TL;DR
Thorsten Meyer AI has published Outcome-First Decisions, an open-source framework that reviews initiatives by current outcomes and ongoing cost. The Day 8 Built in Public dispatch says the tool returns one of three verdicts: keep, change or kill, with the explicit aim of making stalled work easier to end.
Thorsten Meyer AI has published Outcome-First Decisions, an open-source decision framework that tells operators whether to keep, change or kill an initiative based on the outcome it is producing now and the cost of continuing it.
The framework was introduced in the site’s Built in Public series as Day 8 of 19 and is described as part of the operator portfolio’s “Decision Layer.” According to the source material, Outcome-First Decisions is available on GitHub under the AGPL-3.0 license and is intended as a small, opinionated framework rather than a broad management system.
Its central mechanism is called the Worth Filter. The filter asks one forward-looking question: whether the outcome an initiative is producing now is worth its ongoing cost. The source says the framework deliberately excludes sunk cost, effort already spent and identity attachment from the decision.
The framework returns one of three verdicts. Keep means the outcome justifies continued investment. Change means the underlying idea may still have value, but its current form is not working. Kill means the outcome does not justify the cost and the initiative should be ended cleanly.
Outcome-First Decisions — keep, change, or kill
The hardest decision isn’t what to start — it’s what to stop. Judge every initiative by the outcome it produces now, not the effort already spent.
Independent commentary, produced with AI assistance under human editorial oversight. The views are the author’s own and may change. Outcome-First Decisions is open source under AGPL-3.0, provided “as is” without warranty; see the repository LICENSE. The framework’s verdicts are reasoning aids based on the inputs given and may be wrong — decision support, not decisions; verify independently before acting. Product and company names are trademarks of their respective owners; mention does not imply endorsement.
Portfolio Reviews Get Sharper
The development matters for operators, founders and teams managing multiple projects because it addresses a common portfolio failure: initiatives that are no longer producing enough value but continue to consume time, maintenance and capital.
The framework’s stated emphasis is subtraction. Instead of asking what new project should be launched, it asks what existing work still earns its place. That framing could be useful for teams with limited capacity, especially where stalled work survives because no one wants to formally end it.
The source frames “kill” as the verdict the tool is designed to make easier to say. That is a claim about the framework’s purpose, not proof of its effectiveness. No adoption figures, case studies or independent evaluations were included in the provided material.
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Part Of The Decision Layer
Outcome-First Decisions is presented as the review component in a larger sequence described as “validate → plan → review.” The source says this closes the loop in the Decision Layer of the Thorsten Meyer AI operator portfolio.
The dispatch also links the framework to broader project principles: local-first operation, provider-agnostic reasoning and inspectable open-source release. The material says reviews run on owned compute, the reasoning is not tied to one model provider and the method is open for inspection under AGPL-3.0.
The source places Outcome-First Decisions within an 18-product “operator constellation,” alongside projects including IdeaNavigator, IdeaClyst, Threlmark and others. The provided material does not give usage data for those products or show how the new framework is being used across them.
“The hardest decision isn’t what to start — it’s what to stop.”
— Thorsten Meyer AI dispatch
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Adoption Details Are Missing
It is not yet clear how widely Outcome-First Decisions is being used, whether the GitHub repository includes a working product or only framework materials, or what inputs the system requires to generate its verdicts.
The source also does not provide performance benchmarks, examples from outside the author’s portfolio, or evidence that the framework improves decision quality. Its outputs are described as reasoning aids that may be wrong, and the material says users should verify independently before acting.
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GitHub Release Faces Scrutiny
The next test is whether users can inspect the AGPL-3.0 repository, understand the Worth Filter and apply the keep/change/kill review to real portfolios. Future dispatches in the 19-day series may also show how Outcome-First Decisions connects with the rest of the operator portfolio.
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Key Questions
What is Outcome-First Decisions?
It is an open-source framework from Thorsten Meyer AI that reviews initiatives and returns one of three verdicts: keep, change or kill.
What does the Worth Filter do?
The Worth Filter asks whether the current outcome of an initiative is worth the ongoing cost of keeping it alive.
Is this a final decision-making system?
No. The source describes the framework as decision support. Its verdicts may be wrong and should be checked before action is taken.
What license is used?
The source says Outcome-First Decisions is open source under the AGPL-3.0 license.
What remains unknown?
The provided material does not show adoption numbers, independent testing, detailed inputs or a public track record for the framework’s recommendations.
Source: Thorsten Meyer AI
