[{"data":1,"prerenderedAt":1239},["ShallowReactive",2],{"footer-vacatures-en":3,"hub-starten-met-ai-en":4,"content-by-keys-offers-en-ai-reality-check,vibe-code-kickstart,ai-prototype-sprint":76,"content-by-keys-useCases-en-processen-automatiseren-met-ai,interne-ai-assistent-met-eigen-kennis,ai-idee-technisch-haalbaar,is-ai-nodig,ai-betrouwbaar-genoeg,zelf-bouwen-of-software-kopen,ai-toevoegen-aan-bestaand-product,vibe-coding-goed-beginnen":470,"content-by-keys-buyerTriggers-en-ai-laten-bouwen,vastgelopen-met-ai":1082,"content-by-keys-cases-en-":1218,"why-9to5-en":1219},[],{"id":5,"title":6,"approach":7,"body":22,"cta":29,"description":26,"extension":32,"hero":33,"key":35,"label":36,"meta":37,"navigation":38,"path":39,"proof":40,"relations":52,"seo":67,"stem":70,"summary":71,"visuals":72,"__hash__":75},"buyerTriggers_en\u002Fbuyer-triggers\u002Fstarten-met-ai.md","We want to get started with AI, but aren't sure how.",{"title":8,"steps":9},"From a challenge to a sound technical approach.",[10,13,16,19],{"title":11,"text":12},"Define the problem","We establish which decision you need to make, which process you want to improve and what a good result would look like.\n",{"title":14,"text":15},"Understand the context and systems","We look at existing software, data, integrations, users and technical constraints.\n",{"title":17,"text":18},"Assess the options","We compare AI, automation, existing software, integrations and custom development in terms of feasibility, risk and value.\n",{"title":20,"text":21},"Deliver a decision and a way forward","You get a concrete technical direction, the main risks and a logical next step.\n",{"type":23,"value":24,"toc":25},"minimark",[],{"title":26,"searchDepth":27,"depth":27,"links":28},"",2,[],{"title":30,"body":31},"Not sure whether AI is the right solution here?","Briefly describe the idea or process you have in mind. We'll quickly tell you what looks technically promising and what a sensible first step would be.\n","md",{"intro":34},"You might have an idea, a process that could work better or simply a sense that AI could do more for you. We help you work out what looks promising, where the risks lie and whether AI is actually the right solution.\n","starten-met-ai","Start with AI",{},true,"\u002Fbuyer-triggers\u002Fstarten-met-ai",{"intro":41,"points":42},"We don't advise from a fixed preference for AI or custom software. Because we build software ourselves, we can honestly assess what is technically feasible and worthwhile, and what you are better off not building.\n",[43,46,49],{"title":44,"text":45},"Engineers look at the real system","We look at the AI idea, but also at the data, existing software, integrations and users.\n",{"title":47,"text":48},"AI is a tool, not the default answer","Automation, existing software, an integration or building nothing are all serious options too.\n",{"title":50,"text":51},"Advice and implementation from the same people","If building turns out to make sense, we can carry out the next steps ourselves. That keeps our advice realistic.\n",{"useCaseKeys":53,"offerKeys":62,"caseKeys":66},[54,55,56,57,58,59,60,61],"processen-automatiseren-met-ai","interne-ai-assistent-met-eigen-kennis","ai-idee-technisch-haalbaar","is-ai-nodig","ai-betrouwbaar-genoeg","zelf-bouwen-of-software-kopen","ai-toevoegen-aan-bestaand-product","vibe-coding-goed-beginnen",[63,64,65],"ai-reality-check","vibe-code-kickstart","ai-prototype-sprint",[],{"title":68,"description":69},"Getting started with AI? From idea to technical approach | 9to5 software","Help with a serious AI challenge. An AI agent, ChatGPT, Claude or conventional software? We assess what is feasible, what not to build and the next step.\n","buyer-triggers\u002Fstarten-met-ai","We see opportunities for AI, but first want to know what makes sense, what is feasible and what is technically sound.\n",{"hero":73,"proof":74,"approach":74},"sq-orient-options","ls-route-converge","oMS04pD9lTBstiI46yn57yKInU-_urtigoQYGlj0PWA",[77,210,343],{"id":78,"title":79,"body":80,"catalogue":84,"cta":94,"description":26,"extension":32,"fit":99,"hero":103,"key":63,"meta":106,"navigation":38,"next":107,"outcome":120,"path":132,"price":133,"process":136,"proof":151,"relations":164,"scope":169,"seo":197,"stem":200,"summary":201,"summaryPanel":202,"visuals":207,"__hash__":209},"offers_en\u002Foffers\u002Fai-reality-check.md","AI Reality Check",{"type":23,"value":81,"toc":82},[],{"title":26,"searchDepth":27,"depth":27,"links":83},[],{"audience":85,"promise":86,"deliverables":87,"note":93,"visual":73},"For organisations that first want to know what's technically sound and feasible.\n","In one compact engagement, you'll learn what to do, what to avoid and what's needed technically.\n",[88,89,90,91,92],"Technical feasibility and key risks","Build \u002F buy \u002F don't build","Recommended technical approach","What AI should and shouldn't do","A concrete next step","Decision document + discussion with a senior engineer.",{"title":95,"body":96,"primaryCta":97,"local":98},"Want to know what is wise first?","Share your AI question with us. If a Reality Check isn't needed, we'll tell you.\n","Book an AI Reality Check","Senior AI and software engineering from Delft, for organisations in Delft, The Hague, Rotterdam and the surrounding area.\n",{"title":100,"intro":101,"useCaseKeys":102},"When is this offer a fit?","When the main question is not yet how to build something, but what you should be building in the first place.\n",[54,55,56,57],{"headline":104,"intro":105,"primaryCta":97},"Know what to do with AI before you start building.","You see opportunities for AI, but first want to know what is wise. We examine one concrete process or up to three ideas and give you a well-founded technical direction. Even if the conclusion is that you are better off without AI.\n",{},{"title":108,"items":109},"What happens next?",[110,113,116],{"title":111,"text":112,"offerKey":65},"Prove that it works first?","Then an AI Prototype Sprint is often the logical next step.\n",{"title":114,"text":115,"offerKey":64},"Keep building yourself?","Then a Vibe Code Kickstart lets us set up the technical foundation properly.\n",{"title":117,"text":118,"offerKey":119},"Scope already clear enough?","Then we can go straight to Build & Integrate.\n","build-integrate",{"title":121,"items":122},"Afterwards you have...",[123,126,129],{"title":124,"text":125},"A clear technical direction","You know which approach is promising and which options you are better off leaving alone.\n",{"title":127,"text":128},"The main uncertainties on the table","Integrations, data, reliability, risks and human oversight are made concrete enough to make a decision.\n",{"title":130,"text":131},"A logical next step","You know whether to build, buy, integrate, validate something first or stop.\n","\u002Foffers\u002Fai-reality-check",{"label":134,"type":135},"€1,950 excl. VAT","fixed",{"title":137,"steps":138},"How it works.",[139,142,145,148],{"title":140,"text":141},"Sharpen the question","We determine which decision you need to make and what a good result would be.\n",{"title":143,"text":144},"Understand the technical context","We look at processes, data, existing software, integrations and preconditions.\n",{"title":146,"text":147},"Test the options","We compare realistic routes on feasibility, risk and technical complexity.\n",{"title":149,"text":150},"Deliver decision + route","You get our conclusion, technical direction and a concrete next step.\n",{"title":152,"intro":153,"points":154,"caseKeys":163},"Why should you believe this?","We don't advise from a fixed preference for AI or custom software. Because we build software ourselves, we can judge when building is wise and when it is not.\n",[155,157,160],{"title":44,"text":156},"We look at the AI idea and also at data, integrations, software and operations.\n",{"title":158,"text":159},"AI isn't always the answer","Plain automation, existing software or building nothing are real alternatives.\n",{"title":161,"text":162},"We can carry out the follow-up too","If building turns out to make sense, the advice doesn't have to go to another technical party first.