ALGOV INSIGHTS / 30 GUIDES
Better questions.
Better decisions.
AI is changing how software is built. We help separate genuine opportunities from promises and choose solutions that make sense for your business.
From your first automation to developing your own product. Explore examples, decision criteria and checklists to use with your team. Start with the question holding you back today.
CHOOSE A STARTING POINT
What would you like to change?
Improve everyday work.
Find the right first process and see whether the investment pays off.
Start with automation ↗02 / YOUR OWN PRODUCTBuild something people need.
Validate your idea, focus the scope and reach users sooner.
Plan your MVP ↗03 / BETTER AIGo beyond a good demo.
Get your data, permissions and measurable quality right.
Explore quality basics ↗ALGOV LIBRARY
Find your next step.
Results: 30 of 30
01 AI Strategy / 4 min
Where to start AI automation in a company?
The first AI project should solve a problem that the team recognizes without a presentation. See how to select a process, calculate the starting point, and plan a pilot that provides a basis for decision-making.
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02 AI Strategy / 4 min
How to calculate the ROI of an AI implementation without '10x' promises?
Model cost is only one line item. We show the calculation that accounts for quality control, integrations, maintenance, and the actual utilization of saved time.
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03 AI Strategy / 4 min
Ready-made AI tool or a dedicated solution?
A subscription may be sufficient. Sometimes you need integration, and sometimes you need your own product. The decision should be based on the process, data, and the cost of exiting the solution.
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04 AI Strategy / 4 min
AI Pilot: How to move from idea to a deployment decision?
A pilot is an experiment with acceptance criteria. We explain what materials to prepare, who to involve, and how to avoid a prototype that never gets used.
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05 AI Strategy / 4 min
AI Strategy in the Enterprise: A Roadmap Instead of a Tool List
Ten independent experiments can create ten new problems. Build a plan that aligns business goals, data readiness, and process accountability.
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06 AI Strategy / 4 min
Why isn't the team using AI? A plan for effective adoption
Access to a tool does not mean a change in how work is done. Find out what is blocking users and how to implement AI without adding another obligation to their workload.
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07 AI Technology / 4 min
AI Assistant in the Enterprise: From Good Prompts to Quality Control
A prompt helps define the model's behavior. A useful assistant also requires reliable data, tests, permissions, and a method for handling situations where it does not know the answer.
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08 AI Technology / 4 min
AI agent or workflow? How to choose the right level of autonomy
Not every process requires an agent that independently selects the next steps. We compare a controlled workflow with autonomy using the examples of handling inquiries and preparing quotes.
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09 AI Technology / 4 min
RAG in the enterprise: how to build an assistant that leverages your knowledge
Connecting a file catalog is just the beginning. A useful RAG system requires order in documents, accurate retrieval, updates, and access control for every source.
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10 AI Technology / 4 min
MCP in practice: what does the AI agent integration standard offer?
MCP organizes the connection between AI applications and tools and data sources. However, it does not replace business rules, permissions, or good integration design.
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11 AI Technology / 4 min
Context engineering: why a longer prompt doesn't always help
The model needs information relevant to the task. See how to organize instructions, history, and data instead of adding everything to one increasingly long message.
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12 AI Technology / 4 min
How to choose an AI model for your product? Quality, cost, and response time
Model rankings do not know your documents or your customers' expectations. Prepare a comparison that leads to a choice suitable for a specific task.
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13 Products and integrations / 4 min
An MVP that answers business questions
The first version of the product should help make the next decision. See how to limit scope without removing value and plan an experiment with real users.
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14 Products and integrations / 4 min
Does AI accelerate developers? How to measure the impact in a team
More generated code does not necessarily mean faster product delivery. See how to account for review, fixes, deployment, and maintenance.
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15 Products and integrations / 4 min
Legacy modernization with AI: how to evolve a system without a major rewrite
AI can help understand older code. The decision to modernize still requires boundaries, behavioral tests, and a data migration plan.
