IT交付应该如何适应以获得代理AI的好处

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TheAIfrontier:

WhereITdelivery

meetshumanoversight

Whenthepriceofbuildingsoftwarefalls,advantage

shiftstoknowingexactlywhattobuild,wheretoimposegovernance,andhowtomanagetheagenticworkforce

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Contents

Introduction—thebottleneckshiftsasworkmovesdownstream

3

1.Requirementsandintent—wheredoesvaluegowhencodeisfree?

6

2.Engineering—buildingreliableengineeringoperatingmodels

18

3.Deliveryandoperations—canagentsshipandoperatesoftwaresafely?28

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3

Introduction

AgenticAIcutsthecostofcodingbutdoesnotmeansoftwaredevelopmentcomescheap

DeployingagenticAIdoesn’tshortenthedeliverychain;itreshapesit.

Thebusinessmustdecidewhatitwantsmoreclearlyandmorequickly,

engineeringmustverifyaheavierloadofoutputwithoutlettingqualityslip,andoperationsmustidentifytheactionsthatagentsmaytakeinproduction,andunderwhatcontrols.Thispaperexploresthesethreeimperatives.

Exhibit1:Thebottleneckshiftsasworkmovesdownstream—clarity,thenverification,thencontrol

1INTENT

Requirementsandintent

3RUN

Deliveryandoperations

AGENTSTAKEON:

•Draftandenrichrequirements•Checktheporfolioforconflicts•Prototypeoptionsinhours

AGENTSTAKEON:

•Prepareapatch,rerunatest

•Restartaservice

•Propose,notpass,theproductiongate

WHATBECOMESSCARCE:Clarity

WHATBECOMESSCARCE:Control

HUMANSKEEP:

Thebusinesssignsofftheintent

HUMANSKEEP:

Productionpolicystaysgoverned

Theworkflowsdownstream–thebottleneckmoveswithit

2BUILD

Engineering

AGENTSTAKEON:

•Generatecodeandtests

•Runaself-verificationloop

•Handle~80%ofexecutiondecisions

WHATBECOMESSCARCE:Verification

HUMANSKEEP:

Engineeringenforcesthequalitybar

Autonomyfollowsverifiability.Measurehowmuchgoodworksurvivesfromintenttoproduction.

Source:OliverWymananalysis(schematic).Readslefttorightintheordertheworkflows;eachchapterofthisdocumenttakesonestage.

4

Thebottleneckshiftsasworkmovesdownstream

Foryears,softwaredeliverywasorganizedaroundascarceresourceinthemiddleoftheworkflowchain.Engineeringcapacitywasthebottleneck.Nowthathaschanged.Agentic

AImeanscodecanbeproducedmuchfaster,butthatdoesnotmeantherestofthechain

acceleratesinparallel.Instead,pressuremovesupstreamtoclarityofintentandworkmovesdownstreamtoverification,release,andoperationalcontrol.Thefollowingthreechaptersareorderedinthesamedirectionastheworkflows,reflectingtherealitythateachonecreatestheconditionsforthenext:

Chapter1—Requirementsandintentstartbeforealineofcodeiswritten.Whenproducing

softwarebecomeseasier,anunclearbriefbecomesmoreexpensive.Theriskisthatthewrongthingcannowbebuiltatspeed.Wearguefortreatingrequirementsasacollectionofmanagedassetsthatareclear,testable,versioned,andreconciledacrossteams,whilekeepingthefinaldecisionswiththebusiness.Thepracticalquestioniswhethertheorganizationcanstatewhatitwantsclearlyenough,anddecidequicklyenough,foragentstoact.

Chapter2—Engineeringisconcernedwiththebuilditself.ThisiswhereagenticAIis

mostvisible,andwhereitiseasiesttoconfusemoreoutputwithmorevalue.Asgeneration

accelerates,theprocessofreview,testing,anddomainjudgementbecomestheconstraint.Thechapterthereforeshiftsattentionawayfromcodevolumeandtowardverifiability.Thatmeansgivingagentsworkthatcanbecheckedreliably,makingqualitygatescontinuousandtoughtobypass,andmeasuringwhatactuallymakesitthroughthepipeline,ratherthanhowmuchcodeisproduced.

