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32 articles · Practical guides, tutorials and ideas
AI models helped find two unauthenticated remote-code-execution flaws in PHP’s core engine, the runtime behind up to 70% of websites. Attacks began within minutes. What happened, why npm and PyPI face the same pressure, and what every team should change.
Separate orders, payment attempts and bank settlements so duplicate returns, delayed results and refunds remain explainable.
Build a usable stock register, separate sales from adjustments, and use a simple replenishment worksheet before automating your shop.
A practical decision worksheet for small businesses moving from separate spreadsheets to connected purchasing, inventory and sales records.
Separate being discovered from taking orders, accepting payments and fulfilling them. Start with one complete customer journey.
A practical visibility checklist for shops and services: accurate details, useful descriptions, real evidence and a clear way to contact you.
Follow the official registry process, choose an appropriate name and keep the domain under the right owner’s control.
Compare setup, transaction, refund and settlement terms without relying on a universal merchant fee percentage.
Understand the documented ePay return and verification flow, then prepare an account-specific implementation and test plan.
Prepare the server-side boundaries and failure tests for KPG-2 without mistaking a browser return for final payment evidence.
Explain what you do, where you work and how to contact you—without keyword stuffing, fake claims or unclear service promises.
A practical comparison framework for writing, coding, research and everyday work, with official plan references and a repeatable evaluation worksheet.
Understand the difference between an occasional-use plan and a recurring work budget, and avoid confusing a chat subscription with metered API usage.
How to evaluate Google AI Plus and Pro alongside your existing storage and productivity needs, without treating a promotional price as a permanent budget.
Why an effective monthly price is different from a monthly charge, and how to decide whether a longer AI subscription commitment suits your workload.
A source-checking workflow for choosing a research assistant, including a comparison worksheet that measures citation quality rather than answer length.
Understand why a free consumer chat app and a metered developer API need separate cost calculations, with a practical checklist for an application prototype.
How retrieval gives an AI application useful context — and how to build a small retrieval baseline before adding a vector database.
A fixed process and a tool-using agent solve different problems. Here is how to choose, with a practical support example.
A practical evaluation plan for Devanagari, Romanized Nepali, mixed-language questions, numbers and local context.
Tokens, training, context and generation explained through a small support-assistant example — including where confident mistakes come from.
Understand how an AI application connects to useful tools and information — and which responsibilities the protocol does not take over.
Replace magic phrases with a repeatable method for writing instructions, showing examples and checking whether a prompt improved.
Build a small, repeatable evaluation set that checks useful outcomes, factual support, boundaries, latency and cost.
A small server-side example with input validation, a timeout and clear errors — plus the steps needed before exposing it to users.
Understand pgvector with a disposable database, a tiny dataset and an explicit distinction between example vectors and real embeddings.
A practical method for finding unnecessary context, retries and repeated work without sacrificing the quality users depend on.
Choose an achievable first workflow, protect business data and measure the result before adding more automation.
Build foundations, use open learning resources and finish a small project you can explain — without chasing every new model.
Spreadsheets break down when VAT rules, party credit balances, and intermittent connectivity collide. Here is why we architected KhataIN around the real daily rhythms of Nepali business.
Resumes describe history; coding challenges test rote memorization. How Codexpal Learn calibrates real problem-solving, architectural judgment, and verified skill signals.
Modern tech websites love buzzwords. At Codexpal, we believe that serious engineering is clearest when explained in plain human language.
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