Prompt & Context Engineering

Claude Code quotas: an OpenAI workaround and the Chinese alternatives in practice

The Prompt Is Not the Beginning

Why a good AI dialogue starts with the right starting point

Your AI Work Profile

What a machine needs to know about you — and why the most useful personalisation does not begin with a master prompt.

Prompt, Context, Intent

The three layers of a useful AI instruction — and why a well-phrased sentence is not automatically a well-formed brief.

When AI starts prompting you

How to read an answer without quietly adopting its direction.

No master prompt replaces a solid data foundation

Why better outcomes usually begin with better materials.

A context window is not memory

Why long chats need a hand-off before they become unclear.

The hand-off

Transfer an AI project without losing information — a small document that turns a conversation back into a workable project.

Turn chat chaos into knowledge

How to turn valuable conversations into a clear working state — without a copy-and-paste marathon.

A second brain for people and models

How a readable knowledge system grows from notes, decisions and connections.

The three-part AI workspace

Why a clear division of roles — workhorse, sparring and source check — leads to better decisions than using one chat for everything.

A second model is not a luxury, but quality work

A first draft does not need blind trust. It needs an independent counter-reading.

The prompt library

From one-off prompts to tested building blocks: why reusable instructions become valuable only when they have a purpose, a test and a version.

Test, don't admire

Positive, negative and repairable AI scenarios: how an impressive answer becomes a working tool you can trust within clear limits.

What a good AI skill really is

Not a personality trait or a decorative title, but a clear, tested capability: what it is for, what it needs, what it delivers and where it stops.

A big job is many small steps

No single prompt finishes a large task at once. Break it into short, checkable steps and you keep quality and overview — and after each step you know whether you are still on the right track.

Five phases, one procedure: AI consulting with the Sakızlı model

A good recommendation does not begin with a fast answer, but with a procedure that keeps uncertainty visible. The Sakızlı five-phase consulting model gives AI consulting that procedure — and puts contractual, legal and regulatory questions at its centre.

The browser plans, the agent builds, the human decides

How a vague idea becomes a responsible workflow when research, execution and approval are kept distinct.

From idea to handoff package

A good start is not a long wish list. It is a small set of documents that makes the goal, boundaries and acceptance criteria unambiguous.

What an agent harness is — and why autonomy needs boundaries

A reliable agent is not made by one prompt. It is made by an environment that keeps its steps visible and stoppable.

How a domain expert becomes a useful tool

A person is not automated; a clear slice of expert work is made accessible to others.

Document so a project still works months from now

Not every decision needs a long explanation. But the next person should be able to understand how an idea became a reviewable result.

Local, cloud or hybrid? A decision architecture for small and medium-sized businesses

The right question is not: Where does the AI run? It is: Which task may go into which environment?

Choose local language models without falling for marketing

The best choice does not begin with a model name. It begins with an honest description of the task, the data and the environment you actually have.

Safe agents: permissions, sandboxes, reviews and the art of saying no

Autonomy does not become trustworthy because a system may do more. It becomes trustworthy when it knows what it may not do.

AI prompts back: how models help shape our judgement

Every answer changes the next thought. Recognising that feedback lets us use AI without surrendering judgement to its linguistic confidence.

When context wears out

Long projects drift not because context is missing, but because no one actively maintains its relevance, provenance and validity.

Automate only what you can verify

The boundary of useful automation is not where a system can act, but where its outcomes can still be checked reliably.

From experiential knowledge to an expert system

Expertise does not become automatable by writing everything down. It becomes usable when decisions, examples, boundaries and exceptions work together in a testable form.

Skills are software

Once an instruction selects tools, reads files or triggers actions, it is no longer merely text. It becomes part of the security architecture.

The hybrid AI architecture

Sovereignty does not come from running everything locally or everything in the cloud. It comes from deliberate routing, bounded hand-offs and dependable ways back.

From personal assistant to team intelligence

Shared AI work does not begin by giving everyone the same chatbot. It begins with shared knowledge, clear rights and visible responsibility.

Beyond the Prompt

The operating system for working with artificial intelligence. A long essay on prompting, context, knowledge, agents, quality and digital sovereignty.

Agentic Operations Kit

A versionable knowledge core that translates the entire article base into agentic work contracts — with platform-specific adapters instead of six diverging tool manuals.