Outcome-First Decisions: Keep, Change, or Kill

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

TL;DR

Outcome-First Decisions introduce a framework that emphasizes evaluating ongoing projects based on current outcomes rather than past investments. It aims to improve portfolio management by making stopping decisions clearer and more deliberate.

A new decision framework called Outcome-First Decisions is gaining attention for its focus on evaluating ongoing initiatives solely based on current outcomes, helping organizations decide whether to keep, modify, or end projects.

Outcome-First Decisions is a framework designed to address the common problem of organizations continuing projects that no longer produce valuable results. It introduces the Worth Filter, a mechanism that forces decision-makers to judge initiatives by their current outcomes rather than past investments or emotional attachments. The framework offers three verdicts: keep, change, or kill, with a bias toward making kill decisions easier to articulate. It is open-source under the AGPL-3.0 license and emphasizes local, provider-agnostic implementation, allowing frequent review without significant cost. The approach aims to improve portfolio health by systematically removing underperforming or obsolete projects, freeing resources for more productive efforts.
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 Impact Organizational Efficiency

This framework matters because it addresses a persistent challenge in portfolio management: the tendency to continue projects due to sunk costs, identity, or effort justification. By focusing on current outcomes, organizations can more effectively prune their portfolios, reduce hidden costs associated with maintaining dead projects, and allocate resources more strategically. Implementing Outcome-First Decisions could lead to more agile, focused organizations capable of adapting quickly to changing conditions, ultimately improving overall performance and innovation capacity.
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Background of Portfolio Management and Decision Challenges

Organizations often accumulate a long tail of ongoing projects that neither succeed nor are explicitly terminated, leading to hidden costs and resource drain. Traditional decision-making methods tend to be backward-looking, emphasizing past investments and effort, which can hinder effective pruning. Outcome-First Decisions was developed to provide a systematic, outcome-focused approach to address this issue, emphasizing the importance of regular, honest evaluations to maintain a healthy portfolio. The framework builds on recognized challenges in project and product management, advocating for routine ‘garbage collection’ of initiatives that no longer produce value.

“The hardest decision in any portfolio isn’t what to start. It’s what to stop. Outcome-First Decisions help make that decision clearer and more deliberate.”

— Thorsten Meyer, creator of the framework

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Uncertainties Around Implementation and Outcome Measurement

It is not yet clear how accurately organizations can measure and interpret outcomes, especially in complex or slow-developing initiatives. There is also concern that the framework’s bias toward killing could lead to premature termination of projects that might succeed over a longer horizon. Additionally, the effectiveness of the Worth Filter depends heavily on the quality of outcome metrics, which can be subjective or gamed. How organizations will adapt this framework to different contexts remains to be seen.

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Next Steps for Adoption and Testing of the Framework

Organizations interested in Outcome-First Decisions are expected to pilot the framework within their portfolios, adjusting the Worth Filter metrics to suit their specific goals. Further development and case studies are anticipated to refine best practices and demonstrate the framework’s impact on portfolio health. Ongoing community feedback and open-source collaboration will likely shape future iterations, with wider adoption contingent on proven effectiveness in diverse organizational settings.

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Key Questions

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

It emphasizes evaluating ongoing initiatives based solely on current outcomes rather than past investments or effort, enabling more deliberate pruning of projects that no longer produce value.

What is the Worth Filter and how does it influence decisions?

The Worth Filter is a mechanism that forces decision-makers to judge projects by their current results, making it easier to justify killing initiatives that no longer justify their costs.

Can this framework prevent premature killing of promising projects?

The framework aims to mitigate this risk by emphasizing outcome measurement, but its effectiveness depends on accurate metrics and judgment calls by decision-makers.

Is Outcome-First Decisions suitable for all types of organizations?

While designed to be provider-agnostic and flexible, its success depends on the organization’s ability to measure outcomes objectively and adapt the framework to their context.

How can organizations start implementing this decision approach?

Organizations can begin by integrating regular outcome-based reviews into their portfolio management processes, using the open-source framework as a guide to systematically evaluate and prune initiatives.

Source: ThorstenMeyerAI.com

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