[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"post-why-we-charge-for-value-not-hours":3,"$fXeC77ibo_YuG-ZnFG3hwyaNC83zFAKw-FvBNoL2JrIM":14},{"slug":4,"title":5,"excerpt":6,"category":7,"author":8,"readingTime":9,"coverImage":10,"bodyHtml":11,"metaTitle":5,"metaDescription":12,"date":13},"why-we-charge-for-value-not-hours","Why we charge for value, not hours","Billing by the hour rewards slowness and punishes experience. Here is why we look at what a solution brings the business, not what it cost us.","How we work","MightCore","6 min",null,"\u003Cp>\u003Cstrong>Billing by the hour rewards slowness and punishes experience: the faster you solve a problem, the less you earn. So we look at the value a solution brings the business, not how many hours somebody sat over it.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>That sounds like a marketing line, so let us take a concrete example — and say where the model has its limits.\u003C\u002Fp>\n\n\u003Ch2>What is wrong with billing by the hour\u003C\u002Fh2>\n\u003Cp>Picture two vendors. One solves a problem in two days, because they have solved it ten times before. The other takes two weeks, learning on your money. At an hourly rate you pay the second one five times more for a worse, slower result.\u003C\u002Fp>\n\u003Cp>It is absurd. That is the built-in perversity of the hourly model: it rewards exactly what you, as a client, do not want. Experience that saves time shows up as a smaller invoice — so there is no pressure on the vendor to be both fast and good.\u003C\u002Fp>\n\n\u003Ch2>What charging for value means\u003C\u002Fh2>\n\u003Cp>Instead of asking \"what did this cost us\", we ask \"what will this bring the business\". If an automation saves an employee twenty hours a month, its value is those twenty hours — regardless of whether the solution took us two days or two weeks.\u003C\u002Fp>\n\u003Cp>For the client there is one big advantage. You know the price up front, and it is tied to the outcome, not to our time. You do not have to watch whether somebody is working slowly on purpose, because our speed is our problem, not yours.\u003C\u002Fp>\n\u003Cp>How this translates into a concrete engagement model is covered in \u003Ca href=\"\u002Fblog\u002Ffixed-price-or-hourly-which-is-better-for-the-client\">fixed price or hourly\u003C\u002Fa>.\u003C\u002Fp>\n\n\u003Ch2>How the value is worked out\u003C\u002Fh2>\n\u003Cp>This is the harder part. We do not pretend it is exact. It comes from numbers we establish at the start: how much time or money the current state costs, how often, how many mistakes happen. That is why, for us, \u003Ca href=\"\u002Fblog\u002Fwhy-context-comes-before-code\">context comes before code\u003C\u002Fa> — you cannot work out value without understanding the problem.\u003C\u002Fp>\n\u003Cp>When those numbers are not available, we say so and look for a model that makes sense to both sides. We never invent a value to justify a higher price — that would be the same dishonesty as working slowly on an hourly rate, just from the other direction.\u003C\u002Fp>\n\n\u003Ch2>Where this model has limits\u003C\u002Fh2>\n\u003Cp>It does not fit everything. For exploratory work, where nobody knows in advance what will work — typically new AI features — the value cannot be set up front, and a transparent hourly rate with a ceiling is fairer.\u003C\u002Fp>\n\u003Cp>The point of the whole approach is simple: we want our interests to line up with yours. When we earn by genuinely helping you, rather than by how long it takes, we are pulling in the same direction. If you want to see what that looks like on a real project, \u003Ca href=\"\u002Fcontact\">get in touch\u003C\u002Fa> or read about \u003Ca href=\"\u002Fpricing\">our approach to pricing\u003C\u002Fa>.\u003C\u002Fp>","Why value-based pricing is fairer to the client than hourly, how the value is worked out, and where this model has its limits.","2026-06-17T00:00:00.000Z",[15,22,28,33,34,40,47,53,59,64,68,73,79,84,88,93,98,104,108,113,118,123,129,135,140,145,150,155,160,165,170,175,180,185,190,195,200,205,210,214,219,224],{"slug":16,"title":17,"excerpt":18,"category":19,"author":8,"readingTime":20,"coverImage":10,"date":21},"how-to-talk-to-a-language-model-prompting-in-practice","How to talk to a model: prompting without incantations","Prompt engineering is not a list of magic phrases. It is the ability to say exactly what you want — which is harder than it sounds.","Guides","7 min","2026-07-08T00:00:00.000Z",{"slug":23,"title":24,"excerpt":25,"category":26,"author":8,"readingTime":20,"coverImage":10,"date":27},"how-to-choose-a-language-model-and-control-costs","Choosing