← Back to article

Equation 8 · Why Coding Agents Fail: Long-Horizon Reliability in OpenAI Codex

What does this equation mean?

R=Eg∼DEτ∼P(τ∣g)[V(sT,g)].R=\mathbb{E}_{g\sim D}\mathbb{E}_{\tau\sim P(\tau\mid g)} \left[V(s_T,g)\right].

Read the formula alongside the article passage below. Each part has a deeper page with its role in the equation, the supporting passage and nearby citations.

Inputs and operationsE_gsim DE_τsim P(τmid g) [V(s_T,g)]
Result or conditionR
How to read the two sides of this formula. Follow the article passage for the meaning of each quantity.

This equation states an equality: the expressions on both sides have the same value under the article’s assumptions. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.

Read it piece by piece

RR

Symbol R

System reliability under task distribution D.

Understand this part →

gg

Symbol g

g appears inside an expected value, so its contribution is averaged under the distribution or condition shown by that operator.

Understand this part →

DD

Symbol D

the system reliability under task distribution.

Understand this part →

τ\tau

Symbol τ

τ appears inside an expected value, so its contribution is averaged under the distribution or condition shown by that operator.

Understand this part →

PP

Symbol P

P appears inside an expected value, so its contribution is averaged under the distribution or condition shown by that operator.

Understand this part →

VV

Symbol V

V appears inside an expected value, so its contribution is averaged under the distribution or condition shown by that operator.

Understand this part →

sTs_T

Symbol s_T

sTs_T appears inside an expected value, so its contribution is averaged under the distribution or condition shown by that operator.

Understand this part →

=

=

The expressions on both sides represent the same quantity under the stated assumptions.

Understand this part →

See an illustrated explanation →
subscript

subscript

The lower label selects a particular version, component, or indexed member of the quantity. For example, x₀ and xₜ can be values at different positions.

Understand this part →

How to interpret it

Read it with the definitions, units, and assumptions supplied by the article.

What the article says around this equation

where sts_t is environmental state, oto_t the agent’s observation, and ata_t its action. Task success is not a property of the final message. It is an externally evaluated predicate V(sTs_T,g) over final state and goal g . System reliability under task distribution D is R=Eg∼DEτ∼P(τ∣g)[V(sT,g)]R=\mathbb{E}_{g\sim D}\mathbb{E}_{\tau\sim P(\tau\mid g)} \left[V(s_T,g)\right]. Every term matters. Change the task distribution, model, harness, tools, retry budget, permissions, environment, or evaluator and the reliability estimate changes.

Read the equation in its article →

Sources cited in the article section

These citations give research context. Read each source to check which claims it supports.

Return to Why Coding Agents Fail: Long-Horizon Reliability in OpenAI Codex

See this formula across 1 published context →

Browse the mathematical compendium →