📊 Full opportunity report: Outcome-First Decisions: Keep, Change, or Kill on ThorstenMeyerAI.com — validation score, market gap, and execution plan.

TL;DR

A new framework called Outcome-First Decisions emphasizes evaluating initiatives by their current outcomes to decide whether to keep, change, or kill them. It aims to improve portfolio management by prioritizing results over sunk costs.

The Outcome-First Decisions framework has been introduced as a method for organizations to evaluate ongoing initiatives based solely on their current outcomes, rather than past investments or emotional attachment. This approach aims to improve portfolio management by facilitating decisive actions—keep, change, or kill—based on whether the initiative’s current results justify its ongoing costs.

The framework, developed by Thorsten Meyer, centers around a decision tool called the Worth Filter, which prompts decision-makers to assess the current outcome of each initiative without considering sunk costs or effort justification. It produces three verdicts: keep, change, or kill. The goal is to prevent organizations from maintaining projects that are neither succeeding nor being actively terminated, which can drain resources and focus. The framework is open source under the AGPL-3.0 license, designed to run locally on owned infrastructure, and provider-agnostic, ensuring broad applicability. It emphasizes that the hardest decision—killing a project—is often avoided due to emotional or organizational biases, and the framework seeks to make such decisions more straightforward and justified.

While the framework aims to foster disciplined pruning, experts caution that outcome measurement can be biased or gamed, and premature killing of slow-start projects remains a risk. The framework does not supply judgment or emotional courage but provides a structured, transparent basis for decision-making.

Outcome-First Decisions — Keep, Change, or Kill · Built in Public Day 8/19
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

Why Outcome-First Decisions Reshape Portfolio Management

This framework addresses a common organizational challenge: maintaining a long tail of ongoing projects that neither succeed nor are actively terminated. By focusing on current outcomes, it encourages more disciplined resource allocation, freeing capacity for new or more promising initiatives. This approach can lead to increased efficiency, reduced waste, and better strategic focus, especially in organizations managing large portfolios of initiatives.

Amazon

portfolio management decision tools

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The Challenge of Continuing Ineffective Initiatives

Organizations often struggle with the tendency to keep projects alive due to sunk cost fallacy, organizational inertia, or emotional attachment. Traditional decision-making processes are biased toward continuation, leading to resource drain and opportunity costs. Thorsten Meyer’s framework builds on recent management theories emphasizing outcome-based evaluation and disciplined pruning, offering a structured way to address these issues. It aligns with ongoing trends toward more agile, results-oriented portfolio management practices.

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

— Thorsten Meyer

Amazon

outcome measurement software

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Limitations of Outcome Measurement and Emotional Bias

It remains unclear how effectively the framework can be applied across different organizational contexts, especially where outcome metrics are difficult to define or measure. There is also concern that the bias toward killing projects can lead to premature termination of slow-start initiatives that might have long-term value. The framework does not address how to balance emotional and strategic considerations, leaving room for subjective judgment.

Amazon

project evaluation framework

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As an affiliate, we earn on qualifying purchases.

Adoption, Testing, and Refinement of the Framework

Organizations interested in Outcome-First Decisions are expected to pilot the framework within their portfolios, adapting it to their specific context. Further case studies and empirical evaluations will clarify its effectiveness and limitations. The open-source nature of the tool allows for community-driven improvements and integration into existing portfolio management systems.

Amazon

resource allocation decision tools

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Key Questions

How does Outcome-First Decisions differ from traditional portfolio reviews?

It focuses solely on current outcomes rather than past investments or effort, promoting decisive action based on present results.

Can this framework help prevent premature killing of slow-start projects?

The framework encourages outcome-based evaluation, but it does not automatically account for long-term or slow-start initiatives, so judgment remains important.

Is the framework applicable to all types of organizations?

While designed to be provider-agnostic and flexible, its effectiveness depends on the organization’s ability to measure and interpret outcomes accurately.

What are the main risks of using Outcome-First Decisions?

Risks include outcome measurement bias, premature termination of valuable projects, and reliance on subjective judgment for complex decisions.

Will the framework be integrated into existing project management tools?

Its open-source design allows organizations to adapt and integrate it into their current systems, with community contributions expected to expand its capabilities.

Source: ThorstenMeyerAI.com

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