Notes from our projects.
What we learn building software, AI and automation for clients: migrations, backends, AI workflows and the mistakes worth avoiding.
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How to bring generative AI into your company: a 90-day plan
A practical 90-day plan for generative AI: pick the first process, assign owners, choose tools, run a checked pilot, manage risks, avoid stalling.
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What is an AI agent? A plain-English guide for business teams
What an AI agent is, how it differs from a chatbot and an AI workflow, what it’s made of, and where it’s worth using in an ordinary company.
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What is MCP? The Model Context Protocol explained for companies
What the Model Context Protocol is, how it connects AI apps to your CRM, files and databases, when you need it and what to secure first.
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When to use AI agents, and when a simple workflow is better
Six questions that show whether a task needs an AI agent, an AI workflow or a plain rule, plus the cost trade-offs and the patterns that work.
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RAG explained: how AI answers questions from your own documents
How retrieval-augmented generation works, what makes its answers good or bad, and when it is the right way to give AI your company’s knowledge.
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How to find the first AI use cases worth building
A four-step method to find AI use cases in your company: list repetitive work, estimate the hours, check risk and data, then score and pick one or two.
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What is generative AI? A plain-English guide for business owners
How large language models work, what they’re good and bad at, and where generative AI fits into the daily work of an ordinary company.
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From AI pilot to production: why pilots stall and how to avoid it
Why AI demos impress but pilots stall, what has to change before people rely on an AI system every day, and a checklist for moving a pilot into production.
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AI in HR and recruitment: where it helps and where to be careful
Which HR and hiring tasks AI handles well, why screening and ranking candidates carry legal risk under GDPR and the EU AI Act, and practical guardrails.
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How to measure the ROI of an AI project, with a worked example
Set a baseline, measure time saved and quality, count build, running and review costs, and follow one worked ROI example for an AI project step by step.
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AI, GDPR and the EU AI Act: what a European company needs to know
How GDPR applies when you use AI, what the EU AI Act requires and by when, and the practical steps most small and mid-sized companies need.
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Build or buy AI: when off-the-shelf is enough and when to go custom
When an off-the-shelf AI tool is enough, when a custom build pays off, why most companies end up with a hybrid, and what to ask vendors before you sign.
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Human in the loop: where to keep people in AI processes
Five ways to keep a person in an AI process, how to design a fast review screen, and how to move the line as you learn to trust the system.
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AI in customer support: what to automate and what to keep human
Six jobs AI can do in a support team, which requests to automate first, what to leave to people, and how to measure whether it actually helps.
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How AI agents use tools: function calling in plain English
How a model asks your systems for data and actions, what your code does in between, how to design safe tools, and where MCP fits in.
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What an AI project really costs: build, run and maintain
The three costs of an AI project, typical build prices, a worked example of monthly running costs and the levers that keep the bill under control.
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AI document processing for invoices, contracts and forms
How AI reads invoices, contracts and forms, how rules catch its mistakes, what to leave to a person, and how to test accuracy on your own documents.
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Prompting, RAG or fine-tuning: which one does your AI project need?
Three ways to adapt an AI model to your company: what each one changes, what it costs, and the order to try them in before you train anything.
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Tokens and context windows: why AI forgets and what it costs
What a token is, what fits in a model’s context window, why long chats drift, and how tokens set the price of every AI request.
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AI voice agents for business calls: how they work and where they fit
How an AI voice agent handles a phone call, which calls it suits, what to keep human, Slovak and GDPR questions, and how to run a first pilot.
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AI hallucinations: why they happen and how to design around them
Why language models state wrong facts with confidence, when that’s dangerous, and the design techniques that catch errors before customers see them.
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Self-hosted LLM or API? Privacy, quality and cost compared
Public API, EU-hosted API or an open-weight model on your own servers: how they compare on privacy, quality, cost and effort, and when each one fits.
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AI for B2B sales teams: account research, CRM notes and follow-ups
Where AI saves sales reps real time: call prep, CRM updates from meetings, follow-up and proposal drafts. Plus what to keep human and how to start.
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Multi-agent AI systems: when one agent isn’t enough
What multi-agent AI systems are, when splitting work between agents helps, what it costs, and why one agent with good tools is the better start.
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Getting your team to actually use AI: a 6-week rollout plan
Why licences alone rarely change how people work, and a 6-week plan with champions, role-based use cases and a prompt library that does.
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Writing prompts that work: a practical guide for business teams
The parts of a good prompt, ready-to-copy templates for everyday tasks, common mistakes, and how to tell when a prompt isn’t enough.
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How to write an AI usage policy your team will actually follow
What a short AI policy should cover: approved tools, data rules, checking outputs, disclosure and incidents. With a template outline you can copy.
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Keeping AI agents safe: prompt injection, permissions and audit logs
How AI agents that read emails, documents or web pages can be tricked, and the defences that work: least privilege, hard limits, approvals and logs.
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Bubble to React+Supabase: Migration guide
A step-by-step guide to moving a Bubble app to React and Supabase: when it makes sense, how to redesign the data model, rebuild workflows and plan the cutover.
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Bubble to React+Supabase: Should you migrate?
Compare the work of staying on Bubble with rebuilding in React and Supabase, including maintenance, data, permissions, and team skills.
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WeWeb to React: Migration guide
How to move WeWeb pages, collections, variables, and workflows into a React app while preserving the behavior users rely on.
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Should You Migrate Your Bubble App to Custom Code?
When a Bubble rebuild is worth the cost, when to stay, and what your team needs to maintain a custom codebase.
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Workflows, AI Workflows, and AI Agents
Understand the differences between traditional workflows, workflows with AI steps, and autonomous AI agents, and when to use each approach.
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Bubble workload optimization – how to efficiently build your no-code app?
Bubble now prices by workload units. What consumes them, and how to build your Bubble app so it uses fewer.
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WeWeb & Xano vs Bubble: Which tools should you use?
Why our no-code agency started looking beyond Bubble, and how WeWeb with Xano compares: strengths, limits and when to pick which.
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Xano or Supabase for your WeWeb project?
Xano or Supabase behind WeWeb? A short comparison of learning curve, real-time features, pricing and SQL, with our recommendation for each.
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Xano performance optimization guide
How to improve Xano performance with database indexes, caching, API changes, and asynchronous processing.
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Xano security checklist
Essential security measures every Xano application should implement, from authentication to data protection.
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JurajCEO, QikBuild
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