\n",[],{"buyerTriggerKeys":165,"useCaseKeys":166,"relatedOfferKeys":167,"caseKeys":168},[35],[54,55,56,57,58,59,60],[65,64,119],[],{"title":170,"intro":171,"activities":172,"deliverables":181,"exclusions":190},"What is included in this offer?","A bounded technical investigation with a concrete decision as the result.\n",{"intro":173,"items":174},"A senior engineer examines the actual question and the context around it.\n",[175,176,177,178,179,180],"Intake and sharpening the problem","Examining one concrete process or up to three AI ideas","Assessing feasibility, dependencies, integrations and risks","Comparing build, buy, integrate or not building","Determining where AI does and does not make sense","Taking human oversight and key preconditions into account",{"intro":182,"items":183},"Not a generic AI report, but a compact decision document that lets you move forward.\n",[90,184,185,186,187,188,189],"What AI should and should not do","Rough solution direction and relevant integrations","Main risks and assumptions","Build \u002F buy \u002F don't build advice","Indication of size and the next step","Review session with a senior engineer",{"intro":191,"items":192},"The Reality Check is meant to make a decision, not to build the whole system already.\n",[193,194,195,196],"Production-ready implementation","Fully worked-out UX or product design","Extensive organisation-wide AI strategy","Unbounded research into multiple processes or business units",{"title":198,"description":199},"AI Reality Check | Technical feasibility of AI | 9to5 software","A senior AI and software engineer assesses what is feasible and worthwhile: an AI agent, Claude, ChatGPT or conventional software? With an approach, risks and next step.\n","offers\u002Fai-reality-check","In a compact engagement we determine what is technically sensible and feasible, where the risks are and what a wise next step is.\n",{"qualifier":203,"result":204,"duration":205,"nextStep":206},"Fixed price · one process or up to three AI ideas","A reasoned technical direction and build \u002F buy \u002F don't build advice","About two weeks","Build, validate with a prototype first, or deliberately stop",{"hero":73,"proof":208,"process":74},"sq-guardrails-check","yAAdWR1HeTz_g1hVnQ1w2rPY4-tRkksM8Ro6yjOmeok",{"id":211,"title":212,"body":213,"catalogue":217,"cta":228,"description":26,"extension":32,"fit":233,"hero":237,"key":64,"meta":240,"navigation":38,"next":241,"outcome":254,"path":265,"price":266,"process":268,"proof":282,"relations":295,"scope":301,"seo":331,"stem":334,"summary":335,"summaryPanel":336,"visuals":340,"__hash__":342},"offers_en\u002Foffers\u002Fvibe-code-kickstart.md","Vibe Code Kickstart",{"type":23,"value":214,"toc":215},[],{"title":26,"searchDepth":27,"depth":27,"links":216},[],{"audience":218,"promise":219,"deliverables":220,"note":226,"visual":227},"For teams that want to keep building themselves with Claude Code, Codex, Cursor, Lovable, Bolt or similar AI tools.\n","We put the right foundation in place. Then you or your team can keep building independently.\n",[221,222,223,224,225],"Stack, architecture and project structure","Data, authentication and environments where needed","Deployment, logging and error handling","Test strategy and AI coding guardrails","One validated end-to-end flow + handover","A professional foundation. Then you build on it.","sq-foundation-build",{"title":229,"body":230,"primaryCta":231,"local":232},"Building yourself, but starting right?","Tell us what you want to make and how you want to keep building afterwards.\n","Start a Vibe Code Kickstart","From Delft we help teams and entrepreneurs in the region get AI-assisted development off the ground in a technically sound way.\n",{"title":100,"intro":234,"useCaseKeys":235},"When you want to build yourself with AI tools, but don't want to gamble with the technical foundation.\n",[61,236],"product-goed-opzetten-voor-ai-development",{"headline":238,"intro":239,"primaryCta":231},"We lay the foundation properly. Then you keep building.","AI coding tools make building software more accessible and faster. But the wrong technical foundation gets expensive later. We set up one product or codebase professionally, validate a working end-to-end flow and then hand it over to you.\n",{},{"title":108,"items":242},[243,246,250],{"title":244,"text":245},"You keep building","That's the usual route. The Kickstart lets you pick up speed on your own afterwards.\n",{"title":247,"text":248,"offerKey":249},"Get stuck on something specific later?","Then a Rescue Sprint can resolve one concrete blocker.\n","rescue-sprint",{"title":251,"text":252,"offerKey":253},"Has the project gone off the rails technically?","Then a Vibe Code Rescue Audit first restores the overview.\n","vibe-code-rescue-audit",{"title":121,"items":255},[256,259,262],{"title":257,"text":258},"A professional technical foundation","Architecture, project structure, data, deployment and access are set up deliberately.\n",{"title":260,"text":261},"Guardrails for AI-assisted development","Tests, conventions and project instructions help coding agents work within the right boundaries.\n",{"title":263,"text":264},"A product you can take forward yourself","One end-to-end path works and the key technical choices are documented.\n","\u002Foffers\u002Fvibe-code-kickstart",{"label":267,"type":135},"€4,950 excl. VAT",{"title":137,"steps":269},[270,273,276,279],{"title":271,"text":272},"Sharpen product + way of working","We determine what you want to build yourself, with which tools and which technical requirements come with it.\n",{"title":274,"text":275},"Lay the foundation","We set up architecture, data, auth, deployment and project structure properly.\n",{"title":277,"text":278},"Add guardrails","We set up tests, conventions and instructions so AI tools make better technical choices.\n",{"title":280,"text":281},"Validate + hand over","We build one end-to-end path, document the foundation and make sure you can continue on your own.\n",{"title":152,"intro":283,"points":284,"caseKeys":294},"We have nothing against vibe coding. With a good engineering foundation you can build much more yourself before you need senior help again.\n",[285,288,291],{"title":286,"text":287},"Senior software engineering as the starting point","The foundation is set up as if the product will actually be used later.\n",{"title":289,"text":290},"Focused on AI-assisted development","The structure helps both people and coding agents understand the codebase.\n",{"title":292,"text":293},"Dependency is not the business model","The Kickstart has succeeded when you can carry on without us.\n",[],{"buyerTriggerKeys":296,"useCaseKeys":298,"relatedOfferKeys":299,"caseKeys":300},[35,297],"ai-laten-bouwen",[61,236],[249,253],[],{"title":170,"intro":302,"activities":303,"deliverables":315,"exclusions":324},"One bounded Kickstart for one product or codebase.\n",{"intro":304,"items":305},"We set up exactly the technical parts that keep speed from turning into chaos later.\n",[306,307,308,309,310,311,312,313,314],"Choosing the stack and architecture","Setting up the repository and project structure","Laying down the base data model","Authentication and authorisation where needed","Environments and deployment structure","Logging and error handling","Test strategy and technical conventions","Guardrails and instructions for AI coding tools","Validating one primary end-to-end flow",{"intro":316,"items":317},"A working technical foundation that is ready for you to build on.\n",[318,319,320,321,322,323],"Set-up codebase and project structure","Working base for deployment and environments","Technical documentation","AI development instructions and conventions","Validated primary flow","Handover explaining the key choices",{"intro":325,"items":326},"We lay the foundation and don't build the complete product within this Kickstart.\n",[327,328,329,330],"Fully worked-out product functionality","Unbounded feature development","Ongoing technical guidance or retainer","Extensive migration of an existing complex codebase",{"title":332,"description":333},"Vibe Code Kickstart | Set up AI coding properly | 9to5 software","Building software yourself with Claude Code, Codex, Cursor, Lovable or Bolt? 9to5 sets up architecture, deployment, auth, data, tests and AI coding guardrails professionally.