Efficiency

AI is one of the largest new items in the engineering budget, and its return depends on how much of that spend becomes shipped software. Without a fast, reliable build loop, agents churn on flaky failures, abandon tasks they cannot diagnose, or collide on merge — all of it billed, none of it landed. Context Engineering and its MCP Servers give agents the build context to fix what broke instead of guessing across repeated runs; Failure Handler diagnoses failures so agents self-correct rather than abandon; and Flaky Tests Detection stops them from chasing failures that were never real. Universal Cache, Predictive Test Selection, and Test Distribution shorten verification so changes merge before parallel agents collide, while Develocity Agents keep the toolchain healthy. Artifact Governance tracks which agent-authored changes reach production. See the full case on AI.

CI compute leaks three ways at once: work you've already done gets redone, builds that fail on a flaky test or a brittle toolchain get rerun, and the machines you pay for sit half-idle. Universal Cache reuses build outputs, dependencies, and toolchains so settled work isn't recomputed, and Predictive Test Selection runs only the tests a change touches. Flaky Tests Detection and Develocity Agents cut the flaky-test and toolchain failures that force reruns, so you don't pay twice to verify a change that was fine all along. And Performance Insights goes after a different kind of waste entirely — idle cores, disabled parallelization, an over-provisioned machine — with agents acting on it, not just charting it. Every lever reclaims the same budget: more delivery from the CI spend you already carry, not a bigger bill.

Every token an agent spends is a hard dollar, whether it lands a merge-ready change or just churns — and as you run more agents, that bill rises right along with the output. A significant share of that spend is waste: an agent reasoning over raw logs ingests tens of thousands of low-density lines, chases false paths, and re-runs builds to reproduce what the logs never captured. Build Scan® gives the agent a wide, queryable record to read the cause from, Context Engineering and MCP Servers bound what enters its context, Failure Handler investigates each systemic failure once so other agents skip it, and Flaky Tests Detection stops it debugging failures that were never real. The cost per shipped change falls and holds as you add agents, so output can grow faster than the bill.

Developer time is the most expensive capacity your delivery has, and much of it never reaches product work, draining into waiting on builds and tests, chasing failures the change never caused, and diagnosing what broke. Universal Cache and Predictive Test Selection cut the wait between change and trusted result, and Test Distribution fans the rest across a pool of agents, so engineers stay in flow. Flaky Tests Detection quarantines non-deterministic tests so they stop failing builds that were fine; when a build does break, Failure Handler takes a developer from it failed to the root cause over the build record, not a manual hunt across logs. Develocity Agents keep that loop fast as the codebase grows. The reclaimed hours come back as engineering capacity — including faster, more reliable delivery; see DORA.