Evidence-backed practices

Emerging Practices

Evidence-backed engineering practices emerging across public engineering organizations, shown with the use case, problem encountered, reported response, and Selection conditions behind each observation.

47Evidence
47Assessed
0Pending
165Observations
100%Coverage

Assessment coverage measures evidence records explicitly assessed for emerging practices. Assessed evidence may legitimately contain zero practice observations.

57 evidence-backed practice observations · coordination

CompanySpecific use case being solvedProblem encounteredReported practiceSelection condition
AnthropicAccept very high rates of concurrent changes without making every commit contend on global repository state.Packfile processing, locking, and shared-reference movement place unrelated work on the same coordination-critical path.Scion creates incremental server-side changesets without packfiles or locks and separates changeset creation from the small number of supported reference updates.coordinationeconomicsexecution
AnthropicMaintain human control when generated change volume makes uniform line-by-line review increasingly expensive.Agents can produce locally plausible code that violates system architecture, uses brute-force access paths, or over-engineers hypothetical concerns.Engineers review every change request with increasing emphasis on intent, architectural invariants, system-level tradeoffs, and rejecting invalid solution patterns.coordinationverification
AnthropicIntegrate hundreds or thousands of changes while tests execute against a rapidly advancing main branch.A globally locked merge queue serializes change and cannot keep pace when main advances substantially during each test run.Anthropic invests in post-merge and pre-deployment automated testing, accepts concurrent integration, and uses agents to repair resulting conflicts.coordinationexecutionverification
AnthropicObserve subtle operational behavior across independently scalable source-control components.Fixed alerts can miss novel or weak signals in component telemetry and logs.Anthropic assigns persistent superfan agents to individual components to inspect telemetry and logs alongside conventional alerting.coordinationobservability
AtlassianOperate agent access across many enterprise products and external AI clients.Distributed integrations make it difficult to enforce data policy, constrain connectivity, and reconstruct agent actions.Atlassian centralizes domain, permission-scope, IP, data-protection, and data-loss-prevention controls with organization-wide audit logging.coordinationobservabilityverification
AtlassianAllow agents and teammates to edit shared organizational documents concurrently.An agent can overwrite a teammate's newer change when it acts on stale document state.Atlassian uses version-aware, section-level edits that pause on concurrent changes and expose a preview before publication.coordinationobservabilityverification
AtlassianGovern a broad MCP surface containing read, write, and destructive operations.Treating all tool calls alike prevents clients and administrators from applying stronger controls to higher-impact actions.Atlassian separates read, write, and destructive actions, scopes access by toolset, and enables explicit confirmation for higher-risk operations.coordinationverification
GitHubAccept frequent concurrent pushes from developers, automation, and agent fleets.Coordinating every part of a push across durable replicas makes write latency and throughput depend on work that does not require global agreement.GitHub narrows synchronous coordination to the reference update while allowing object storage, connectivity validation, and secret scanning to proceed independently or in parallel.coordinationexecution
GitHubIncrease automated repository throughput while retaining organizational control.Higher agent activity can outrun governance if throughput replaces review, protection, auditability, or approval mechanisms.GitHub treats branch protection, required review, audit logs, repository visibility, and human approval as constraints the new architecture must preserve.coordinationobservabilityverification
Astekin et al.Decide whether an engineering task needs non-agentic, single-agent, or multi-agent execution.Selecting a complex agent architecture without a lightweight baseline can hide whether cooperation contributes any task-specific benefit.Evaluate an explicit ladder from direct model query through single-, dual-, and multi-agent configurations under matched task conditions.coordinationeconomicsverification
Astekin et al.Introduce multi-agent cooperation for a bounded software-engineering workflow.Additional agents impose systematic execution costs while accuracy gains vary by task.Begin with a lightweight task-aware baseline and adopt multi-agent workflows only when comparative evaluation demonstrates a benefit that justifies the added cost.coordinationeconomicsverification
CursorRespond to a suspected deployment regression with authority appropriate to organizational risk.A single remediation policy is either too passive for low-risk cases or too autonomous for consequential production changes.Configure the rollout bot to escalate to the author, pause progressive delivery, or prepare a revert pull request for human approval.coordinationexecutionverification
CursorDelegate work when fresh subagent context saves more than coordination costs.Isolated subagents can reduce inherited context but may duplicate work or pursue tasks invalidated by the parent's progress.Avoid blanket instructions to delegate exploration and constrain alternate-model selection to cases directed by the user or harness.contextcoordinationeconomics