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16 Products and integrations / 4 min
CRM and ERP Integration: What to Define Before Connecting APIs
The technical connection may work, yet the data may still not match. The most critical decisions concern responsibility for records, exceptions, and reprocessing.
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17 Products and integrations / 4 min
A B2B platform that customers want to use: scope of the first version
Business customers are not looking for another login account. They want to know the price, availability, and order status without waiting for a sales representative's response.
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18 Products and integrations / 4 min
Discovery before app pricing: what you pay for and what should be delivered
Good analysis limits the unknowns that later turn into costly changes. It should end with materials for decision-making, not just a presentation.
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19 Quality and security / 4 min
Evals: How to test AI quality before changing the model or prompt
Manually checking a few responses will not reveal what broke elsewhere. Build an evaluation set that corresponds to the tasks and the consequences of errors.
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20 Quality and security / 4 min
Prompt injection: why a document cannot issue commands to an agent
The assistant reads emails, files, and web pages. Not every piece of content it encounters should influence its operating rules. We explain the boundaries of trust in a practical project.
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21 Quality and security / 4 min
Permissions in the AI assistant: who can see which response?
A corporate assistant should not become a shortcut to data outside the user's role. Plan access in search, memory, history, and operations.
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22 Quality and security / 4 min
Human in the loop: how to design meaningful approval of AI actions
The “approve” button does not provide control if the user does not know what they are approving. Show the difference, the consequences, and the data needed for the decision.
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23 Quality and security / 4 min
AI Monitoring in Production: What to Observe Beyond Server Errors
An application may respond technically correctly while simultaneously failing to assist the user. Correlate infrastructure status with task quality and the cost of its handling.
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24 Quality and security / 4 min
AI costs in production: how to avoid surprises after the pilot
A small test does not yet reveal how the system behaves under high traffic. See how to plan the budget for retries, long-running tasks, and atypical users.
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25 Experience and growth / 4 min
SEO, GEO, and AEO in the AI era: what is truly worth doing on your website
New acronyms do not change the fundamentals: the user and the search engine must understand what you offer and why it is worth trusting you. Start with content, structure, and technical accessibility.
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26 Experience and growth / 4 min
Lighthouse and Core Web Vitals: A fast page beyond a score of 100
A high test score is useful, but the client uses a real phone and network. See how to combine aesthetics, animations, and efficient task completion.
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27 Experience and growth / 4 min
AI application accessibility: forms, streaming, and motion control
Accessibility starts with the ability to complete a task. In AI interfaces, long responses, changing statuses, and the need to refine results add complexity.
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28 Experience and growth / 4 min
AI in customer service: start with agent assistance
The greatest value does not always come from a public chatbot. An internal assistant can shorten information retrieval, organize a ticket, and prepare a response for review.
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29 Experience and growth / 4 min
Document automation with AI: from PDF to verified data
Reading text does not end the process. A company needs data in the appropriate format, with completeness control and secure transfer to the system.
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30 Experience and growth / 4 min
UX for AI products: trust is built through control, not just a chat window
Chat can be a good starting point, but not every task is best handled through conversation. Design the entry point, preview, correction, and completion of work around the user's goal.
Read articleHOW WE CREATE CONTENT
Knowledge you can verify.
The ALGOV team prepares these guides using research and AI tools. We combine source materials with practical project scenarios, give context for research data and distinguish illustrative calculations from actual project results.
These educational materials are a starting point for a conversation about your process. We define scope, requirements and expected outcomes individually. Each article lists its sources and update date. Have feedback or a topic to suggest? Email hello@algov.pl.
LET'S TAKE THE FIRST STEP
Let's discuss
your project.
You don't need a finished specification. Tell us what you want to improve, and we'll find the right place to start together.
- We'll find where technology can bring you the most value.
- We'll discuss scope, budget and a practical plan.
- We'll agree on a clear next step, with no obligation.