TL;DR
Thorsten Meyer AI has published Outcome-First Decisions, an open-source framework that reviews initiatives by current outcomes and ongoing cost. The framework returns one of three verdicts: keep, change, or kill. Its central claim is that ending low-return work can free capacity for better uses.
Thorsten Meyer AI has published Outcome-First Decisions, an open-source decision framework designed to help operators decide whether existing initiatives should be kept, changed, or killed, a problem the project frames as central to managing a portfolio without letting low-return work consume capacity.
The framework, described in the source material as part of the Built in Public series, uses what it calls the Worth Filter. That filter asks whether the outcome an initiative is producing now is worth the cost of continuing it, rather than weighing sunk cost, effort already spent, or organizational attachment.
Outcome-First Decisions produces three possible verdicts. Keep means the outcome justifies the ongoing cost. Change means the work may still have value, but its current form is not working and should be deliberately altered. Kill means the outcome does not justify the cost and the work should end so attention, maintenance time, and capital can be redirected.
The source material says the project is open source under the AGPL-3.0 license and is available on GitHub. It also describes the framework as local-first and provider-agnostic, meaning reviews are intended to run on owned compute and not depend on a single model provider. The project is presented as decision support, not as an automated decision-maker.
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 announcement matters for operators, founders, and teams managing multiple projects because it targets a recurring portfolio problem: work that is no longer producing enough value but remains active because no one has made a clear stop decision. The framework treats that continuation cost as a drain on focus and capital.
By making kill an explicit verdict rather than an implied failure, Outcome-First Decisions attempts to make stopping work a normal part of portfolio management. That could help teams separate evidence about current outcomes from emotional pressure tied to past effort.
The impact will depend on how honestly teams supply inputs and whether they are willing to act on the verdicts. The source material cautions that the framework’s output may be wrong and should be independently checked before action is taken.
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Part Of A Decision Layer
The source places Outcome-First Decisions inside a broader operator portfolio described as 18 products built on a local-first, provider-agnostic foundation. It identifies the framework as the review component in a decision sequence that also includes validation and planning.
The dispatch frames the new release as Day 8 of 19 in the Built in Public series. It says the decision layer is now complete with a loop of validate, plan, and review. Outcome-First Decisions is positioned as the part that closes that loop by reviewing whether existing work still earns its place.
The relevant background is the source’s claim that many portfolios carry a long tail of projects that are neither succeeding nor being ended. The framework responds to that pattern by focusing only on forward-looking outcomes and ongoing costs.
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Adoption And Accuracy Unknown
It is not yet clear how widely Outcome-First Decisions is being used, how the GitHub repository is structured, or what evidence exists that the framework improves portfolio outcomes in practice. The source material does not provide user numbers, benchmark results, case studies, or independent validation.
It is also unclear how the framework weighs different types of cost, such as engineering maintenance, opportunity cost, reputation risk, revenue loss, or team morale. The source describes the verdicts and operating thesis, but not a detailed scoring method in the provided material.
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Repository Review Comes Next
The next step for readers is to inspect the GitHub repository, license terms, and any available documentation before adopting the framework. Teams considering it will need to define the inputs they trust, decide who can issue a keep, change, or kill verdict, and test whether the review process changes real portfolio decisions.
The Built in Public series is also expected to continue beyond Day 8, according to the source’s 19-day framing. Further posts may clarify how Outcome-First Decisions connects with the other products and review workflows in the operator portfolio.
Evidence-Guided Practice
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Key Questions
What is Outcome-First Decisions?
Outcome-First Decisions is an open-source framework from Thorsten Meyer AI for reviewing active initiatives and assigning one of three verdicts: keep, change, or kill.
What does the Worth Filter do?
The Worth Filter asks whether the current or expected outcome of an initiative is worth the ongoing cost of continuing it. The source says it excludes sunk cost, past effort, and identity-based attachment from the decision.
Is the framework meant to make decisions automatically?
No. The source describes the verdicts as reasoning aids and says users should verify independently before acting.
What license applies to the project?
The source material says Outcome-First Decisions is open source under the AGPL-3.0 license and provided without warranty.
Source: Thorsten Meyer AI