Will LarsonGive an agent enough project state to reason beyond one assigned task.Goals, measures, work state, and implementation context held in private human knowledge cannot regulate an automated project loop.Represent goals and approach in a Notion RFC, measures in Datadog or Snowflake, and shared work state in a Linear project that the agent can audit.contextcoordinationobservability
Will LarsonAdvance a broad engineering goal across a changing set of tasks.A task-scoped agent cannot identify missing work, reconcile changed issue state, or choose the next non-blocked action.Review metrics and issues, create newly identified tasks, update state, execute non-blocked work, and select the next action from current project state.coordinationexecutionobservability
Will LarsonImplement one project across frontend, backend, infrastructure, and data repositories.Repository-scoped checkouts make coordinated cross-repository agent changes difficult to manage.Maintain about ten independent local workspaces, each with a checkout of every repository, and operate agents at workspace rather than repository scope.contextcoordinationexecution
CursorKeep long-running work active while still executing tests or operations that require a developer's machine.Laptop-bound execution limits duration and parallelism, while some tasks still require local state or hardware.Run the Project persistently on a cloud computer and let its coordinator start a local agent when machine-specific testing is needed.coordinationexecution
CursorDirect a feature, migration, or recurring maintenance program that outlives one agent session.A developer otherwise has to repeatedly plan work, start agents, relay context, and integrate results across a long-running body of work.Create a persistent Project whose coordinator plans and delegates while separate worker agents implement and test bounded tasks.coordinationexecution
OpenAIParallelize complex work across independent subproblems without implementing a custom coordination layer.Applications otherwise need to build and observe delegation, separate subagent contexts, parallel execution, and result aggregation themselves.Delegate independent work to parallel subagents with separate contexts while a main agent coordinates and combines their results.coordinationexecutionobservability
CursorCoordinate multi-day programs containing many stacked pull requests and subagents.Parallel work needs explicit ownership, bounded context transfer, durable state, and independent verification.pstack defines coordinator, optional sub-coordinator, worker, and verifier roles; structured state files; queue events; and worker briefs.contextcoordinationverification
CursorChoose whether a task should use multi-agent orchestration or a plain agent.Coordination ceremony can cost more than it saves on work small enough for one agent.The Orchestrate playbook says not to orchestrate when one agent can finish inside the task budget and uses a task-scale threshold for orchestration.coordinationeconomics
MetaConvert expert corrections into durable improvements to agent knowledge and reasoning.Manually tracing dependencies, editing interdependent files, and proving that a correction does not break existing behavior can take weeks.Diagnose feedback, compile minimal edits with parallel impact analysis, perform independent review and structural checks, then submit a validated pull request for expert approval.coordinationlearningverification
UberReduce the cost of high-volume agentic engineering work.Using an expensive primary model for every bounded subtask makes scaled execution more costly.A primary model decomposes and evaluates work while lower-cost subagents execute bounded tasks.coordinationeconomics
Destefanis and AsteDecompose a software change across agents with dependent outputs.Each contribution can be locally correct while a convention spanning two owners remains unresolved and causes the integrated system to fail.Identify cross-agent interfaces explicitly and assign one agent responsibility for validating each end-to-end contract.contextcoordinationverification
Destefanis and AsteUnderstand how a multi-agent coding run coordinates beneath its final output.Pass rates and aggregate tokens hide which agents communicated, which files carried shared state, when coordination happened, and where it failed.Represent agents and files as nodes and log messages, reads, and writes as timestamped, costed edges linked to the run's verified outcome.coordinationobservabilityverification
Destefanis and AsteChoose between direct messaging and persistent shared artifacts for an agent team.One-to-one messages repeat shared information, while mandatory files add overhead when the work already communicates through file interfaces.Measure the task's emergent coordination network and require shared files only where they replace message-heavy many-to-many traffic.contextcoordinationeconomics
Destefanis and AsteIntroduce a coordinator or orchestrator into a multi-agent workflow.Naming an agent as coordinator in its prompt may create no hub, authority, routing behavior, or reliable outcome improvement.Inspect the interaction graph and comparative outcomes to verify that the proposed coordinator actually performs a structural integration role.coordinationobservabilityverification
CloudflareLet sites identify and selectively admit legitimate agents.Sites cannot reliably make policy decisions when machine actors are indistinguishable, spoofed, or treated as generic bots.Cloudflare presents Web Bot Auth and PACT as cryptographic identity and delegated trust mechanisms for agents.coordinationexecution