Chapter3—Deliveryandoperationsfacilitatethefinalstepintoproduction.Here,the

questionisnolongerwhetheranagentcanact,butwhatauthorityitshouldbegiven.The

chapterdrawsapracticalboundary.Contingentonthedeliverysystem,leaderscandelegate

local,reversibledata-planeactionssuchaspreparingapatch,rerunningatest,orrestartinga

servicetoAI.Meanwhile,theycanaskhumanstooverseeproductionpolicy,approvalgates,andothercontrol-planedecisions.Thisonlyworksiftheplatformmakeseveryactionobservable,

attributable,andreversible.

Whatconnectsthethreechapters

Thebottleneckmovesbutdoesnotdisappear.Fastergenerationreducesoneconstraint

butexposesthenext.Italsoremovesafilterthatpreviouslyoperatedforfree.Whenbuildingwasexpensive,thecostfactorprohibitedcreationoflow-valuefeatures.Nowthecostislower,restraintmustbedesignedin.Ifthatdoesn’thappen,softwaregrowsmorecomplex,more

costlytorun,andhardertouse.Underthenewmodel,thescarceresourcesbecomeclarityupstream,verificationinthemiddle,andcontroldownstream.Investmentshouldmove

withthem.

5

Autonomyshouldfollowverifiability.Thesameprincipleappliesateverystage,sothe

businesssignsoffonintent,engineeringenforcesthequalitybar,andhumanteamsgovernproductionpolicy.Agentsshouldbegivenmorefreedomwheretheirworkcanbecheckedquicklyandreversedsafely,butnotsimplywheretheyaretechnicallycapableofacting.

Measurethechain,nottheactivity.Codevolume,tooladoption,andperceivedspeedareweakproxiesforvalue.Whatmattersishowmuchgoodworksurvivesfromintenttoproduction,andwithqualityandstabilityintact.Inaddition,itisimportantthatsoftwareisactuallyusedonceitgetsthere.Theimperativeistoinstrumentthatflowandlettheevidencesetthepaceofrollout.

Howtoreadthisdocument

Onfirstreading,werecommendtakingthethreechaptersinorder.Thatmakessensebecauserequirementscreatethespecificationengineeringhastoverifyandengineeringcreates

thechangesthatdeliverymustreleaseandoperatesafely.Afterthat,eachchapterstands

onitsownasadecisionguide.Together,theyansweroneCIOquestion:whenagentsmake

productionfaster,whathastochangearoundtheworksothatspeedleadstoreliablesoftwareratherthanfasterreworkandrisk?

Exhibit2:Thebottleneckmovesdownstream,bythenumbers

Chapter1—Requirementsandintent

Canyoustatewhatyouwantclearlyenoughanddecidequicklyenough,foragentstoact?

15%

ofCIOscanroutinelyspotcontradictory

orincomplete

requirementswithinoneworkingday

74%

sayitwouldtakesignificanteffort

11%

couldnot

answeratall

Chapter2—Engineering

Doestheproductivitygainsurvivethetripfromcommittoproduction?

+240%

upliftincommitswithagenticcodingtools

+30%

upliftinshippedreleasesfromthesametools

27%

ofcode-generation

programssee

generationoutrunningreviewandtestcapacity

41%

ofCIOsestimatethat5%ormoreof

AI-assisteddefectsreachproduction

Chapter3—Deliveryandoperations

Canagentsshipandoperatesoftwaresafely,andcanyoureconstructwhattheydid?

10%

oforganizations

canlistevery

productionagent’sowner,scope,cost,andlastcertificationdateondemand

25%

haveatamper-

evidentaudittraillinkingeachactiontoitsapproval

30%

ofrespondentsreportlittleornotrustin

AI-generatedcode

Source:TheOliverWyman2026ParallelSurveysofCEOsandTechLeadersonAgenticAIandIT,July2026;Demirer,MusolffandYang,MITSloan,2026,forthecommit-to-releaseuplift;DORA,StateofAI-assistedSoftwareDevelopment2025,fortrustinAI-generatedcode.Figuresaspresentedinchapters1to3.

