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 is a framework that guides organizations to evaluate whether to keep, change, or kill initiatives based on current outcomes. It aims to improve portfolio management by emphasizing stopping unproductive projects.

A new decision-making framework called Outcome-First Decisions has been introduced to help organizations evaluate and prune their project portfolios based on current outcomes, rather than sunk costs or emotional attachment. This approach aims to address the persistent problem of organizations continuing unproductive initiatives, which can drain resources and hinder growth.

Outcome-First Decisions is a framework built around the core question: ‘What outcome is this initiative producing right now, and is that worth its ongoing cost?’ It employs a mechanism called the Worth Filter, which forces decision-makers to focus solely on forward-looking results rather than past investments or effort. The framework offers three verdicts: keep, change, or kill. It is open source under the AGPL-3.0 license and designed to be provider-agnostic and local-first, enabling frequent, cost-free reviews of ongoing projects.

The framework emphasizes the importance of pruning portfolios to free capacity for more valuable initiatives. It recognizes that emotional biases and sunk costs often prevent organizations from stopping unproductive projects, leading to inefficiencies and opportunity costs. By making kill decisions easier and more transparent, Outcome-First aims to institutionalize the discipline of stopping, which is often overlooked despite its high leverage.

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 matters because it addresses a common organizational flaw: the tendency to continue supporting projects that no longer produce value. By shifting the focus to current outcomes, it helps organizations eliminate waste, optimize resource allocation, and improve agility. It encourages a culture of honest evaluation and disciplined pruning, which can lead to faster innovation cycles and better strategic alignment. However, the approach also raises questions about how accurately outcomes are measured and whether emotional or strategic considerations might still influence decisions.

Amazon

project portfolio management software

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The Challenge of Stopping Unproductive Initiatives

Many organizations accumulate a long tail of ongoing projects and commitments that are neither succeeding nor being formally terminated. These ‘zombie’ initiatives consume attention, capital, and focus, often justified by sunk costs or organizational identity. Traditional decision-making processes tend to favor continuation over termination, leading to portfolio stagnation. The Outcome-First framework emerges as a response to this problem, offering a systematic way to evaluate ongoing initiatives based on their present results rather than past effort.

Earlier management practices emphasized starting new projects but lacked robust mechanisms for stopping them once they proved unproductive. The framework formalizes the discipline of pruning, which is critical for maintaining a healthy, dynamic portfolio capable of adapting to changing circumstances.

“Outcome-First Decisions is about making the hardest decision in any portfolio: what to stop, not what to start.”

— Thorsten Meyer

Amazon

decision-making framework tools

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As an affiliate, we earn on qualifying purchases.

Unresolved Questions About Implementation and Bias

It remains unclear how organizations will accurately measure outcomes, especially for slow-start or long-term projects. There is also concern about potential misuse or gaming of the system, which could lead to prematurely killing valuable initiatives. Additionally, the framework cannot address emotional or strategic considerations that may influence decision-makers’ willingness to stop projects, even when the data suggests doing so.

Amazon

outcome-focused project evaluation tools

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Next Steps for Adoption and Refinement

Organizations interested in Outcome-First Decisions are likely to pilot the framework in select portfolios, testing its effectiveness in real-world scenarios. Further development may include refining outcome metrics, integrating the framework into existing portfolio management tools, and establishing best practices for handling slow-start projects. As the framework gains traction, community feedback and case studies will shape its evolution.

Amazon

portfolio review software

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 emphasizes evaluating initiatives based on current outcomes rather than past investments or effort, making termination decisions clearer and more objective.

Can this framework be applied to all types of projects?

While designed to be provider-agnostic and flexible, its effectiveness depends on the ability to measure meaningful outcomes, which may vary across project types.

What are the risks of using Outcome-First Decisions?

Potential risks include mismeasuring outcomes, prematurely killing slow-start projects, or allowing emotional biases to influence decisions despite the framework’s intent.

Is the framework available for public use?

Yes, it is open source under the AGPL-3.0 license and can be implemented and adapted freely.

Source: ThorstenMeyerAI.com

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