CloudflareLet agents compensate resource owners directly for content, APIs, or excess resource consumption.Advertising and seat-based business models do not map cleanly to software actors that consume resources without rendering human interfaces.Cloudflare presents x402-compatible payments, agent wallets, monetization gateways, and receipts as transaction rails for agent interactions.coordinationeconomicsobservability
CloudflareLet agents perform actions on websites without reverse-engineering the DOM.DOM parsing, guessed form fields, and synthesized clicks are brittle interfaces for machine actors.WebMCP lets sites register explicit tools and schemas that agents can invoke using the user's existing session and state.coordinationexecutionobservability
CursorIntegrate changes produced simultaneously by many agents.Conventional merge behavior accumulated more than 70,000 conflicts in an earlier run.Cursor uses neutral third-party agents for merge conflicts and a purpose-built version-control system at higher commit throughput.coordinationexecution
CursorCoordinate hundreds of agents building a substantial software system concurrently.Homogeneous agents make conflicting architectural decisions and spend context on both global planning and local implementation.Cursor separates planner agents that decompose and delegate goals from worker agents that execute bounded pieces.contextcoordination
CursorKeep independently produced implementation decisions coherent across a swarm.Workers can make locally reasonable but globally incompatible design decisions.Cursor uses reconciler agents to resolve conflicting design decisions.coordination
CursorReview large volumes of concurrently agent-produced code.A single review mechanism can become a verification bottleneck as swarm output grows.Cursor uses stacked review agents with different review lenses.coordinationverification
StripeAllow coding agents to provision and configure infrastructure without exposing production by default.An agent that goes off-script can create direct production impact if credentials and environment access are too broad.Use named environments with isolated credentials and default agents to the development environment rather than production.coordinationexecution
StripeMove from code generation to runnable software without requiring a human to configure each provider dashboard.Provisioning infrastructure, connecting services, and managing credentials remain adjacent bottlenecks even when an agent can write the application code.Expose infrastructure provisioning through a structured agent skill or embedded CLI and connect it to multiple providers through delegated, scoped authority.contextcoordinationexecution
SpotifyCoordinate agent-generated migrations across thousands of repositories while directing scarce human attention.At fleet scale, teams need to know which changes were created or merged and which require human intervention.Fleetshift schedules and orchestrates Honk changes and tracks migration progress, pull-request state, and changes needing human attention.coordinationobservability
OpenAIRun more concurrent Codex coding tasks than an engineer can comfortably supervise as separate sessions.Engineers lost track of work and debugged stalled agents beyond roughly three to five simultaneous sessions.Symphony moves task assignment and workspace lifecycle into an always-on orchestrator where open tasks receive agents in isolated workspaces and humans review outcomes.coordinationexecutionobservabilityverification
CursorExecute multiple parts of an engineering task concurrently.Parallel agent work needs decomposition, isolation, and dependency-aware composition to avoid interfering changes.Cursor Multitask decomposes work into asynchronous subagents, uses worktrees to isolate concurrent changes, and parallel plans to preserve task dependencies.coordinationexecution
SpotifyApply a dataset migration across thousands of downstream consumers.Repository-scale changes need coordinated scheduling and pull-request execution across a large fleet.Spotify combines Honk, Backstage, Codesearch, and Fleet Management to target and orchestrate the migration.coordinationexecution
CloudflareProvide many engineering clients and agents with governed access to models and internal capabilities.Direct client-to-model integrations make attribution, permissions, model changes and cost control difficult to manage consistently at organizational scale.Route AI clients through a shared proxy Worker and AI Gateway so identity, permissions, model catalog configuration, usage attribution and routing can be changed centrally.coordinationeconomicsexecutionobservability
CloudflareIncrease the chance that agent-generated changes already fit repository and organizational constraints before human review.Agent outputs remain plausible but locally wrong when context acquisition, execution and standards enforcement are disconnected.Wire Backstage context, repository AGENTS.md, centralized tools and Codex-backed AI review into one engineering path; Cloudflare reports that the resulting first draft is now usually close enough to ship.contextcoordinationeconomicsexecutionlearningobservabilityverification
CloudflareReview every merge request on a standard CI path without applying the same review cost and expertise to every change.Uniform generic review does not match the risk profile or expertise required by different engineering changes.Classify merge requests by risk tier and delegate review to specialized agents for code quality, security, standards compliance, documentation, performance and release impact.coordinationeconomicsverification