Requirementsandintent

Wherevaluegoeswhencodeisfree

1

INTENT

Requirements

andintent

Scarce:Clarity

2

BUILD

Engineering

Scarce:Verification

3

RUN

Deliveryandoperations

Scarce:Control

7

Whenbuildingthewrongthing

isfastandcheap,knowing

exactlywhatyouwantbecomes

thescarceresource.

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Needsandintention:wheredoesvaluegowhencodeisfree?

Whathaschanged

AIismakingitmucheasiertocodeworkingsoftware.Whatstillremainsdifficult,though,isdecidingwhattobuild—anddoingsopreciselyandquicklyenoughtokeepagentsmoving.

Whilecodeusedtobethepinchpoint,thatscarcityhasnowshiftedtoclear,consistentbriefs

aswellasthebackingofexecutivedecisionsmadequicklyenoughtoact.Thisonlybecomes

harderatalargecompany,wherehundredsofrequestscancomeinatanyonetimefrom

differentteamsincreasinglyusingAIinthedraftingprocess.ThoserequestscannotcontradictoneanotherandeachmustbecompleteenoughtopreventAIfrombuildingthewrongthingatspeed.Writingagoodbriefusedtobeacraft.Itnowhastobemanagedlikealivingproduct.

Exhibit3:Withagents,handoverscompressandcycletimeisreclaimed

Beforeagents:everystagerunsathumanspeed

PlanandDesignBuildTestDeploy

Afteragents:buildrunsatagentspeed

Deploy

Build

30%cycletimereclaimed

Test

PlanandDesign

Decidingwhatto

dobecomes

moreimportant

Build:becomes

largely

automated

Agentictestis

automatedbut

businessacceptance

becomescriticalpath

CoredeliverystepHandoverstep

Source:Anthropic,“TheAI-NativeSDLCplaybook,”August2026.

8

©OliverWyman

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9

Ourpointofview

CompaniesmustdevoterealinvestmentintousingAIandpropertoolstogetthebrief

right,ratherthanjustgeneratingcodemorequickly.Treatthebriefasalivingsource

oftruthcompletewithversionhistory:updaterequirementsacrossfunctions,reconcile

contradictions,andrecordhowkeydecisionsweremade.Keepfinalsign-offwiththe

business,andrebuildhowbusinessandITworktogetheraroundfrequent,well-run

decisions.ThevalueAIoffersincreasinglydependsonwhetherbusinessescandefinewhattheywantandmakethenecessarydecisionsquickly.Fastercodegenerationdoesnotfixunclearorconflictingrequirements.

Weareconfidentaboutthisdirection:theconstrainthasshiftedfrombuilding

softwaretodecidingwhattobuild.Wearemorecautiousaboutthetoolsthemselves.

Academicresearchshowsthatsoftwarecannowautomaticallycheckrequirementsfor

contradictions,butend-to-endtoolsformanagingthebriefarestillnascent,andthereisnotyetalarge-scale,independentmeasureofwhetherrequirementsaddressprojects’

overarchingobjectives.1

Exhibit4:CEOsseethegaininreengineeringthework,notinthetools

WhereCEOsbelievethegainsfromagenticAImainlycomefrom,%ofrespondents

Reengineeringhowtheworkisdone

andgoverningourdataRoughlyequal

61%34%4%

Buyinganddeployingthebesttoolsandmodels

Source:TheOliverWyman2026ParallelSurveysofCEOsandTechLeadersonAgenticAIandIT,July2026.

1A.Veizaga,S.Y.ShinandL.C.Briand,“AutomatedSmellDetectionandRecommendationinNaturalLanguageRequirements,”IEEETransactionsonSoftwareEngineering50(4),2024,pp.695–720

10

Apracticaltest.Askyourteamstoidentifywhichcurrentrequirementscontradictone

another,andwhichareincomplete.InourCIOsurveyof130respondents,only15%saidtheirorganizationcouldroutinelyanswerthatquestionwithinoneworkingday.Another74%saiditwouldtakesignificanteffort,and11%couldnotansweratall.Ifyourorganizationcannotprovideareliableanswerquickly,fixthatcapabilitybeforelettingAIbuildatscale.