a language model and keeping costs under control","Benchmarks tell you almost nothing useful. What actually decides a model choice, and where the costs nobody predicted come from.","Engineering","2026-06-30T00:00:00.000Z",{"slug":29,"title":30,"excerpt":31,"category":26,"author":8,"readingTime":32,"coverImage":10,"date":13},"programming-in-the-age-of-ai-what-actually-changed","Programming in the age of AI: what actually changed","No, it did not replace developers. But it changed where they spend their time — and not all of those changes are comfortable.","9 min",{"slug":4,"title":5,"excerpt":6,"category":7,"author":8,"readingTime":9,"coverImage":10,"date":13},{"slug":35,"title":36,"excerpt":37,"category":38,"author":8,"readingTime":20,"coverImage":10,"date":39},"ai-modelka-pre-vas-brand-sprievodca","An AI model for your brand: the complete guide","From brief through avatar creation to the first campaign — step by step.","AI UGC","2026-06-16T00:00:00.000Z",{"slug":41,"title":42,"excerpt":43,"category":44,"author":8,"readingTime":45,"coverImage":10,"date":46},"pripadova-studia-cleago","Case study: Cleago — a platform built on context","How we designed and built a solution for Cleago (www.cleago.sk) by first understanding the context and only then coding.","Case studies","5 min","2026-06-02T00:00:00.000Z",{"slug":48,"title":49,"excerpt":50,"category":51,"author":8,"readingTime":9,"coverImage":10,"date":52},"where-not-to-use-ai-and-why-nobody-tells-you","Where not to use AI (and why nobody tells you)","A company selling AI has little incentive to talk about its limits. Let us fix that — these are the places AI simply does not belong.","For business","2026-05-27T00:00:00.000Z",{"slug":54,"title":55,"excerpt":56,"category":7,"author":8,"readingTime":57,"coverImage":10,"date":58},"how-to-spot-a-good-software-vendor-and-the-red-flags","How to spot a good software vendor (and the red flags)","You spot a good vendor by what they do before the contract is signed, not by their portfolio. Here are the signs of trust and the warning signs.","8 min","2026-05-20T00:00:00.000Z",{"slug":60,"title":61,"excerpt":62,"category":38,"author":8,"readingTime":45,"coverImage":10,"date":63},"ai-model-consistent-brand-across-campaigns","A consistent brand with an AI model across campaigns","An AI model can be a brand's steady face — if you handle consistency and transparency the right way. Here is how.","2026-05-19T00:00:00.000Z",{"slug":65,"title":66,"excerpt":67,"category":44,"author":8,"readingTime":45,"coverImage":10,"date":63},"pripadova-studia-produktove-fotky","Case study: 80% less time spent creating product photos","A real example of deploying AI photos in an online store — from brief to results.",{"slug":69,"title":70,"excerpt":71,"category":51,"author":8,"readingTime":57,"coverImage":10,"date":72},"where-ai-actually-fits-in-a-company","Where AI actually fits in a company (and where it is just flashy)","Concrete applications across departments — what works today, what needs preparation, and what is still a demo rather than a tool.","2026-05-06T00:00:00.000Z",{"slug":74,"title":75,"excerpt":76,"category":77,"author":8,"readingTime":9,"coverImage":10,"date":78},"rest-vs-graphql-pre-eshopy","REST vs. GraphQL API for modern online stores","When to choose which approach and what the impact on performance and development is.","Development","2026-04-21T00:00:00.000Z",{"slug":80,"title":81,"excerpt":82,"category":7,"author":8,"readingTime":20,"coverImage":10,"date":83},"fixed-price-or-hourly-which-is-better-for-the-client","Fixed price or hourly: which is better for the client","A fixed price moves the risk to the vendor, hourly moves it to the client. Here is when each fits — and why neither is always the right one.","2026-04-15T00:00:00.000Z",{"slug":85,"title":86,"excerpt":87,"category":51,"author":8,"readingTime":32,"coverImage":10,"date":83},"how-to-bring-ai-into-your-company-first-steps","How to bring AI into your company without wasting the money","Most AI projects do not fail on technology. They fail because nobody said what was supposed to get better. Where to start instead.",{"slug":89,"title":90,"excerpt":91,"category":44,"author":8,"readingTime":9,"coverImage":10,"date":92},"case-study-monolith-to-modular-migration","Case study: from a monolith to a modular architecture with no downtime","An illustrative example of gradually modernising an older application — where every change was risky and maintenance