\n","offers\u002Fvibe-code-kickstart","We set up the technical foundation properly. After that, you or your team keep building independently with Claude Code, Codex, Cursor, Lovable, Bolt or other AI coding tools.\n",{"qualifier":337,"result":338,"duration":205,"nextStep":339},"Fixed price · one product or codebase","A professional technical foundation with one working end-to-end flow","You or your team continue independently with AI coding tools",{"hero":227,"proof":208,"process":341},"ls-system-assemble","e9euJh732-H8mgX6Ag-tYTMatUDDPi69gH_31YmK9Ms",{"id":344,"title":345,"body":346,"catalogue":350,"cta":360,"description":26,"extension":32,"fit":365,"hero":369,"key":65,"meta":372,"navigation":38,"next":373,"outcome":384,"path":395,"price":396,"process":398,"proof":412,"relations":425,"scope":430,"seo":457,"stem":460,"summary":461,"summaryPanel":462,"visuals":467,"__hash__":469},"offers_en\u002Foffers\u002Fai-prototype-sprint.md","AI Prototype Sprint",{"type":23,"value":347,"toc":348},[],{"title":26,"searchDepth":27,"depth":27,"links":349},[],{"audience":351,"promise":352,"deliverables":353,"note":359,"visual":341},"For a specific AI idea whose key technical assumptions need to be validated first.\n","From one clear use case to a working end-to-end prototype that lets you really test the technology.\n",[354,355,356,357,358],"Technical architecture for one use case","Working end-to-end prototype","Up to two key integrations","Validation of key assumptions and reliability","Demo, documentation and advice on moving to production","A working technical flow, not a clickable mock-up.",{"title":361,"body":362,"primaryCta":363,"local":364},"Prove it works technically first?","Share the use case with us. We'll help you choose the smallest prototype that actually proves something important.\n","Start an AI Prototype Sprint","AI prototyping by senior engineers from Delft, for organisations in the region.\n",{"title":100,"intro":366,"useCaseKeys":367},"When the idea is clear enough to build, but still needs to be proven before you go to production.\n",[368,58,60],"ai-prototype-laten-bouwen",{"headline":370,"intro":371,"primaryCta":363},"Prove that it works before you turn it into a complete product.","You roughly know what you want, but not yet whether the technology behaves in practice as you hope. In one bounded Sprint we build the key flow and test the assumptions that determine whether investing further is wise.\n",{},{"title":108,"items":374},[375,378,381],{"title":376,"text":377,"offerKey":119},"The prototype proves the direction","Then Build & Integrate can deliver the production version.\n",{"title":379,"text":380},"The outcome calls for adjustment","Then you have learned concretely which technical route doesn't work, without building a complete product first.\n",{"title":382,"text":383,"offerKey":253},"The prototype has become production itself","If an experiment already has real users and needs professionalising, the Rescue route is a better fit.\n",{"title":121,"items":385},[386,389,392],{"title":387,"text":388},"A working end-to-end prototype","The key user flow actually works with the chosen AI technology and integrations.\n",{"title":390,"text":391},"Technical assumptions are tested","You know better where quality, reliability and integrations are or aren't feasible.\n",{"title":393,"text":394},"A decision about production","You know what it takes to turn the prototype into a serious product or production component.\n","\u002Foffers\u002Fai-prototype-sprint",{"label":397,"type":135},"€6,950 excl. VAT",{"title":137,"steps":399},[400,403,406,409],{"title":401,"text":402},"Define use case + success criterion","We pin down which technical assumption this Sprint needs to prove.\n",{"title":404,"text":405},"Set up architecture + flow","We choose the shortest technical route that validates the real problem.\n",{"title":407,"text":408},"Build + evaluate","We deliver the end-to-end flow and test where the solution is fragile.\n",{"title":410,"text":411},"Demo + production advice","We show what works, what is still uncertain and what a next phase needs.\n",{"title":152,"intro":413,"points":414,"caseKeys":424},"A good prototype is more than a pretty click-through demo. It answers the technical question that decides whether the concept can work.\n",[415,418,421],{"title":416,"text":417},"We test the real thing","We test real integrations, data flows and model behaviour where relevant.\n",{"title":419,"text":420},"Small enough to learn","We keep you from building half a product before the key assumption is proven.\n",{"title":422,"text":423},"Ready for a real follow-up decision","Continuing, adjusting or stopping can all be a good outcome.\n",[],{"buyerTriggerKeys":426,"useCaseKeys":427,"relatedOfferKeys":428,"caseKeys":429},[35,297],[368],[63,119,253],[],{"title":170,"intro":431,"activities":432,"deliverables":443,"exclusions":450},"One clear use case, one primary flow and a controlled amount of technology around it.\n",{"intro":433,"items":434},"We build enough to test the real technical risk, without building the complete end product right away.\n",[435,436,437,438,439,440,441,442],"Sharpening scope and success criteria","Defining the technical architecture","Building a working prototype","Up to two key external integrations","Delivering one primary end-to-end flow","Configuring the model, agent or instructions","Validating the key technical assumptions","Evaluating reliability at a high level",{"intro":444,"items":445},"A tangible prototype plus enough technical clarity for a follow-up decision.\n",[355,446,447,448,320,449],"Technical architecture direction","Validated core flow","Demo of the result","Advice for production and next steps",{"intro":451,"items":452},"A Prototype Sprint proves the core. Production hardening is a separate step.\n",[453,454,455,456],"Full production guarantees or SLAs","Extensive scalability and operationalisation","Unbounded integrations or multiple main flows","Full product development beyond the agreed use case",{"title":458,"description":459},"AI Prototype Sprint | Working AI prototype | 9to5 software","Turn one AI concept into a working end-to-end prototype, for example with Claude or OpenAI. Includes architecture, integrations, validation and production advice.\n","offers\u002Fai-prototype-sprint","From one concrete AI idea to a working end-to-end prototype that lets you actually test the key technical assumptions.\n",{"qualifier":463,"result":464,"duration":465,"nextStep":466},"Fixed price · one concrete AI idea","A working end-to-end prototype with tested technical assumptions","One bounded Sprint of about three weeks","A reasoned decision about production, for example via Build & Integrate",{"hero":227,"proof":468,"process":341},"sq-process-steps","WOLcKM4lFt5312Z6kkvWsCyd0jk_equXhLoXFeu1UMg",[471,547,625,701,777,853,930,1006],{"id":472,"title":473,"body":474,"description":26,"desiredOutcome":478,"extension":32,"hero":489,"key":54,"meta":491,"navigation":38,"path":492,"problem":493,"proof":505,"recognition":517,"recommendedApproach":532,"relations":534,"seo":539,"stem":542,"summary":543,"visuals":544,"__hash__":546},"useCases_en\u002Fuse-cases\u002Fprocessen-automatiseren-met-ai.md","Which processes are suitable for AI or automation?",{"type":23,"value":475,"toc":476},[],{"title":26,"searchDepth":27,"depth":27,"links":477},[],{"intro":479,"items":480},"You don't want to end up with a list of twenty AI ideas. You want to know where a technical investment actually makes sense.\n",[481,484,487],{"title":482,"text":483},"The best opportunities first","You know which processes combine enough value, volume and technical feasibility to explore further.\n",{"title":485,"text":486},"AI where it's needed","We distinguish between AI, regular automation, existing software and simple integrations.\n",{"title":92,"text":488},"You know which question to validate or build first, or which not to pursue any further.\n",{"intro":490},"Maybe you see opportunities for AI everywhere. Or so many that you don't know where to start. We help determine which processes are interesting, which technology fits them and which ideas you're better off leaving alone.