Whathappenswhendecisionsfailtokeepupwithcoding?

AIisincreasingcode-generationcapacityfasterthanlargeorganizationscanreconcile

requirementsandmakedecisions.Fivechallengesmovethebottleneckupstream.Thefirsttwoconcernthequalityandcoherenceofintent.Thenexttworelatetoauthority,governance,anddecisionspeed.Thefifthconcernsthedisciplinetodecidewhatnottobuild:

Exhibit5:Cheapcodeamplifiesthebriefitisgiven

Coherentsoftware,

deliveredfaster;decisions

keptwiththebusiness

Aclear,current,governed

brief:goals,constraints,

definitions,andprior

decisionsmadeexplicit

Agentsgenerateatmachine

speedrequirements,

prototypes,andcode

draftedinhours

Agentsfillthegaps

themselves:inconsistent

assumptionsscaledacross

teams,reworkdiscovered

afterbuild

Anambiguousorstale

brief,orarequirement

clearinisolationbut

wrongincontext

Fastercodingdoesnotmeanfasterdeciding:sign-offstayswiththebusiness,sodecisionspeedbecomestheconstraint.

OliverWymananalysis(schematic).Chapter1setsoutthefivechallengesthatmovethebottleneckupstream.

1.Agentscanscaleinconsistentassumptions

AIcandraftrequirementsandprototypesinhours,butitdoesnotpickupthereal-world,

informalcontextthatpeoplebuildthroughmeetings,experience,andday-to-daycollaboration.Separately,applications’documentationmightbeoutdatedeitherinwritingspecsorthe

codeitself.

Ifgoals,constraints,dependencies,datadefinitions,andpriordecisionsarenotmadeexplicitorkeptcurrent,agentswillfillinthegapsthemselves.Failingtodosomeansthatdifferentteamsandagentsdownstreammaymakedifferentassumptions,producinglargevolumesofplausiblecodethatneitherfittogethernorreflecttheintendedoutcome.

EmployeescanstilluseAItodraftrequirementsfaster,buttheyshouldalsouseittobringup,enrich,andstresstesttheimplicationsofthoserequirementsbeforebuildingbegins.

11

2.Arequirementcanbeclearinisolationbutwrongincontext

Arequirementreadclearlyonitsowncanstillfailwhenintroducedtotherestoftheorganization

—clashingwithexistingdatamodels,systems,processes,policies,regulations,orotherchanges

alreadyunderway.Softwarecannowcheckrequirementsforcontradictionsacrossanentire

portfolioatonce:independentacademictestsshowthatAIcanreliablyflagincompleteor

ambiguousrequirements,andearlystudiesextendthistorequirementsthatclashordependon

oneanother.2Thataddressesaproblemmanualreviewwouldstruggletohandleatscale,butonlyifthecompanyfirstagreesoncommondefinitionsforAItocheckagainst.

Butdetectingcontradictionsistherelativelyeasypart.Themoredifficultstep,ascontrolledstudiesshow,ischeckingeachrequirementagainstexistingsystems,rules,anddependencies,anddoingsobeforeanycodeiswritten.Doingsowillcatcherrorsbeforetheymultiply.3Butwhileautomatedchecksmaybeabletoestablishthatthesoftwarematchesthebrief,theycannotestablishthatthebriefexpresseswhatthebusinessneedsorwants.

3.Fastercodingdoesnotnecessarilymeanfasterdecision-making.Humanbeingsstillhavetosignoffonrequirements

AImightbeabletoorganizeanddraftrequirementsbutjudgingwhetherwhattheyhavedrafted

isright—andformallyapprovingit—isnotsomethingthatcanbedelegated.Thatresponsibility

stayswiththebusinessbecauseultimatelythebusinessisresponsiblefortheoutcome.4Anydelaythatresultsaddtothecost:agentseitherwait,reducingthevalueoftheinvestmentinthem,ortheycontinueworkingbasedonself-generatedassumptions.Thatcausesdriftandcreatesmorework

furtherdowntheroad.

