TL;DR

Thorsten Meyer AI has published Outcome-First Decisions, an AGPL-3.0 open-source framework for reviewing portfolio initiatives. The framework centers on a Worth Filter that judges current outcomes against ongoing cost, while leaving adoption, accuracy and real-world usage still unproven.

Thorsten Meyer AI has published Outcome-First Decisions, an AGPL-3.0 open-source framework meant to help operators decide whether to keep, change or kill portfolio initiatives based on current outcomes and ongoing cost, according to the project dispatch.

The source material confirms that the framework is open source, hosted on GitHub and licensed under AGPL-3.0. It is presented as part of ThorstenMeyerAI.com’s Built in Public series and tied to what the site calls the operator portfolio.

The core mechanism is the Worth Filter. The dispatch says it asks whether an initiative’s current and expected outcome is worth the cost of continuing, while excluding sunk cost, prior effort and identity as reasons to keep work alive.

The framework returns three verdicts: keep, change or kill. In Meyer’s description, keep means the outcome justifies continued cost, change means the underlying effort may still have value but needs a deliberate alteration, and kill means the initiative no longer earns the capacity it consumes.

Built in Public · Day 8 / 19 ThorstenMeyerAI.com · the operator portfolio
The Decision Layer · Day 08 Dispatch

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.

01 The Worth Filter
The Worth Filter
is the outcome worth the ongoing cost?
judged forward (outcome) — not backward. Ignored: sunk cost · effort spent · identity
✓ Keep
Affiliate cluster A
compounding revenue
Channel E
reach still growing
↻ Change
Product C
right problem, wrong shape
alter deliberately — don’t drift
✕ Kill
Experiment B
flat · high upkeep
Side project D
zero traction · sunk cost
3verdicts: keep · change · kill outcomesthe only input that counts AGPLopen source · local-first
02 Why stopping is the leverage
kill
the verdict everything in human nature avoids — made normal, not a failure.
forward
judge what it will produce next, not what you’ve already spent. Sunk cost is gone either way.
capacity
killing dead work reclaims the focus and capital trapped in it — the cheapest growth there is.
03 The thesis the whole series inherits
01
Local-first
Reviews run on owned compute — cheap enough to run as often as honesty requires.
02
Provider-agnostic
The reasoning isn’t welded to one model. Swap freely; no lock-in.
03
Non-developer build
A small, opinionated framework — AGPL-3.0, open so the method stays inspectable.
04
Edit by subtraction
The whole product is subtraction — killing what no longer earns its place.
04 The operator constellation
18 products · one foundation
Today: Outcome-First lit — the keep/change/kill review that closes the loop. The Decision layer is complete: validate → plan → review.
Content
DojoClaw
RoundupForge
Stenvrik
ChannelHelm
IdeaNavigator
Decision
IdeaClyst
Threlmark
Outcome-First
Platform
Grimfaste
Delvasta
Open / Reg
Glasspane
QAtrial
Markets
Polybot
TradingAgents
Defense / Intel
Argus
VigilSAR
VigilSAR-Bench
Diagnostic
World Model Readiness
Local-first · Provider-agnostic foundation

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.

ThorstenMeyerAI.com · Built in Public · Day 8 of 19 · © 2026 Thorsten Meyer

Portfolio Stops Get A Test

The release matters for operators, founders and small teams managing multiple projects because it formalizes a decision many organizations delay: ending work that no longer produces enough value. Meyer’s claim is that the cheapest available growth can come from reclaiming attention, maintenance time and capital from initiatives that should have ended.

That claim remains an interpretation from the project author, not an independently measured result. The practical value will depend on whether users apply the filter consistently, provide accurate inputs and accept negative verdicts when the framework recommends stopping work.

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Day Eight In The Series

Outcome-First Decisions appears as Day 8 of Meyer’s 19-part Built in Public series. The source material says the project follows a decision layer that now covers validate, plan and review, placing Outcome-First at the review stage.

The dispatch also places the framework inside a larger portfolio described as 18 products built on a local-first and provider-agnostic foundation. Those descriptions are the author’s positioning; the source material does not provide external adoption figures or third-party tests.

“The hardest decision in any portfolio isn’t what to start. It’s what to stop.”

— Thorsten Meyer AI dispatch

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Adoption And Accuracy Remain Open

It is not yet clear how many users have tested the framework, how the GitHub repository is structured, or whether the Worth Filter has been compared against other portfolio review methods. The source material does not include benchmarks, case studies or outside validation.

The project also says its verdicts may be wrong and should be verified independently before action. That means any recommendation to kill or change an initiative should be treated as decision support rather than an automatic operational call.

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GitHub Activity Becomes The Signal

The next measure of traction will likely come from the public repository: issues, pull requests, forks, documentation updates and examples of teams using the framework. Further posts in the Built in Public series may also show how Meyer connects Outcome-First Decisions to the broader operator portfolio.

Amazon

project kill or continue decision tools

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Key Questions

What is Outcome-First Decisions?

It is an open-source framework from Thorsten Meyer AI for reviewing initiatives and returning one of three verdicts: keep, change or kill.

What does the Worth Filter do?

It asks whether the outcome an initiative is producing now is worth the cost of continuing. The dispatch says sunk cost, past effort and identity are not counted as valid reasons to continue.

Is the framework open source?

Yes. The source material says Outcome-First Decisions is on GitHub and licensed under AGPL-3.0.

Does it make final decisions for users?

No. Meyer’s disclaimer describes the verdicts as decision support and says users should verify independently before acting.

What is still unknown?

Public adoption, independent testing, repository activity and real-world results are not established in the provided source material.

Source: Thorsten Meyer AI

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