CloudflareDelegate a bounded task without sharing the parent's entire context and mutable state.Subagents need independent context and tools while the parent still needs a defined mechanism for delegation and result collection.Create isolated child agents with their own state, model, memory, and tools, connected to the parent through typed streaming RPC.contextcoordinationexecution
MetaCreate structured AI-readable repository knowledge across a large multi-repository system.Manually documenting thousands of files and hidden engineering conventions does not scale.Orchestrate specialized explorer, analyst, writer, critic, fixer, tester, and gap-filling agent roles to pre-compute repository context.contextcoordination
Dae-Kyoo KimDesign agent boundaries for tasks that depend on information accumulated across a development phase.Overly narrow task boundaries can discard useful continuity between related activities.Use phase-level specialization where contextual continuity across related tasks improves artifact validity, such as operation identification or test design in the study.contextcoordination
Dae-Kyoo KimChoose how narrowly to specialize agents across a software-development workflow.Increasing role specialization does not consistently improve artifact validity across all engineering tasks.Compare task-specialized, phase-specialized, and process-generalist configurations and choose specialization granularity according to the task rather than assuming narrower roles are universally better.coordinationlearningverification
Shafin et al.Generate complete classes through a structured multi-agent software-development process.Direct code generation does not separate requirements, design, implementation, and verification responsibilities, making it difficult to study how process structure changes outcomes.Assign Requirement Engineer, Architect, Developer, and Tester agents distinct responsibilities and pass artifacts sequentially between them with feedback-based refinement.contextcoordination
Shafin et al.Use verification results to refine generated implementation code before the workflow finishes.Generated implementations can fail executable tests even after requirements and design stages have completed.Have a Tester agent create and execute tests, emit a test report, and allow the Developer agent up to three bug-fix cycles from that feedback.coordinationexecutionverification
SpotifyExecute software migrations across a large repository fleet with a background coding agent.Deterministic transformation declarations do not cover every migration, while repository targeting, pull-request lifecycle, review, and production merging still need coordinated infrastructure.Spotify retained Fleet Management for repository targeting and pull-request lifecycle while replacing transformation declarations with natural-language instructions executed by a coding agent.coordinationexecution
SpotifyTurn developer requests from Slack or GitHub into background coding work.The background coding agent needs sufficient task information before it can independently produce a pull request.An interactive agent gathers task information and hands a resulting prompt to the background coding agent.contextcoordination
Yin et al.Decide whether richer multi-agent orchestration is worth its operational complexity.Additional roles and coordination loops can increase reasoning steps, corrections, latency, and resource consumption without a proportional outcome gain.Measure trajectory length and correction behavior alongside effectiveness so coordination overhead is visible when comparing agent architectures.coordinationeconomicsexecution
Yin et al.Choose between lightweight and more elaborate agent orchestration for a software-engineering task.Agent quantity is an unreliable proxy for execution quality or efficiency.Compare reasoning depth, coordination strategy, feedback integration, effectiveness, and cost instead of assuming that adding agents improves the workflow.coordinationeconomicslearning
Google CloudMigrate tens of thousands of applications when direct coordination with every application owner is impractical.The coordination cost of scheduling and executing owner-by-owner migrations becomes prohibitive at warehouse scale.Use programmatic change generation, automated verification and rollout systems, and AI repair agents to minimize required application-team involvement, escalating difficult cases to owners.coordinationeconomicsexecution
Google CloudSeparate repair strategies for build failures and test failures while preserving one migration workflow.Build and test failures require different repair loops, and a test repair may itself encounter a build failure.Use an outer orchestrator that repeatedly calls specialized build-fixer and test-fixer agents, with the test-fixer able to invoke the build-fixer as needed.coordinationexecutionverification
CursorKeep humans in control of remotely executing coding-agent tasks.A long-running remote task needs supervision and a way to recover when the agent needs correction or human intervention.Expose per-agent status and allow the user to send follow-up instructions or take over execution at any point.coordinationobservability
CursorExecute several software-engineering tasks without serially occupying one foreground coding session.A single interactive agent session limits how much independent engineering work can proceed at once.Run multiple coding agents in parallel, with each agent operating in its own remote environment.coordinationexecution