4.Briefqualitybecomesthebottlenecktosuccessfullyexecuting

It’softenthecasethatbriefsarenotmanagedproperly:theremaybenoversionhistoryoramastersourcefromwhichsoftwaremaybegenerated(Thatismoreaquestionofspec-as-productmaturityratherthanoneaboutthelevelofautonomygrantedtoanagent).

Goingforward,though,itisessentialtoensurethatthebriefremainscompleteandconsistent,andthatbusinessdecisionsarereflectedaccordingly.Thefurtheracompanyscalesupautomation,

themoredisciplinethebriefrequires—goingallthewayonlypaysoffwhengenerationtoolsarematureandtrusted.5Ifthat’sdonesuccessfully,thenrequirementsmanagementthenstopscreatingmorepaperworkandbecomesstewardshipofavaluableasset.

2I.Darif,F.Niu,M.Abdellatif,L.C.Briand,S.RameshandA.Adiththan,“AutomatingtheDetectionofRequirementDependenciesUsingLargeLanguageModels,”,February2026.

3Taghavi&Bhavani,“SpecKitAgents:Context-GroundedAgenticWorkflows,”Apr2026.

4OnAI’sdraftingcapability:M.A.Zadenoori,J.Dąbrowski,W.Alhoshan,L.ZhaoandA.Ferrari,“LargeLanguageModels(LLMs)forRequirementsEngineering(RE):ASystematicLiteratureReview,”September2025.Onvalidationandapprovalremainingwithaccountablebusinessroles:P.MandlandP.Mandl,“AI-drivenSoftwareDevelopment:APragmaticPathtoAgentic

DevelopmentProcesses,”June2026.

5D.B.Piskala,“Spec-DrivenDevelopment:FromCodetoContractintheAgeofAICodingAssistants,”technicalreport,January2026.

12

Thetoolingisalreadysplittingintotwocamps.Establishedrequirementsplatformssuchas

JamaConnectfocusongovernedspecifications,traceability,andregulatedenvironments,whilenewerspec-driventools—suchasAWSKiro,GitHubSpecKit,andBMAD-METHOD—usethe

specificationmoredirectlytocoordinateAI-assisteddevelopment.Thatcategoryofsoftwareisstillevolving,soCIOsshouldpilotbyusecaseratherthanadoptoneofthemasstandardtooearly:therighttooldependsonwhetherthebriefisprimarilyagovernedrecordoran

operationalinputthatcoordinatesagentsacrossdelivery.6

5.Cheapcoderemovesthefilterthatusedtostoplow-value

work

Whenbuildingwasexpensive,costactedasacrudebuteffectivefilter:featuresthatcouldnotjustifyateam’stimewereneverbuilt.Asthemarginalcostofgeneratingafeatureapproacheszero,thatfilterdisappears.Theriskisnotthatdeveloperssitidle,buttheopposite:afloodoffeaturesbuiltbecausetheycouldbe,notbecauseanyoneneededthem.Everyfeaturethat

shipscarriescoststhatgenerationdoesnotreduce.Ithastobetested,secured,documented,integrated,andmaintainedforaslongastheproductlives,anditcompetesforusers’attentionwiththefeaturesthatmatter.

Theresultissoftwarethatgrowsmorecomplexandmoreexpensivetorunwhilebecoming

hardertouse.Guardingagainstthatisademand-sidediscipline,notanengineeringone:an

explicitvaluethresholdeachrequestmustclearbeforeitentersthebrief,usagedatathat

showswhichfeaturesareactuallyadopted,andanamedownerwiththeauthoritytosaynoandtoretirewhatisnolongerused.Ifanorganizationcannotarticulatewhyafeatureshouldexist,itshouldnotletagentsbuilditsimplybecausetheycan.

6Anthropic,“TheAI-NativeSDLCplaybook,”August2026.

