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Cited from real sources 6 min read Updated July 2026

A decision framework by Annie Duke

Annie Duke's Kill Criteria: How to Decide When to Quit a Project

Kill criteria are the specific conditions under which you have agreed, in advance, to stop or pivot. Annie Duke, decision strategist and author of Thinking in Bets and Quit, found that running a premortem on its own rarely changes anyone's plan. Its real job is to surface the signals you would see if this failed, so you can attach an action to each one while you are still capable of thinking clearly about it.

The real use of a premortem

"what a premortem allows you to do is to set up kill criteria"

Not a better plan. A named list of signals, each one wired to an action you committed to before you cared about the answer.

Annie Duke on Lenny's Podcast This will make you a better decision maker Watch at 65:59

The framework

The premortem is not the deliverable

Most teams treat a premortem as a planning exercise. Imagine the project failed, list the reasons, feel appropriately sober, then go build the thing you were always going to build. Duke's observation is that this is roughly what happens: run a premortem and people generally do not change their plan much. The insight evaporates, because nothing forces it to survive contact with a decision.

Her reframe is to treat it as a signal generator. The output you want is not a revised plan, it is a list of things you would observe on the way down. Each becomes a kill criterion: a measurable condition meaning stop or pivot, written while you have no stake in the answer.

It has to be structural, not intentional, because once you launch the biases pointing at continue outrun your resolve. Sunk cost is the loudest. Duke's inversion: waste is forward-looking. What you already spent is gone either way; the real waste is the next six months poured into something you know is dead.

things go on way too long even like they're over budget and you've blown the timeline and when you finally shut it down you realize you should have done it a lot earlier
Duke on how slow teams are to quit after launch Watch at 66:21

So the framework is not think harder about risk. It is convert the risk you already imagined into named signals, and pre-commit to what you will do when each one appears.

How to apply it

How do you set kill criteria that actually fire?

Seven moves, drawn from how Duke runs the exercise and from the failure modes she names.

  1. 1

    Run the premortem as a signal hunt, not a plan review.

    Prompt the team with a dead future: it is six months from now and this failed. Ask what early signals they saw, not what they would change.

  2. 2

    Have people write independently before anyone talks.

    Duke uses nominal group technique for this. Opinions gathered in the room produce conformity, and the quietest useful signal never gets said.

  3. 3

    Convert each signal into a measurable condition.

    Not 'if traction is weak' but a metric and a date. Vague criteria are the most common reason the exercise does nothing.

  4. 4

    Attach an action to every criterion.

    A threshold with no committed response is a discussion. Decide now whether hitting it means kill, pivot, or a specific test that resolves it.

  5. 5

    Instrument the leading indicators.

    If nobody can see the signal in real time, it will not fire. Wire criteria to something you already watch, or the trigger arrives as hindsight.

  6. 6

    Hold quit reviews on a fixed cadence, separate from ops.

    Inside a status meeting, optimism bias dominates and every miss gets explained away. The review needs its own slot and its own question.

  7. 7

    Honor the pre-commitment when it triggers.

    The predictable failure is renegotiating at the moment the criteria fire. Duke's warning: quitting on time will almost always feel like quitting too early.

A worked example

Duke describes running this with a sales team. Every rep got the same prompt: you won a lead through an RFP, worked it six months, and the deal is now dead. Looking back, what were the early signals? The list was long. Three became kill criteria, each with an action attached.

  • The RFP was clearly written with a competitor in mind. Action: ask them directly whether they are working with that competitor and how far along it is. Kill or proceed on the answer.
  • The customer will not take a demo and only wants to talk about price. Action: kill it. The team decided this pattern means they are a box being checked so someone else can be beaten down on price.
  • No decision maker in the room after the first few meetings. Action: offer executive alignment at the next meeting. If the answer is no, kill it.

Note what this does for the rep. Walking away normally invites the question of why you stopped pursuing the deal. A pre-agreed criterion turns that from a judgment call into a policy the team already signed off on.

Boundary conditions

When it works, when it fails

Works best when

  • The commitment is long enough that sunk cost will accumulate before you get proof either way
  • You can name leading indicators, not only the final outcome you are waiting on
  • You set them before launch, while nobody's identity is attached to the answer
  • Someone other than the project owner is in the room when the criteria are reviewed

Fails when

  • The criteria are too vague to be actionable, which is the most common version of the mistake
  • Quit reviews happen inside the standard operating meeting, where optimism bias wins
  • The criteria get renegotiated at the exact moment they are about to trigger
  • Nothing is instrumented, so the signal only becomes visible in the postmortem

Knowing about a bias does not protect you from it. Duke treats sunk cost like a visual illusion: you can explain it, demonstrate it, understand it completely, and still fall for it. Only a constraint built earlier, before the temptation was in the room, changes what you do.

instead of just kind of hoping that when I see those signals I actually act rationally which is a hope that it will not come true
Duke on why intention is not a plan Watch at 69:22

Where operators disagree

Duke locates the problem in the individual: resulting, motivated reasoning, and hindsight bias drive decision errors, so you fix decisions by fixing personal process. The systems thinkers disagree about where the leverage sits. Donella Meadows and Peter Senge argue behavior is produced by structure, feedback loops, incentives, and delays, so blaming individual judgment misses the cause. Cassie Kozyrkov sits closer to Duke: decision hygiene, set criteria before you see the data.

Both levels operate at once. Kill criteria are a personal-process intervention that works best when the structure backs it: a review cadence that exists on the calendar, and incentives that do not punish the rep who walked away from a dead deal.

Kill criteria pair with the frameworks that generate the signal. Sean Ellis's 40 percent product-market fit test is a ready-made threshold you can commit to before you run it. Garry Tan's launch-the-jankiest-version rule is the other half: ship early enough that the signal arrives while quitting is still cheap.

The sources

Where Duke discusses this

65:59
Timestamp

Lenny's Podcast · This will make you a better decision maker

Why a premortem exists: setting up kill criteria

Duke reframes the premortem's real purpose as generating kill criteria, the signals that mean it is time to pivot or stop.
67:57
Timestamp

Lenny's Podcast · This will make you a better decision maker

The sales-team example, three criteria with actions

An RFP written with a competitor in mind, a customer who only discusses price, no decision maker in the room, each wired to an action.
32:00
Timestamp

Lenny's Podcast · This will make you a better decision maker

The Illusion of Long Feedback Loops

Challenging the notion of long feedback loops, Duke argues that decision-makers can actively shorten them by identifying and tracking predictive signals.
40:00
Timestamp

Lenny's Podcast · This will make you a better decision maker

The Difficulty of Quitting and Learning from Failure

Duke discusses the psychological biases that make quitting difficult, such as sunk cost fallacy and identity protection.

Useful? Pass it to a founder six months into something they already know is dead.

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