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

TL;DR

Outcome-First is a decision framework that guides organizations to evaluate projects by their current outcomes, recommending whether to keep, change, or kill them. It emphasizes pruning to improve overall portfolio health.

A new decision-making framework called Outcome-First is gaining attention for its approach to portfolio management, emphasizing the importance of stopping initiatives that no longer produce valuable outcomes. Developed as an open-source tool, it guides organizations to evaluate projects based solely on current results, rather than past investments or effort.

Outcome-First is designed to address the common problem of organizations maintaining a long tail of ongoing projects that neither succeed nor are actively terminated. The framework introduces the Worth Filter, a mechanism that prompts decision-makers to assess whether the current outcomes justify ongoing costs. The three possible verdicts are: keep, change, or kill. The framework is provider-agnostic and runs locally, making it accessible and flexible for various organizational setups. Its primary goal is to enable disciplined pruning, freeing capacity and resources trapped in projects that no longer add value. The framework is open source under the AGPL-3.0 license, encouraging transparency and collaborative improvement.

By focusing on outcomes rather than effort or sunk costs, Outcome-First aims to shift organizational culture toward more honest and effective portfolio management. It is positioned as the final step in a decision cycle: after ideation and planning, it reviews ongoing initiatives to determine if they should continue, be modified, or be terminated. This process helps prevent the accumulation of dead projects that drain focus and resources without delivering meaningful results.

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 Transforms Portfolio Management

This framework matters because it addresses a fundamental challenge faced by organizations: the tendency to keep underperforming initiatives alive due to emotional attachment, sunk costs, or inertia. By formalizing a discipline of outcome-based evaluation, it encourages more disciplined pruning, which can lead to increased efficiency, better resource allocation, and a healthier project portfolio. The open-source nature ensures transparency and adaptability, potentially influencing industry standards for decision-making processes.

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project portfolio management software

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The Need for Better Project Termination Methods

Many organizations struggle with the ‘long tail’ of projects that persist despite diminishing returns. Traditional decision-making often relies on backward-looking metrics like effort invested or effort remaining, which can bias toward continuation. The Outcome-First framework builds on existing ideas about outcome-based evaluation, emphasizing current results to guide decisions. Its development responds to the widespread challenge of avoiding premature or unnecessary project termination, which can be costly but is often avoided due to emotional or political reasons.

“Outcome-First makes the hardest decision in any portfolio straightforward: should it still exist? It removes the excuses and biases that keep dead projects alive.”

— Thorsten Meyer, creator of the framework

Amazon

decision-making framework tools

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Limitations and Risks of Outcome-First Evaluation

It remains unclear how organizations will accurately measure outcomes, especially for slow-start or long-term initiatives. There is also concern that the framework’s bias toward killing could lead to premature termination of projects with slow but valuable progress. Additionally, the framework cannot replace the emotional and political factors influencing decision-making, which may still hinder honest evaluations.

Amazon

outcome-based 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 are encouraged to pilot the framework within their portfolios, adapting it to their specific metrics and contexts. Further development may include integrating outcome measurement tools and case studies to refine decision criteria. Community feedback and collaborative improvements on GitHub will likely shape its evolution, aiming for broader adoption and effectiveness.

Amazon

portfolio pruning software

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Key Questions

How does Outcome-First differ from traditional project evaluation?

It focuses solely on current outcomes and whether they justify ongoing costs, rather than past investments or effort spent.

Can organizations customize the outcome metrics used in the framework?

Yes, since it is provider-agnostic and runs locally, organizations can tailor metrics to their specific goals and contexts.

Is the framework suitable for all types of initiatives?

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

What are the main challenges in implementing Outcome-First?

Accurate outcome measurement, overcoming emotional biases, and ensuring commitment to honest evaluation are key challenges.

Source: ThorstenMeyerAI.com

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