13

Exhibit6:Wheretoshiftmoneyandattention

Managingtherequirements,thebrief,

andthedecisionsasliving,traceableassets

Automaticallycheckingrequirementsacrossprojectsforconflicts

Empoweringbusinessandproductownersto

approvedecisionsandresolvingtrade-offswithinaweek,orideallyaday

FromTo

Treatingthebriefasathrowawaydocumentthatbecomesobsoleteafterhandovertoengineers

Relyingonpeopletocatcheverycontradictionbyhand

Approvalsonamonthlyorquarterlycycle,stallingagenticgains.

Shippingthoseroughprototypesasthefinishedproduct

Quick,throwawayprototypesusingvibecodingtotestwhatuserswant

Fixingtargetedpainpointstoshowprogress,

withoutsteppingbacktoconsiderstartingwithablankslate

Mappingtheend-to-endprocess,decisions,

exceptions,anddesiredoutcomesbeforebuilding

Allowingagentsandengineerstofillgapswithundocumentedassumptions

Recordingassumptions,constraints,and

unresolveddecisionsaspartofthebrief,soagentsdon’tmakeinconsistentassumptions

Buildingeveryrequestbecausegenerationmakesitcheap

Avaluethresholdeachrequestmustclearbeforeitentersthebrief,usagedataonwhichfeaturesareadopted,andanamedownerwhocan

declinerequestsandretirefeatures

Source:OliverWymananalysis.

Clarifycoredefinitions

Manycross-teamconflictsstartwithtermsthatmeandifferentthingstodifferentpeople.

“Customer,”“activeaccount,”“revenue,”andeven“done”caneachcarrythreeorfourdefinitionsacrossfinance,sales,andoperations.Beforepeopleandagentscanworkfromthesame

requirements,theorganizationneedsasharedlanguageforitscorebusinessconcepts.That

meansagreeingnotjustwhatthetermsinquestionmean,butalsohowtheyarerepresented

indata:theidentifiers,fields,relationships,andrulesbehindthem.Butwhilepeoplecan

usuallybridgesuchinconsistenciesthroughconversationandexperience;agentscannot.If

names,definitions,anddatastructuresdiffer,agentsmayinterpretthesamerequestdifferentlyeachtime.

Exhibit7showsthestandardapproach:holdagreedterms,datastructures,andthecontext

thatgivesthemmeaninginonegovernedplace,thenusethatreferenceforeveryrequirementandagent.Asingleenterprise-widedefinitionwillnotalwaysbeappropriate,soapproved

variantsshouldstatewheretheyapply.Ownership,versionhistory,andchangecontrolmatterhere,becausechangingadefinitionordatastructurecanhavearippleeffectacrossseveralrequirementsandagentbehaviorsatonce.

14

Untilthosedefinitionsareagreedandcentralized—technologistscallita‘sharedsemantic

layer’—eachteam,andnoweachAIagent,worksfromitsownversion.Thedifferentteamswillonlynoticethecontradictionswhenthepiecesfailtofit.

Theyshouldthereforestartsmallbyagreeingonthemostimportanthandfulofterms,holding

themcentrally,andusingthemasthereferenceforeveryrequirementandagent.That

governanceisalsowhatmakesautomaticconflictcheckingpossible,becausesoftwarecanflagaclashonlywheneachtermhasagoverneddefinitiontocheckagainst:oneenterprisemeaningwherepossible,oranexplicitsetofcontext-specificmeaningswithclearrulesforwhereeach

applies.It’snotpossibletobuythatkindofworkofftheshelfsoitwillrequirework.Itmaydredgeupopendefinitionalargumentsthatpreviouslystayedburiedinmismatchedspreadsheets,butitisthefoundationonwhicheverythingelsewillbebuilt.

