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.