\n",{},"\u002Fuse-cases\u002Fprocessen-automatiseren-met-ai",{"intro":494,"causes":495},"Not every annoying process is automatically a good AI problem. The value lies in the combination of process, data, technical feasibility and impact.\n",[496,499,502],{"title":497,"text":498},"AI is taken as the starting point too quickly","A fixed rule, integration or existing tool can sometimes solve the same problem more simply and reliably.\n",{"title":500,"text":501},"The real bottleneck is still unclear","What looks like manual work at first sight may be caused by a poor process or a missing integration.\n",{"title":503,"text":504},"Feasibility differs per task","Some tasks tolerate uncertainty, others require virtually error-free behaviour.\n",{"intro":506,"points":507},"We start with the problem you're trying to solve, and only then ask which AI model fits. Sometimes the best technical conclusion is that part of it doesn't need AI at all.\n",[508,511,514],{"title":509,"text":510},"Software engineering before AI hype","We also compare AI with automation, integrations and existing software.\n",{"title":512,"text":513},"Technical feasibility counts from the start","Data, systems and operational constraints are part of the assessment.\n",{"title":515,"text":516},"We can build the follow-up too","The advice doesn't have to be translated again by another technical party afterwards.\n",{"intro":518,"signals":519},"This question often comes up when there is clear inefficiency, but it's not yet clear which technical solution fits it best.\n",[520,523,526,529],{"title":521,"text":522},"Lots of repetitive knowledge work","Employees keep reading, checking, summarising or classifying similar information.\n",{"title":524,"text":525},"Information is copied over by hand","Data moves via people from email, documents or spreadsheets into other systems.\n",{"title":527,"text":528},"There are many AI ideas at once","Different teams see opportunities, but nobody knows which are the most interesting technically and commercially.\n",{"title":530,"text":531},"You don't want to automate for the sake of it","The solution has to demonstrably reduce time, errors or friction.\n",{"intro":533},"In an AI Reality Check we examine up to three ideas or one concrete process. We assess value, technical feasibility, data, integrations, risks and build versus buy. If one part then needs to be proven in practice, an AI Prototype Sprint can be the logical next step.\n",{"buyerTriggerKeys":535,"primaryOfferKey":63,"offerKeys":536,"caseKeys":537,"relatedUseCaseKeys":538},[35],[63,65],[],[57,59],{"title":540,"description":541},"Which processes are suitable for AI or automation? | 9to5 software","Find out which business processes are suitable for AI or automation. 9to5 examines processes, systems, data and technical feasibility.\n","use-cases\u002Fprocessen-automatiseren-met-ai","You see opportunities to make manual work smarter, but first want to know where AI actually adds value and where regular automation fits better.\n",{"hero":468,"problem":73,"proof":545},"ls-workflow-flow","Z9mZqpG5Qyu0wkGGaYeR4PecFC7nvQXcfsPeGf6UX80",{"id":548,"title":549,"body":550,"description":26,"desiredOutcome":554,"extension":32,"hero":566,"key":55,"meta":568,"navigation":38,"path":569,"problem":570,"proof":582,"recognition":594,"recommendedApproach":609,"relations":611,"seo":616,"stem":619,"summary":620,"visuals":621,"__hash__":624},"useCases_en\u002Fuse-cases\u002Finterne-ai-assistent-met-eigen-kennis.md","Can we build an internal AI assistant with our own knowledge?",{"type":23,"value":551,"toc":552},[],{"title":26,"searchDepth":27,"depth":27,"links":553},[],{"intro":555,"items":556},"You first want to know whether an internal assistant can really become usable before having a complete system built.\n",[557,560,563],{"title":558,"text":559},"Know what is technically feasible","You get insight into which sources are usable and how AI could get access to them.\n",{"title":561,"text":562},"Understand what reliable enough means","We determine where source references, validation or human review are needed.\n",{"title":564,"text":565},"A realistic solution direction","You know how data, retrieval, permissions and user experience can come together technically.\n",{"intro":567},"An internal assistant sounds logical: ask a question and get an immediate answer from your own knowledge. But whether that works well depends heavily on your sources, permissions, required reliability and the kind of questions employees ask.\n",{},"\u002Fuse-cases\u002Finterne-ai-assistent-met-eigen-kennis",{"intro":571,"causes":572},"An internal AI assistant is not simply ChatGPT with a folder of documents. Its quality is largely determined by sources, retrieval, access rights and the question of what a reliable answer is.\n",[573,576,579],{"title":574,"text":575},"Internal knowledge is rarely neatly structured","Documents differ in quality, freshness and format.\n",{"title":577,"text":578},"More context is not automatically better","Too much irrelevant information can actually make answers worse.\n",{"title":580,"text":581},"Access remains a security matter","The assistant must not become a new route to information a user normally may not see.\n",{"intro":583,"points":584},"A good knowledge assistant calls for both AI expertise and regular software engineering. Sources, data, permissions and integrations are at least as important as the model.\n",[585,588,591],{"title":586,"text":587},"We start with the information","First understand what knowledge is available and what users want to do with it.\n",{"title":589,"text":590},"Permissions belong in the design","Security is not treated as a later add-on.\n",{"title":592,"text":593},"We can go from research to implementation","If the idea proves feasible, the technical context doesn't have to be rebuilt from scratch at another party.\n",{"intro":595,"signals":596},"This usually comes up when knowledge does exist, but is hard to find or widely spread across the organisation.\n",[597,600,603,606],{"title":598,"text":599},"Employees keep asking the same questions","Answers sit in documents, manuals, SharePoint, databases or with experienced colleagues.\n",{"title":601,"text":602},"Search returns too much noise","People know the information exists somewhere, but can't quickly find the right passage or version.\n",{"title":604,"text":605},"A general chatbot is not enough","Good answers require knowledge that is not public or generally available.\n",{"title":607,"text":608},"Permissions make it complicated","Not every employee may see the same documents or data.\n",{"intro":610},"With an AI Reality Check we examine the desired questions, sources, access rules and required reliability. If the biggest uncertainty then needs practical testing, an AI Prototype Sprint can prove the most important end-to-end flow.\n",{"buyerTriggerKeys":612,"primaryOfferKey":63,"offerKeys":613,"caseKeys":614,"relatedUseCaseKeys":615},[35],[63,65],[],[58,60],{"title":617,"description":618},"Internal AI assistant with your own knowledge | 9to5 software","An internal ChatGPT using your own documents and data? 9to5 examines sources, RAG and retrieval, permissions and technical feasibility.\n","use-cases\u002Finterne-ai-assistent-met-eigen-kennis","You want to know whether employees can reliably use AI to work with internal documents, data and knowledge that is now spread across different sources.\n",{"hero":622,"problem":208,"proof":623},"sq-knowledge-filter","ls-system-connect","rPps0CfPhGKhgluvbpO1IUJG7v8sTi68GVuZUyI1cG0",{"id":626,"title":627,"body":628,"description":26,"desiredOutcome":632,"extension":32,"hero":644,"key":56,"meta":646,"navigation":38,"path":647,"problem":648,"proof":660,"recognition":672,"recommendedApproach":687,"relations":689,"seo":694,"stem":697,"summary":698,"visuals":699,"__hash__":700},"useCases_en\u002Fuse-cases\u002Fai-idee-technisch-haalbaar.md","Is our AI idea technically feasible?",{"type":23,"value":629,"toc":630},[],{"title":26,"searchDepth":27,"depth":27,"links":631},[],{"intro":633,"items":634},"You want enough technical evidence to decide whether it is wise to invest time and budget in the idea.