expensive.","2026-04-14T00:00:00.000Z",{"slug":94,"title":95,"excerpt":96,"category":19,"author":8,"readingTime":57,"coverImage":10,"date":97},"ai-agents-and-tool-calling-when-it-makes-sense","AI agents and tool calling: when it makes sense and when it does not","An agent is a model allowed to act. That is interesting and dangerous in equal measure. How it works, and where to be careful.","2026-03-25T00:00:00.000Z",{"slug":99,"title":100,"excerpt":101,"category":102,"author":8,"readingTime":9,"coverImage":10,"date":103},"uctovnictvo-novej-generacie","Next-generation accounting: a platform built on context","A vision of an intelligent layer on top of existing accounting tools.","Accounting","2026-03-17T00:00:00.000Z",{"slug":105,"title":106,"excerpt":107,"category":19,"author":8,"readingTime":9,"coverImage":10,"date":103},"context-driven-development-context-gathering-in-practice","Context Driven Development in practice: how gathering context changes the outcome","The most expensive mistakes come from a misunderstood brief. Here is what the context gathering that prevents them looks like.",{"slug":109,"title":110,"excerpt":111,"category":7,"author":8,"readingTime":9,"coverImage":10,"date":112},"what-happens-in-a-first-software-consultation","What happens in a first consultation, and what you take away","A first consultation is not a sales call. It is an hour spent understanding your problem — and you often leave with a clearer view, even if we never start.","2026-03-11T00:00:00.000Z",{"slug":114,"title":115,"excerpt":116,"category":19,"author":8,"readingTime":32,"coverImage":10,"date":117},"how-to-orchestrate-language-models-in-practice","Orchestrating language models: from one prompt to a system","One prompt is a demo. An application is something else. On splitting work, routing between models, and where to leave ordinary code alone.","2026-03-04T00:00:00.000Z",{"slug":119,"title":120,"excerpt":121,"category":102,"author":8,"readingTime":45,"coverImage":10,"date":122},"digitalising-accounting-e-invoicing","Digitalising accounting: e-invoicing and what it brings","Electronic invoicing and reporting are becoming the standard. What it means for businesses and how to prepare without panic.","2026-02-17T00:00:00.000Z",{"slug":124,"title":125,"excerpt":126,"category":127,"author":8,"readingTime":57,"coverImage":10,"date":128},"what-is-an-llm-large-language-model-explained","What an LLM is: large language models without the mystique","How does a program that predicts the next word end up writing working code? A look at what actually happens inside a language model.","Fundamentals","2026-02-11T00:00:00.000Z",{"slug":130,"title":131,"excerpt":132,"category":133,"author":8,"readingTime":45,"coverImage":10,"date":134},"ako-ai-setri-naklady-na-video","How AI cuts the cost of video content production","Concrete numbers and a workflow for creating AI videos for online stores.","Marketing","2026-02-10T00:00:00.000Z",{"slug":136,"title":137,"excerpt":138,"category":7,"author":8,"readingTime":20,"coverImage":10,"date":139},"why-context-comes-before-code","Why context comes before code","Most software does not fail on the code; it fails because the wrong thing got built. Here is why everything we do starts with understanding the context.","2026-02-04T00:00:00.000Z",{"slug":141,"title":142,"excerpt":143,"category":127,"author":8,"readingTime":20,"coverImage":10,"date":144},"what-is-artificial-intelligence-explained-without-the-marketing","What artificial intelligence is (and what it is not)","The word AI now means everything, and therefore nothing. Here is what is actually behind it, and where technology ends and marketing begins.","2026-01-21T00:00:00.000Z",{"slug":146,"title":147,"excerpt":148,"category":77,"author":8,"readingTime":9,"coverImage":10,"date":149},"vector-databases-and-embeddings","Vector databases and embeddings: how machines grasp meaning","Semantic search sits behind many AI features. Here is what embeddings are and why modern data work rests on them.","2026-01-20T00:00:00.000Z",{"slug":151,"title":152,"excerpt":153,"category":77,"author":8,"readingTime":9,"coverImage":10,"date":154},"trendy-v-ai-vyvoji-2026","Trends in AI development for 2026","What awaits companies in the area of AI agents, automation and infrastructure.","2026-01-14T00:00:00.000Z",{"slug":156,"title":157,"excerpt":158,"category":44,"author":8,"readingTime":45,"coverImage":10,"date":159},"case-study-ai-product-photography-cosmetics","Case study: AI product photography for a cosmetics e-shop","An illustrative example of how AI content replaced repeated photoshoots and brought a