GuideTechnology
13 min read
A realistic 30-day plan to put this course into practice with free tools and 30 to 45 minutes a day, followed by a long-term roadmap that builds durable skills such as verification, workflow design and evaluation, and a way to keep up as AI changes without chasing every announcement.
GuideTechnology
13 min read
Fourteen compact, tool-independent recipe cards you can copy into your playbook: study, developer, career, research, productivity and automation. Each card gives the goal, the steps, a prompt template, the checks and the risk level, and links back to the article that explains why it works.
GuideTechnology
10 min read
By now you have habits, prompts and rules scattered across a course. This article turns them into one personal AI operating system: your principles, privacy boundaries, verification rules, tool-selection criteria, a playbook of reusable workflows and a review routine, captured in a one-page manual you can keep and update. No paid tools required.
GuideTechnology
12 min read
Agents and AI workflows fail in predictable ways: wrong tools, compounding errors, endless loops, confident 'done' messages that are not true and hostile content. This article lists the failure modes, then shows how to design for reliability with validation, escalation, approval gates, evaluation sets and staged rollout, including a runnable approval-gate example.
GuideTechnology
11 min read
How can a language model that only produces text check a calendar, search a database or edit a file? Through tool calling: the model asks, your program acts. This article explains function calling, the Model Context Protocol and the agent loop, with a runnable toy loop that shows allowed tools, step limits and what the model never does itself.
GuideTechnology
10 min read
Chatbot, workflow, automation, AI-assisted workflow and agent are often used as if they mean the same thing. They differ in who decides the next step, and that difference drives reliability, cost and risk. This article defines each, compares them on one task and gives a decision method built on one rule: use the simplest system that reliably works.
GuideTechnology
12 min read
Responsible AI use is more than accuracy and privacy. This article explains where AI bias comes from and how to test for it, the main copyright and attribution questions for what you put in and what you publish, why disclosure matters and what human judgment and accountability mean in practice.
GuideTechnology
14 min read
Everything you paste into an AI tool goes somewhere, and everything an AI tool reads can try to steer it. This article covers what never to paste, how to tell consumer from business tools, how to redact, how connected tools widen the risk, and what prompt injection is and how to limit it, with a small runnable illustration.
GuideTechnology
11 min read
A reliable research process uses AI for the parts it does well, such as mapping a topic, suggesting search terms and explaining difficult sources, and keeps you in charge of finding, reading and comparing real sources. This article gives an eight-stage workflow, a source matrix and a citation-checking routine.
GuideTechnology
12 min read
Fluent AI output is not proof of truth. This article gives you a practical verification routine: split an answer into claims, decide which need checking, find primary sources, compare independent ones, check dates, context and numbers, record the source and decide how far to trust it, with special care for health, law, money and statistics.
GuideCareer
10 min read
An AI assistant can be a patient, always-available interviewer: asking questions, probing your answers and giving feedback on structure and clarity. It can also flatter you and mark wrong answers right. This article gives a mock-interview protocol for behavioural and technical rounds, and clear rules about not using AI in the real interview.
GuideCareer
11 min read
Job postings are data. This article shows how to turn a handful of them into a requirements table, compare it honestly with what you can already show, plan a realistic learning path and choose portfolio projects that prove real skills, with AI doing the sorting and you doing the judging and the learning.
GuideCareer
10 min read
AI can sharpen vague resume bullets, point out what is unclear and tailor your wording to a role. It can also invent achievements that you will be asked about in an interview. This article gives a fact-first method for resumes, LinkedIn profiles and applications, with firm lines you should not cross.
GuideTechnology
10 min read
Vibe coding means accepting AI-generated code without reading it, which is fine for a weekend toy and risky for anything that has users, data, money or a future. This article gives a fair account of both ends of the spectrum and a project workflow that keeps the speed while preserving your understanding.
GuideTechnology
11 min read
Generated code that works can still be vulnerable, depend on a package that should not be trusted, or resemble code with a licence you must respect. This article lists the common security weaknesses, shows a SQL injection example you can run, gives a short security review routine and explains licensing questions without pretending to be legal advice.
GuideTechnology
10 min read
AI-written code often passes AI-written tests, because both come from the same assumptions. This article shows how to write tests that check what the code should do, how to use AI as a second reviewer without relying on it, what to look for in AI-generated diffs, and how to refactor safely.
GuideTechnology
9 min read
Pasting an error into an assistant can solve a bug in a minute, or produce a patch that hides it. This article gives a safe debugging workflow: reproduce, share safely, ask for hypotheses, test them, review the fix, add a regression test, with a worked example and a list of dangerous 'fixes'.
GuideTechnology
10 min read
Reading code is the safest and often most valuable use of an AI assistant: nothing changes until you decide it should. This article covers explaining unfamiliar code, mapping a codebase, learning an API or framework, writing documentation and brainstorming architecture, with the checks that catch confident mistakes.