\n",[635,638,641],{"title":636,"text":637},"A clear feasibility verdict","You know which parts are realistic and where fundamental uncertainty remains.\n",{"title":639,"text":640},"The biggest technical risks","Data, integrations, reliability and operational limitations are made explicit.\n",{"title":642,"text":643},"A logical validation step","You know what still needs testing before you responsibly build in full.\n",{"intro":645},"An idea can sound logical on paper and still turn out to be technically hard. Conversely, something can sound complicated while a small experiment quickly brings clarity. We help you see that difference early.\n",{},"\u002Fuse-cases\u002Fai-idee-technisch-haalbaar",{"intro":649,"causes":650},"Technical feasibility is more than the question whether a model can perform the task successfully once.\n",[651,654,657],{"title":652,"text":653},"Demo and production are different requirements","An impressive example says little about consistent behaviour at scale.\n",{"title":655,"text":656},"Your own data matters a lot","The quality and availability of information can make or break the solution.\n",{"title":658,"text":659},"Integrations can be decisive","Sometimes the AI part is simple and the real complexity sits in existing systems.\n",{"intro":661,"points":662},"We look at this as engineers. Whether a concept sounds interesting matters less than what it technically takes to make it work reliably enough.\n",[663,666,669],{"title":664,"text":665},"Risks visible early","You discover technical showstoppers before the full project has started.\n",{"title":667,"text":668},"A no is also an answer","A Reality Check may also conclude that the idea is not wise in this form.\n",{"title":670,"text":671},"A concrete technical route","If it is promising, you know which parts then need to be proven or built.\n",{"intro":673,"signals":674},"This question usually comes up when the problem is clear, but the technical possibilities have not yet been sufficiently proven.\n",[675,678,681,684],{"title":676,"text":677},"A vendor says it can be done","But you want to know independently under which conditions that really holds.\n",{"title":679,"text":680},"The demos online look convincing","It's just unclear whether the same technology works with your own data and requirements.\n",{"title":682,"text":683},"One technical part determines the project","For example accuracy, latency, integration or processing of specific documents.\n",{"title":685,"text":686},"The investment after this step is large","You want to reduce uncertainty before having a full product built.\n",{"intro":688},"The AI Reality Check makes the technical assumptions explicit and determines which are plausible and which are not. If one crucial assumption can't be answered on paper yet, an AI Prototype Sprint can validate it in practice.\n",{"buyerTriggerKeys":690,"primaryOfferKey":63,"offerKeys":691,"caseKeys":692,"relatedUseCaseKeys":693},[35],[63,65],[],[58,57],{"title":695,"description":696},"Is our AI idea technically feasible? | 9to5 software","Have the technical feasibility of your AI idea assessed. 9to5 examines models, data, integrations, risks and a realistic solution direction.\n","use-cases\u002Fai-idee-technisch-haalbaar","You have a concrete AI idea and want to know whether it can really be built with the available models, data, systems and constraints.\n",{"hero":73,"problem":208,"proof":74},"nXhvMZpj-Ze0VcqpMSJ12RYkFCrsaViqtrzaF2WVJiI",{"id":702,"title":703,"body":704,"description":26,"desiredOutcome":708,"extension":32,"hero":720,"key":57,"meta":722,"navigation":38,"path":723,"problem":724,"proof":736,"recognition":748,"recommendedApproach":763,"relations":765,"seo":770,"stem":773,"summary":774,"visuals":775,"__hash__":776},"useCases_en\u002Fuse-cases\u002Fis-ai-nodig.md","Do we need AI for our idea?",{"type":23,"value":705,"toc":706},[],{"title":26,"searchDepth":27,"depth":27,"links":707},[],{"intro":709,"items":710},"You want the technically simplest solution that solves the real problem well enough. Even if there turns out to be no AI in it.\n",[711,714,717],{"title":712,"text":713},"Clarity about the real need","We sharpen which problem the user or organisation is actually trying to solve.\n",{"title":715,"text":716},"Alternatives side by side","AI is compared with rules, search functionality, automation, integrations and existing software.\n",{"title":718,"text":719},"No unnecessary complexity","You only choose AI when the benefits outweigh the extra uncertainty, cost and maintenance.\n",{"intro":721},"AI is a means, not a mandatory part of a modern software project. Sometimes a model delivers exactly the flexibility you need. Sometimes it mainly makes a problem more expensive, slower and less predictable.\n",{},"\u002Fuse-cases\u002Fis-ai-nodig",{"intro":725,"causes":726},"AI lowers the barrier to automating complex tasks, but at the same time introduces uncertainty that regular software often doesn't have.\n",[727,730,733],{"title":728,"text":729},"Technology is chosen before the problem","So later you try to make the process fit the chosen solution.\n",{"title":731,"text":732},"Non-determinism has a price","Validation, monitoring and error handling become more important as soon as model output is part of the workflow.\n",{"title":734,"text":735},"Existing solutions are forgotten","An API, integration or standard software can sometimes deliver the same result faster and cheaper.\n",{"intro":737,"points":738},"9to5 software would rather earn from a good technical decision than from unnecessary complexity. We build AI, but have no interest in AI as the default answer to every problem.\n",[739,742,745],{"title":740,"text":741},"Software engineers, not just AI consultants","That's why we can also seriously assess simpler technical alternatives.\n",{"title":743,"text":744},"Build, buy or don't build","Not building is a valid technical conclusion.\n",{"title":746,"text":747},"No automatic follow-up engagement","If the Reality Check gives enough of an answer, nothing needs to follow.\n",{"intro":749,"signals":750},"This is an especially good question when AI was named as the solution early on, while the problem itself hasn't been worked out technically yet.\n",[751,754,757,760],{"title":752,"text":753},"The project started with \"we need to do something with AI\"","There is enthusiasm about the technology, but the concrete problem is still vague.\n",{"title":755,"text":756},"The task seems fairly predictable","You wonder whether regular rules or existing software wouldn't be enough.\n",{"title":758,"text":759},"Reliability is extremely important","Variable model output may be undesirable for the core of the process.\n",{"title":761,"text":762},"You want to avoid vendor and model complexity","AI should only be added when that dependency really delivers something.\n",{"intro":764},"The AI Reality Check deliberately compares several technical routes. The outcome can be AI, a combination of AI and regular software, or simply: don't build with AI. Only if AI really adds something do we then determine a logical next step.\n",{"buyerTriggerKeys":766,"primaryOfferKey":63,"offerKeys":767,"caseKeys":768,"relatedUseCaseKeys":769},[35],[63],[],[56,59],{"title":771,"description":772},"Do we need AI for our idea? | 9to5 software","Not every problem needs AI. 9to5 compares AI with regular software, automation, integrations and existing solutions.\n","use-cases\u002Fis-ai-nodig","You have a problem or product idea and suspect AI could be a solution, but first want to know whether that is technically and practically the wisest route.\n",{"hero":73,"problem":468,"proof":74},"jY_wiimcbcgfU4hJZSC-MbkrLdhoPA3RYSnl1nrt4UI",{"id":778,"title":779,"body":780,"description":26,"desiredOutcome":784,"extension":32,"hero":796,"key":58,"meta":798,"navigation":38,"path":799,"problem":800,"proof":812,"recognition":824,"recommendedApproach":839,"relations":841,"seo":846,"stem":849,"summary":850,"visuals":851,"__hash__":852},"useCases_en\u002Fuse-cases\u002Fai-betrouwbaar-genoeg.md","Can AI perform this task reliably enough?",{"type":23,"value":781,"toc":782},[],{"title":26,"searchDepth":27,"depth":27,"links":783},[],{"intro":785,"items":786},"You want to set a realistic quality bar and know whether the technology can meet it with the right technical measures.