consistent visual identity across seasons.","2025-12-09T00:00:00.000Z",{"slug":161,"title":162,"excerpt":163,"category":77,"author":8,"readingTime":9,"coverImage":10,"date":164},"integrating-ai-into-existing-systems","How to integrate AI into existing systems without a rewrite","You do not have to throw away working software to use AI. Here is an approach that adds value step by step, with low risk.","2025-11-18T00:00:00.000Z",{"slug":166,"title":167,"excerpt":168,"category":19,"author":8,"readingTime":20,"coverImage":10,"date":169},"gdpr-a-ai-obsah","GDPR and AI content: what to watch out for","The legal minimum for companies working with AI content and personal data.","2025-11-11T00:00:00.000Z",{"slug":171,"title":172,"excerpt":173,"category":38,"author":8,"readingTime":9,"coverImage":10,"date":174},"virtualne-ai-modelky","Virtual AI models: the future of advertising or a passing trend?","The possibilities, limits and ethics of virtual influencers for brands.","2025-10-20T00:00:00.000Z",{"slug":176,"title":177,"excerpt":178,"category":38,"author":8,"readingTime":45,"coverImage":10,"date":179},"ai-ugc-in-performance-marketing","AI UGC in performance marketing: what works and what applies","How to use AI content in Meta and TikTok campaigns, why creative testing matters, and what AI-labelling rules apply.","2025-10-14T00:00:00.000Z",{"slug":181,"title":182,"excerpt":183,"category":77,"author":8,"readingTime":9,"coverImage":10,"date":184},"llm-hallucinations-how-to-limit-them","LLM hallucinations and how to limit them in practice","Why AI sometimes states nonsense with confidence, and the techniques we use to keep output trustworthy.","2025-09-16T00:00:00.000Z",{"slug":186,"title":187,"excerpt":188,"category":38,"author":8,"readingTime":45,"coverImage":10,"date":189},"co-je-ai-ugc","What AI UGC is and why the whole world is talking about it","An introduction to AI-generated UGC and its impact on advertising and customer trust.","2025-09-15T00:00:00.000Z",{"slug":191,"title":192,"excerpt":193,"category":44,"author":8,"readingTime":9,"coverImage":10,"date":194},"case-study-b2b-eshop-faster-delivery","Case study: a B2B e-shop ready in weeks, not months","An illustrative example of how context gathering and AI execution shortened a wholesale e-shop build — without cutting quality.","2025-08-19T00:00:00.000Z",{"slug":196,"title":197,"excerpt":198,"category":133,"author":8,"readingTime":45,"coverImage":10,"date":199},"ai-v-marketingu-od-experimentu-k-vysledkom","AI in marketing: from experiment to real results","How to move from \"playing with AI\" to a measurable return on investment.","2025-08-06T00:00:00.000Z",{"slug":201,"title":202,"excerpt":203,"category":102,"author":8,"readingTime":45,"coverImage":10,"date":204},"ai-invoice-processing-in-accounting","AI invoice processing: from scan to posting","Intelligent document processing cuts the routine of retyping invoices. How it works and where AI has its limits.","2025-07-15T00:00:00.000Z",{"slug":206,"title":207,"excerpt":208,"category":77,"author":8,"readingTime":9,"coverImage":10,"date":209},"shopsys-vs-vlastne-riesenie","ShopSys vs. a custom build: when a framework pays off","A decision framework for e-shop owners facing the choice of platform.","2025-06-18T00:00:00.000Z",{"slug":211,"title":212,"excerpt":213,"category":19,"author":8,"readingTime":9,"coverImage":10,"date":209},"rag-why-context-decides-ai-quality","RAG: why context decides the quality of AI output","Retrieval-Augmented Generation connects a language model to your own data. Here is how it works and when to use it.",{"slug":215,"title":216,"excerpt":217,"category":133,"author":8,"readingTime":45,"coverImage":10,"date":218},"ako-ai-meni-ecommerce-na-slovensku","How AI is changing e-commerce","Practical examples of AI in product content, search and personalisation for online stores.","2025-05-21T00:00:00.000Z",{"slug":220,"title":221,"excerpt":222,"category":77,"author":8,"readingTime":20,"coverImage":10,"date":223},"context-driven-development-novy-pristup","Context Driven Development: a new approach to building software","An explanation of the CDD methodology from gathering context to deployment — step by step.","2025-04-09T00:00:00.000Z",{"slug":225,"title":226,"excerpt":227,"category":77,"author":8,"readingTime":9,"coverImage":10,"date":228},"koniec-ery-predrazeneho-vyvoja","Why the era of overpriced software development is over","How AI and a context-driven approach are changing the economics of building software — and why paying for inflated hours no longer makes sense.","2025-03-12T00:00:00.000Z"]