announce a delivery date that several people begin planning around.
Before choosing, identify what the decision sets in motion.
Ask:
“If I proceed, what becomes harder to change? Consider time, money, other people’s work, and expectations.”
Use the answer to examine your actual circumstances. The assistant may suggest consequences that do not apply or overlook ones you know are important.
The purpose is to make the commitment visible.
Separate exploration from expansion
An idea can deserve investigation before it deserves a substantial commitment.
Suppose you want to offer a new service. You could first work through a limited engagement with a clear scope, assess the effort involved, and see whether the result is useful to the client.
That experience gives you information about delivery, demand, and your own interest in the work.
Expanding the service requires another decision.
It may involve hiring, building systems, or making promises to additional clients. Those commitments should reflect what you learned from the initial work.
Keeping the stages distinct gives you opportunities to reconsider deliberately.
Choose a first step that answers a real question
A trial is useful when you know what it is meant to reveal.
“See how it goes” leaves the interpretation open.
A clearer question might be:
“Can we deliver this service within the time available while meeting the agreed quality requirements?”
That tells you what to observe.
Ask an assistant:
“What is the smallest practical test that could answer this question? Explain what it would establish and what would remain uncertain.”
Then assess whether the proposed test is realistic.
A small test can reveal one useful fact without validating the entire idea. Keep its conclusions proportionate to what actually happened.
Set boundaries before starting
A trial can quietly become a permanent commitment.
One extra request leads to another. A temporary arrangement continues because nobody revisits it. Work expands beyond the original purpose.
Define the boundaries early.
What is included? How long will it run? How much time or money are you prepared to commit? What requires a separate decision?
For a new service, you might specify one client, one defined outcome, and a review after delivery.
Those boundaries make the experiment manageable and the later decision clearer.
Decide what would justify continuing
Before the result arrives, describe what you need to see.
Perhaps delivery must fit within a certain amount of time. Perhaps the client needs to find the outcome useful enough to commission further work. Perhaps you need to establish that a technical approach can meet a specific requirement.
Also identify what would justify changing or stopping.
This gives the review a basis beyond enthusiasm or disappointment.
An assistant can help you draft those conditions, but they need to reflect your resources and objectives. Avoid adding measurements simply because they are easy to count.
Account for other people’s expectations
Your ability to change course may depend on what others believe you have promised.
A pilot, a demonstration, and a full release communicate different levels of commitment.
Explain the arrangement accurately.
If you are testing a limited service, say what the test covers. If a date is provisional, make that clear before someone relies on it. If continuing depends on a review, establish when that review will happen.
Clear expectations give everyone a better understanding of what can change.
They also make it easier to respond responsibly when the results suggest another direction.
Make the review an actual decision
At the end of the trial, return to the original question.
What did you learn? Which conditions were met? What remains unresolved? What would the next stage require?
You may choose to continue, modify the approach, repeat a focused test, or stop.
Each outcome should have a reason.
Past effort is relevant when it creates useful assets or knowledge. It does not, by itself, establish that further commitment is worthwhile.
Assess the next stage using what you now know and what it would require from here.
Where Daryl fits
Daryl is a personal AI for Mac, currently in development, designed around local conversation and support for decisions.
I want it to help people examine the consequences of a choice, identify useful first steps, and recognise where another decision should happen before the commitment grows.
This article describes a way to think with AI. It does not announce a released planning or project-management feature.
For me, the appeal of this approach is practical.
You can begin something worthwhile while preserving room to learn. You can make a commitment with a clearer understanding of what changing course would involve.
Before you proceed, ask how you will review the direction.
That question can help you choose a better way to start.
Meet Daryl and get the launch announcement