\n",[787,790,793],{"title":788,"text":789},"A concrete definition of good enough","We make explicit which errors are acceptable and which are not.\n",{"title":791,"text":792},"Insight into remaining risks","You know where AI remains uncertain and what the practical impact of that is.\n",{"title":794,"text":795},"A fitting control layer","We determine where validation, fallback or human review is needed.\n",{"intro":797},"\"Can AI do this?\" is often the wrong question. A better one: how often does it go right, what mistakes does it make and what happens when such a mistake occurs? That tells you whether an AI solution is usable in practice.\n",{},"\u002Fuse-cases\u002Fai-betrouwbaar-genoeg",{"intro":801,"causes":802},"AI is probabilistic, so you can't rule out every failure scenario. You can understand, measure and contain errors.\n",[803,806,809],{"title":804,"text":805},"Average quality says too little","A high score can still hide unacceptable errors.\n",{"title":807,"text":808},"Test examples are often too friendly","Real users and data contain many more exceptions.\n",{"title":810,"text":811},"System design affects reliability","Validation, retrieval and human-in-the-loop can matter more than yet another prompt.\n",{"intro":813,"points":814},"For us reliability is an engineering question, not a feeling after a good demo.\n",[815,818,821],{"title":816,"text":817},"Errors become part of the design","We look explicitly at what can go wrong and what impact that has.\n",{"title":819,"text":820},"Human-in-the-loop where it adds value","A small human check can sometimes be much wiser than pursuing full autonomy.\n",{"title":822,"text":823},"Criteria first, then technology","Only when \"good enough\" is clear can you judge whether a solution is feasible.\n",{"intro":825,"signals":826},"This mostly comes up when an AI demo is convincing, but the task is important enough that occasional errors have consequences.\n",[827,830,833,836],{"title":828,"text":829},"Quality varies per example","Some cases go excellently and others surprisingly badly.\n",{"title":831,"text":832},"Not all errors are equally serious","A wrong phrasing is different from a wrong decision or amount.\n",{"title":834,"text":835},"Manual checking may still be needed","You want to know how much human review is still needed to run the process responsibly.\n",{"title":837,"text":838},"You can't compare objectively yet","The assessment is mostly based on a few separate tests or demos.\n",{"intro":840},"In an AI Reality Check we first define what reliable enough means for this specific task and which risks need to be managed technically. If practical measurements are needed, an AI Prototype Sprint can then actually test the most important scenarios.\n",{"buyerTriggerKeys":842,"primaryOfferKey":63,"offerKeys":843,"caseKeys":844,"relatedUseCaseKeys":845},[35],[63,65],[],[56,55],{"title":847,"description":848},"Is AI reliable enough for this task? | 9to5 software","Find out whether AI is reliable enough for your process. 9to5 looks at error margins, evals, risks, human-in-the-loop and technical feasibility.\n","use-cases\u002Fai-betrouwbaar-genoeg","You can see that AI can in principle perform the task, but want to know whether the quality is predictable enough for serious use.\n",{"hero":208,"problem":468,"proof":545},"1eHc-QVFMSpnvdWD_ldWkQjaMkOCDK0so4qQpB0xL8o",{"id":854,"title":855,"body":856,"description":26,"desiredOutcome":860,"extension":32,"hero":872,"key":59,"meta":874,"navigation":38,"path":875,"problem":876,"proof":888,"recognition":900,"recommendedApproach":915,"relations":917,"seo":922,"stem":925,"summary":926,"visuals":927,"__hash__":929},"useCases_en\u002Fuse-cases\u002Fzelf-bouwen-of-software-kopen.md","Should we build ourselves, use existing software or connect systems?",{"type":23,"value":857,"toc":858},[],{"title":26,"searchDepth":27,"depth":27,"links":859},[],{"intro":861,"items":862},"You don't want to choose a platform you later have to build around, nor fund custom software for something that already exists and works fine.\n",[863,866,869],{"title":864,"text":865},"A reasoned build-buy-integrate choice","You know which parts can be standard and where custom work really adds value.\n",{"title":867,"text":868},"Understand dependencies up front","Lock-in, integrations, data and extensibility are part of the choice.\n",{"title":870,"text":871},"A practical technical route","You know where to start and which investments may come later.\n",{"intro":873},"Building yourself gives control. Existing software gives speed. Smart integration can sometimes be just enough. The best route is the one that fits what you actually need, even if it's the least exciting one technically.\n",{},"\u002Fuse-cases\u002Fzelf-bouwen-of-software-kopen",{"intro":877,"causes":878},"Build versus buy is rarely a binary choice. Many good solutions deliberately combine standard software, APIs and custom work.\n",[879,882,885],{"title":880,"text":881},"Comparing features is not enough","Data ownership, permissions, integrations and future changes often matter more than the feature list.\n",{"title":883,"text":884},"Lock-in only becomes visible later","A quick start can become expensive when important data or workflows are hard to move.\n",{"title":886,"text":887},"Custom work is too quickly seen as all-or-nothing","Sometimes only the distinguishing part needs to be built yourself.\n",{"intro":889,"points":890},"Because 9to5 both builds software and integrates existing systems, we don't automatically reason towards one type of solution.\n",[891,894,897],{"title":892,"text":893},"Custom work is not a goal in itself","We only build ourselves where that offers enough advantage.\n",{"title":895,"text":896},"Integrations are a fully-fledged route","Good existing software doesn't need to be thrown away.\n",{"title":898,"text":899},"Future freedom counts","The cheapest start isn't always the best technical choice in the longer term.\n",{"intro":901,"signals":902},"This question often arises when the first search turns up dozens of AI tools, but not a single solution fits the process exactly.\n",[903,906,909,912],{"title":904,"text":905},"Many possible tools already exist","It's hard to judge which differences matter and which are mostly marketing.\n",{"title":907,"text":908},"No product fits completely","Standard software covers a large part, but misses a few important pieces.\n",{"title":910,"text":911},"Custom software sounds attractive and expensive","You want to know what control or flexibility the extra investment really delivers.\n",{"title":913,"text":914},"Integrations can be a middle ground","Maybe one system doesn't have to do everything if existing parts can be connected well.\n",{"intro":916},"The AI Reality Check compares the relevant technical routes and makes clear what you'd better buy, connect or build yourself. If you then mainly want to develop software yourself, a Vibe Code Kickstart can lay the foundation. For larger custom implementation, Build & Integrate can follow.\n",{"buyerTriggerKeys":918,"primaryOfferKey":63,"offerKeys":919,"caseKeys":920,"relatedUseCaseKeys":921},[35],[63,64,119],[],[57,61],{"title":923,"description":924},"Build yourself, buy software or connect systems? | 9to5 software","Build versus buy for AI or automation? 9to5 compares custom software, existing software and integrations on technology, risk, cost and flexibility.\n","use-cases\u002Fzelf-bouwen-of-software-kopen","The problem is clear, but there are several technical routes. You want to know which combination of buying, building and integrating is wisest.\n",{"hero":73,"problem":928,"proof":74},"sq-connect-nodes","EszLeZUAC_mOFpltDkfCOfBHj_6V8ytDWYOk1Zj_vmQ",{"id":931,"title":932,"body":933,"description":26,"desiredOutcome":937,"extension":32,"hero":949,"key":60,"meta":951,"navigation":38,"path":952,"problem":953,"proof":965,"recognition":977,"recommendedApproach":992,"relations":994,"seo":999,"stem":1002,"summary":1003,"visuals":1004,"__hash__":1005},"useCases_en\u002Fuse-cases\u002Fai-toevoegen-aan-bestaand-product.md","How do we add AI to our existing product?",{"type":23,"value":934,"toc":935},[],{"title":26,"searchDepth":27,"depth":27,"links":936},[],{"intro":938,"items":939},"You want to know which AI feature delivers enough user value and technically fits the product that already exists.