TL;DR: Engineering OKRs fail for two reasons: they're either too granular (story points, sprint velocity) or too vague ("improve the platform"). The sweet spot is quarterly outcomes that are specific enough to measure, big enough to matter, and owned by someone who can actually influence them. Here are 10 real examples.

Key Takeaways

• Story points are not Key Results. Velocity is a planning tool. It tells you how much work fits in a sprint. It doesn't tell you if the work made the product better.

• Good engineering OKRs connect to business outcomes. "Reduce p99 API latency from 840ms to 150ms" matters because it affects product experience and potentially conversion rates: make that connection explicit.

• Reliability and velocity are the two axes. Most engineering OKRs fall into one of these: is the system reliable? Is the team moving fast?

• Engineers are skeptical of management theater. The fastest way to kill OKR adoption in engineering is to set goals that are obviously designed to look good in a QBR rather than drive real improvement.

• OKRs should be set at the team/function level, not the sprint level. Sprint-level work goes in Linear or Jira. OKRs live one level above.

Why engineers distrust OKRs

Let's be honest about this. Engineering teams have often seen OKRs used as:

• A way to make management feel like they have visibility (they don't)

• A performance management wrapper for already-defined sprint work

• A quarterly ritual that has no effect on what the team actually works on

That distrust is earned. If your OKRs are just a slightly different format for the roadmap, they don't add any value. The value of OKRs comes from setting the outcome and letting the team figure out the best way to achieve it: not from rewriting the sprint backlog in OKR form.

The OKRs below are designed for teams that want to drive real systemic improvement, not check a box.

OKR examples: reliability and platform health

OKR 1: Make the system boring to operate

Objective: Achieve platform reliability that removes engineering from the incident response rotation KR1: Reduce p99 API latency from 840ms to under 150ms for the three highest-traffic endpoints KR2: Decrease mean time to detect (MTTD) from 18 minutes to under 3 minutes for P1 incidents KR3: Achieve 99.95% uptime for the core platform (current: 99.2%)

OKR 2: Get ahead of technical debt before it becomes a product problem

Objective: Eliminate the technical debt that's actively slowing feature delivery KR1: Reduce time-to-merge for new features in the core data pipeline from 8 days to under 2 days KR2: Decrease test suite runtime from 47 minutes to under 12 minutes KR3: Migrate 80% of legacy services off the deprecated authentication layer (currently 12 of 60 migrated)

OKR examples: developer velocity

OKR 3: Unblock engineers from shipping

Objective: Make shipping a feature feel fast and safe KR1: Increase deployment frequency from 2x/week to daily releases KR2: Reduce rollback rate from 11% of deployments to under 2% KR3: Cut time from "PR opened" to "merged and deployed" from 4.5 days to under 6 hours for 80% of PRs

OKR 4: Reduce the invisible tax on engineering time

Objective: Give engineers back the time currently spent on operational overhead KR1: Reduce time spent per engineer on incident response from 6 hours/week to under 1.5 hours KR2: Automate 90% of routine deployment checks that currently require manual verification KR3: Reduce "where's the runbook for X?" Slack questions to the platform team by 70%

OKR examples: product delivery

OKR 5: Ship what we promise

Objective: Make engineering delivery predictable enough that product can make reliable commitments to customers KR1: Increase on-time delivery rate for committed roadmap items from 41% to 78% KR2: Reduce mid-sprint scope changes from an average of 4.2 per sprint to under 1 KR3: Deliver the Q3 roadmap milestones with a team post-mortem score of 4.0+ ("would you do it again this way?")

OKR examples: infrastructure and scale

OKR 6: Build infrastructure that scales with the business without linear headcount growth

Objective: Make the infrastructure layer invisible to product engineers KR1: Reduce infrastructure cost per processed event from $0.0042 to $0.0018 (cost-per-unit efficiency) KR2: Decrease provisioning time for new environments from 4 hours to under 15 minutes KR3: Achieve zero manual infrastructure changes needed for 10x usage spike events

OKR examples: security and compliance

OKR 7: Make security invisible to engineers but unbreakable to attackers

Objective: Achieve security compliance without adding friction to the development workflow KR1: Complete SOC 2 Type II audit with zero critical findings KR2: Reduce average time to patch critical CVEs from 11 days to under 48 hours KR3: Achieve 100% of new code going through automated security scanning in CI/CD (currently 34%)

OKR examples: team health

OKR 8: Build a team that doesn't burn out shipping fast

Objective: Sustain high velocity without unsustainable on-call burden KR1: Reduce average weekly on-call interrupts per engineer from 8.3 to under 2 KR2: Achieve engineering team eNPS of 42+ (current: 28) in Q3 pulse survey KR3: No engineer works more than 2 weekend incident shifts per quarter

Bad engineering OKR examples

KR: "Complete all sprint commitments"This is a task list, not a Key Result. What outcome do completed sprints produce?
KR: "Improve code quality"Unmeasurable. "Reduce critical bug escape rate to production from 12/month to under 2/month" is measurable.
Objective: "Support product team with all feature requests"This is a job description, not a goal. What does success look like? What changes?
KR: "Achieve 95% sprint velocity"Velocity is a planning input. It tells you capacity. It doesn't measure whether you built the right thing or built it well.

How Goal Agents pull from engineering tools

The real advantage of automated OKR tracking for engineering is that the data already exists: in GitHub commit history, Linear issue closure, Jira sprint completion, deployment logs. Nobody has to fill out a check-in form.

Brev's Goal Agents connect to GitHub, Linear, and Jira. Deployment frequency, PR cycle time, issue closure rate: these update automatically. The VP Engineering walks into the QBR with current metrics, not a spreadsheet assembled on the morning of the review.

FAQ

How do you keep OKRs from conflicting with sprint planning? They operate at different altitudes. Sprint planning is about what gets done this week. OKRs are about what changes this quarter. The best engineering leaders use OKRs to set the direction and trust the team to figure out the sprint-level execution.

Should individual engineers have OKRs? Generally no. Individual engineers have sprint commitments and career development goals. OKRs are for the team or function level. The exception: senior ICs or TLs working on a specific high-priority initiative.

What's the right number of OKRs for an engineering team? 3–4. More than that and the team is trying to move in too many directions simultaneously. Engineering has high coordination costs: focus compounds.

How do you handle OKRs that depend on another team? Name the dependency explicitly and agree on a commitment from the other team before the OKR is finalized. An OKR that depends on another team's work and doesn't have that commitment is not an OKR: it's a wish.

See also

• OKR check-in template: the weekly format that actually works

• VP of Operations tools: the 2026 stack

Written by Chris Pitchford, Co-founder of Brev | Former VP Sales, Ally.io (acquired by Microsoft as Viva Goals)