AIagents

Useshared

definitionsto

reason,

generate,and

validate

Finance

Metrics,

accounting

rules,

policies

Sales

Customer

definitions,

segments,

products

Operations

Processes,

exceptions,

operations

rules

Exhibit7:Onegoverneddefinitionforpeople,requirements,andagents

RequirementsCreatedand

checked

againstthesamedefinitions

andcontext

Governedbusinessdefinitionsandcontext

Oneagreedmeaningforkeyterms,withownership,

context,andchangehistory

Contexteverytermischeckedagainst

Data&masterdata|Systems&interfaces|Processes&workflows

|Policies,controls®ulation|Architecture&standards

Governanceisessential:clearowners,approvalforchanges,andaudithistorykeepthelayertrusted.

Whyitmatters

Singlesourceoftruth

Oneplaceforkey

businesstermsandtheirdefinitions.

Automaticconflictdetection

Requirementsand

agentsarechecked

againstthesame

definitionsandcontext.

Consistencyacrosstheenterprise

Everyone—peopleandAI—worksfromthesamemeaning.

Changewithcontrol

Ownershipandchangehistoryensure

definitionsevolvewithoutbreakingconsistency.

Source:OliverWymananalysis(schematic).Agreeingthetermsthatmatterandholdingthemcentrallyfacilitatesgovernanceandmakesautomaticcross-projectconflictcheckingpossible.

Manageconflictingobjectives

Oncefoundationaldefinitionsareagreedandinplace,thenext,morecomplexchallengeisresolvingpriorityconflicts.Stakeholdersmayagreeonthefactsbutstillwantdifferent

15

outcomes,butshareddefinitionsandscoringmodelsstillcannotresolvecompetingincentives.Instead,ittakesnameddomainowners,arbitrationusingseniorexecutives,andstrategic

choicesmadebeforethebuildbegins.Withoutanamedowner,theworkeitherstallsortheloudestvoicewins.Neitherofthoseoutcomesprovestheexistenceofastrategy.

AI-enabledrapidprototyping,oftencalled“vibecoding,”providesafasterwaytoconverge

priorities.Insteadofdisagreeingovercompetingrequirementsinalong,text-heavy

specification,teamscanfeedprocessknowledge,data,rules,constraints,andassumptionsintoanagentandturndifferentoptionsintoprototypeswithinhours.Testingthoseoptionswith

usersandbusinessownersquicklyshowswhereprioritiesconflictandmakesthetrade-offs

tangible:whatworks,whatdoesnot,andwhatthebusinessiswillingtogiveup.Shortfeedbackloopsthenturnthechosenoptionintoaricherspecificationwithexplicitusecases,acceptancecriteria,andtestcases.Oncethoseareagreed,subsequentcodegenerationbecomesmore

mechanicalandeasiertoverify.

Exhibit8:HowAIchangesthepathfrombusinessintenttoworkingsoftware

Traditional(text-heavy)

2

Share&

interpret

3

Discover

issues

4

Debate

&rework

5

Build

6

Test

1

Capture

requirements

7

Deliver

AI-enabledvaluechain(withrapidprototyping)

2

3

4

5

6

7

Feed

AIchecks

Human

Rapid

Decideon

Generate

contextinto

of

sign-offthe

prototyping

priorities

codeand

AItool

requirements

brief

(vibecoding)

andmake

trade-offs

tests

1

Align

definitionsanddata

8

Verify&deliver

Continuousfeedbackloop:learn,

refinecontext,improveoutcomes

Controlsthatmakeitwork

•Oneownerandoneauthoritativeversion•Setdecisionrightsandresponsetimes

•Validatebeforeagentsact(humansign-off)•Monitordriftandrevalidate

Source:OliverWymananalysis.SchematicrepresentationofanAI-enabledsoftwaredeliveryvaluechain.

Atarecentfinancial-servicesclient,anagenticworkflowprototypewasreadywithintwodays,butdeploymentwasdelayedbytenweekswhiletheCOO’soffice,IT,andFinancearguedoverwhethertolaunchanarrowlyscopedsolutionquicklyorwaituntilproductionintegration,

controlownership,andthebenefitscasewereallfullyagreedupon.TheclientfoundthatthebestwaytobreakthatdeadlockwasbyappointingaseniorsponsorintheCOO’sofficeasthe

16

accou