\n",[940,943,946],{"title":941,"text":942},"A sharp product use case","You know which user can solve which problem better with AI.\n",{"title":944,"text":945},"A fitting technical architecture","The new functionality connects to existing data, auth and business logic.\n",{"title":947,"text":948},"A realistic implementation route","You know what needs testing first and what can then be built production-ready.\n",{"intro":950},"You don't have to make your product \"AI-first\" to use AI well. Often most of the value lies in one targeted improvement of an existing workflow. So the first question is not how to add AI, but where.\n",{},"\u002Fuse-cases\u002Fai-toevoegen-aan-bestaand-product",{"intro":954,"causes":955},"Adding AI to existing software is both a product choice and an architecture choice.\n",[956,959,962],{"title":957,"text":958},"The technology draws too much attention","An interesting AI possibility is not yet a useful product feature.\n",{"title":960,"text":961},"Existing data and permissions count","A feature has to fit the same user and security context as the rest of the product.\n",{"title":963,"text":964},"New failure modes are added","Variable quality, latency and model costs have to become part of the product experience.\n",{"intro":966,"points":967},"9to5 software likes working in existing products and codebases. So AI doesn't have to stay a separate experiment next to the real product.\n",[968,971,974],{"title":969,"text":970},"Product and technology together","We assess both user value and technical consequences.\n",{"title":972,"text":973},"Existing software remains the starting point","Auth, data and business logic are reused where possible.\n",{"title":975,"text":976},"From exploration to real implementation","If the use case holds up, the same engineers can also build the hard technical follow-up.\n",{"intro":978,"signals":979},"This often comes up when competitors launch AI features or users start asking what AI could mean in the product.\n",[980,983,986,989],{"title":981,"text":982},"There are several possible AI features","Summarising, generating, searching, agents and automation all seem interesting.\n",{"title":984,"text":985},"You don't want to build a gimmick","The feature has to demonstrably solve an existing user problem better.\n",{"title":987,"text":988},"The feature needs product data","AI has to be able to safely use information that is already in the software.\n",{"title":990,"text":991},"The existing architecture sets limits","You want to avoid one AI feature becoming a separate technical island.\n",{"intro":993},"In an AI Reality Check we first determine which AI use case has enough value and technical feasibility and how it fits into the existing product. An AI Prototype Sprint can then prove the core before a larger Build & Integrate implementation follows.\n",{"buyerTriggerKeys":995,"primaryOfferKey":63,"offerKeys":996,"caseKeys":997,"relatedUseCaseKeys":998},[35],[63,65,119],[],[56,58],{"title":1000,"description":1001},"Add AI to an existing product | 9to5 software","Adding AI to an existing app or SaaS product? 9to5 examines promising use cases, architecture, data, integrations and technical feasibility.\n","use-cases\u002Fai-toevoegen-aan-bestaand-product","You see opportunities to make your current software smarter, but first want to determine which AI functionality really adds something, technically and commercially.\n",{"hero":928,"problem":227,"proof":623},"RSVufcPhYOQ6qeNYCFlOmKFGLqdfCrZhxfRPGRtSLjM",{"id":1007,"title":1008,"body":1009,"description":26,"desiredOutcome":1013,"extension":32,"hero":1025,"key":61,"meta":1027,"navigation":38,"path":1028,"problem":1029,"proof":1041,"recognition":1053,"recommendedApproach":1068,"relations":1070,"seo":1075,"stem":1078,"summary":1079,"visuals":1080,"__hash__":1081},"useCases_en\u002Fuse-cases\u002Fvibe-coding-goed-beginnen.md","We want to build software ourselves with AI tools, but start off right technically",{"type":23,"value":1010,"toc":1011},[],{"title":26,"searchDepth":27,"depth":27,"links":1012},[],{"intro":1014,"items":1015},"You want to keep the speed and autonomy of vibe coding without needing a technical rescue operation later.\n",[1016,1019,1022],{"title":1017,"text":1018},"A good technical foundation","Stack, architecture, repository, data and deployment have a clear structure from the start.\n",{"title":1020,"text":1021},"Guardrails for AI coding tools","Tests, conventions and project instructions give coding agents better feedback while building.\n",{"title":1023,"text":1024},"Then carry on yourself","The setup is specifically meant to avoid day-to-day dependency on 9to5.\n",{"intro":1026},"Building yourself with AI can go incredibly fast. That's exactly why it's smart to get the foundation right early. We handle the senior engineering part that AI coding tools don't automatically protect you from. Then you carry on.\n",{},"\u002Fuse-cases\u002Fvibe-coding-goed-beginnen",{"intro":1030,"causes":1031},"AI lowers the cost of writing code, but not automatically the cost of bad technical choices.\n",[1032,1035,1038],{"title":1033,"text":1034},"AI optimises locally","A coding agent solves the current task, but doesn't guard the product's architecture for years by itself.\n",{"title":1036,"text":1037},"Bad patterns scale faster","Once something is in the codebase, AI can repeat it in more places at lightning speed.\n",{"title":1039,"text":1040},"The hard foundational parts come early","Auth, deployment, databases and environments are less visible than features, but fundamental.\n",{"intro":1042,"points":1043},"This offer follows exactly the principle of 9to5 software: build yourself where you can and bring in senior engineering where it's needed.\n",[1044,1047,1050],{"title":1045,"text":1046},"No permanent development capacity","The handover is part of the result, not the start of a retainer.\n",{"title":1048,"text":1049},"AI tools are part of the way of working","We deliberately design the codebase so Claude Code, Codex, Cursor and similar tools can work well in it.\n",{"title":1051,"text":1052},"A rescue remains possible later","If you do get technically stuck somewhere months later, we can step in again in a targeted way.\n",{"intro":1054,"signals":1055},"This fits teams and entrepreneurs who deliberately want to build themselves, but know that a good start prevents a lot of technical misery later.\n",[1056,1059,1062,1065],{"title":1057,"text":1058},"With AI you can already do a surprising amount yourself","Building features is no longer the biggest hurdle.\n",{"title":1060,"text":1061},"Architecture feels harder","Stack, data, auth and project structure require choices whose impact only becomes visible later.\n",{"title":1063,"text":1064},"The product has a serious purpose","This is no throwaway experiment, but software that will affect real users or business processes.\n",{"title":1066,"text":1067},"You don't want a traditional agency model","Ideally you build on yourself afterwards and only bring in senior engineers where it's really needed.\n",{"intro":1069},"The Vibe Code Kickstart is made for this. For one product or codebase we set up the architecture, project structure, data layer, auth, deployment, tests, guardrails and documentation properly and validate one end-to-end path. Then you carry on building yourself.\n",{"buyerTriggerKeys":1071,"primaryOfferKey":64,"offerKeys":1072,"caseKeys":1073,"relatedUseCaseKeys":1074},[35],[64,249],[],[59,60],{"title":1076,"description":1077},"Start vibe coding the right way | 9to5 software","Building software yourself with Claude Code, Codex, Cursor, Lovable or Bolt? 9to5 sets up architecture, deployment, auth, tests and guardrails properly.\n","use-cases\u002Fvibe-coding-goed-beginnen","You want to build software quickly yourself with Claude Code, Codex, Cursor, Lovable, Bolt or similar AI tools, without piling up technical problems from day one.\n",{"hero":227,"problem":208,"proof":341},"4hA0ADe7kA-2HxaPH6ZcA3a9RH-qZ_SJDyW__s2-hrE",[1083,1144],{"id":1084,"title":1085,"approach":1086,"body":1101,"cta":1105,"description":26,"extension":32,"hero":1108,"key":297,"label":1110,"meta":1111,"navigation":38,"path":1112,"proof":1113,"relations":1125,"seo":1137,"stem":1140,"summary":1141,"visuals":1142,"__hash__":1143},"buyerTriggers_en\u002Fbuyer-triggers\u002Fai-laten-bouwen.md","We know what we want. Now it needs to be built.",{"title":1087,"steps":1088},"From a clear scope to something that really works.",[1089,1092,1095,1098],{"title":1090,"text":1091},"Define the scope and success criteria","We make it clear what needs to work, who it is for and when it is good enough to go live.\n",{"title":1093,"text":1094},"Set up the architecture and integrations","We determine how AI, data, existing software, permissions and integrations should work together technically.\n",{"title":1096,"text":1097},"Build and test","We implement the difficult part and test more than the happy path, including reliability, errors and human oversight where needed.\n",{"title":1099,"text":1100},"Bring it into production and hand over","We launch it properly, document the important decisions and make sure your team can carry on independently.\n",{"type":23,"value":1102,"toc":1103},[],{"title":26,"searchDepth":27,"depth":27,"links":1104},[],{"title":1106,"body":1107},"Know what needs to be built?","Explain what you need and which systems it should work with. We'll quickly tell you how to build it properly and what a logical first step would be.\n",{"intro":1109},"You know what needs to be built. We help you build it properly, connect it to your existing systems and get it running reliably in production, using Claude, ChatGPT\u002FOpenAI, Codex or MCP where appropriate. We step in, build, document and hand over, without an open-ended staffing commitment.\n","Build with AI",{},"\u002Fbuyer-triggers\u002Fai-laten-bouwen",{"intro":1114,"points":1115},"AI is only really useful when it works with existing software, data and business processes. We build that as software engineering, not as a standalone demo.\n",[1116,1119,1122],{"title":1117,"text":1118},"Integrations are central to our work","We treat APIs, databases, permissions and existing systems as core parts of the solution, not extras around the AI.\n",{"title":1120,"text":1121},"Reliable beyond the happy path","We also test errors, edge cases and human oversight where needed.\n",{"title":1123,"text":1124},"Production and handover are part of the job","The work is done when the solution is live, documented and manageable for your team.\n",{"useCaseKeys":1126,"offerKeys":1135,"caseKeys":1136},[1127,1128,1129,1130,1131,1132,368,236,1133,1134],"ai-agent-laten-bouwen","interne-ai-assistent-laten-ontwikkelen","bedrijfsproces-automatiseren-met-ai","ai-toevoegen-aan-bestaande-software","eigen-data-en-kennis-gebruiken-met-ai","documenten-en-mails-automatisch-verwerken","agentic-workflows-bestaande-software","tools-vervangen-door-maatwerkflow",[119,65,64],[],{"title":1138,"description":1139},"AI agent development and integration | 9to5 software","Have senior engineers build an AI agent, MCP integration, assistant or automation with Claude, ChatGPT\u002FOpenAI or Codex. From scope to production.\n","buyer-triggers\u002Fai-laten-bouwen","The problem and direction are clear. Now it needs to be built properly, integrated and brought into production.\n",{"hero":227,"proof":341,"approach":341},"ShT4oNEyuY5KbwbXvOuC2vEuCmku084FYvyfv89UAyM",{"id":1145,"title":1146,"approach":1147,"body":1162,"cta":1166,"description":26,"extension":32,"hero":1169,"key":1171,"label":1172,"meta":1173,"navigation":38,"path":1174,"proof":1175,"relations":1187,"seo":1209,"stem":1212,"summary":1213,"visuals":1214,"__hash__":1217},"buyerTriggers_en\u002Fbuyer-triggers\u002Fvastgelopen-met-ai.md","We've already built something, but we're stuck.",{"title":1148,"steps":1149},"We step in, understand, repair and hand over.",[1150,1153,1156,1159],{"title":1151,"text":1152},"Confirm the rescue goal","We establish what is actually going wrong, what is urgent and what needs to be demonstrably better after the rescue.\n",{"title":1154,"text":1155},"Understand the context and code","We examine the code, architecture, data flows, integrations and deployment until the source of the problem is clear.\n",{"title":1157,"text":1158},"Fix and test","We make targeted repairs, add tests, evals and guardrails where needed and check that the solution works under real conditions too.\n",{"title":1160,"text":1161},"Document and hand over","We document decisions, clear critical technical debt and make sure your team can move forward independently again.\n",{"type":23,"value":1163,"toc":1164},[],{"title":26,"searchDepth":27,"depth":27,"links":1165},[],{"title":1167,"body":1168},"Stuck with AI or vibe-coded software?","Briefly describe what you have and where it is going wrong. We'll take a look and quickly tell you what makes sense to repair, keep or rebuild.\n",{"intro":1170},"You don't have to start over just because things have become complicated. We step in, including when you have a vibe-coded app or code generated by AI tools such as Claude Code, Codex or Cursor. We understand what is there, find what is really going wrong and make it technically manageable again.\n","vastgelopen-met-ai","Stuck with AI",{},"\u002Fbuyer-triggers\u002Fvastgelopen-met-ai",{"intro":1176,"points":1177},"Assessing an existing codebase takes more than an automated quality score. It takes senior engineers who can identify the problems that really hurt and make targeted repairs.\n",[1178,1181,1184],{"title":1179,"text":1180},"We work with existing software","A messy or AI-generated codebase is no reason to automatically start from scratch.\n",{"title":1182,"text":1183},"Software engineering and AI","We look at everyday production problems and AI-specific failure modes, such as unreliable output and missing evals.\n",{"title":1185,"text":1186},"Move forward independently again","We document decisions and clear critical technical debt so your team can move forward on its own again.\n",{"useCaseKeys":1188,"offerKeys":1207,"caseKeys":1208},[1189,1190,1191,1192,1193,1194,1195,1196,1197,1198,1199,1200,1201,1202,1203,1204,1205,1206],"vibe-coded-app-professionaliseren","ai-prototype-naar-productie","ai-agent-niet-betrouwbaar","gegenereerde-code-niet-meer-begrijpelijk","ai-code-breekt-steeds","vast-op-auth-database-of-rechten","ai-koppelen-aan-bestaande-systemen","security-en-privacy-ai-oplossing","ai-oplossing-te-langzaam","ai-oplossing-te-duur","tests-evals-monitoring-voor-ai","developmentteam-loopt-vast-met-ai","technische-second-opinion-ai","ai-project-overnemen-van-andere-leverancier","ai-experiment-heeft-echte-gebruikers","prototype-naar-onderhoudbaar-softwareproduct","weg-bij-ai-platform-of-leverancier","vibe-code-project-vastgelopen",[253,249,119],[],{"title":1210,"description":1211},"Stuck with AI? Rescue by senior engineers | 9to5 software","Stuck with an AI agent, prototype or vibe-coded app (Lovable, Cursor, Bolt, Replit)? We analyse the problem, make targeted repairs and restore maintainability.\n","buyer-triggers\u002Fvastgelopen-met-ai","Something is already there, but it is unreliable, hard to understand or technically stuck. We need to get it back under control.\n",{"hero":1215,"proof":1216,"approach":1216},"sq-tangle-knot","ls-rescue-repair","e0bDu3r1P4JqQOadOsQgPsL_EDOsQGpgsqBXrdwFTNw",[],{"id":1220,"title":1221,"extension":1222,"items":1223,"meta":1236,"stem":1237,"__hash__":1238},"why9to5_en\u002Fen\u002Fshared\u002Fwhy-9to5.yml","Why 9to5?","yml",[1224,1227,1230,1233],{"label":1225,"value":1226},"Senior engineering","AI + software engineering",{"label":1228,"value":1229},"Existing software","We step in where it gets complicated",{"label":1231,"value":1232},"Production-ready","Built, tested and reliably deployed",{"label":1234,"value":1235},"Handover","Documented, so you can carry on independently",{},"en\u002Fshared\u002Fwhy-9to5","_iz4GBKRty2Gu5JZKf6tSCRXdwX0sju7lRprYEzQvNE",1792049913916]