Solution design: LLM, RAG, agent, or no AI at all

Three ways to see it

1. 1

   Option zero: no AI. A spreadsheet macro, a checklist, a shell script, or a junior employee given two hours. Many Pakistani 'AI projects' are actually 'we never wrote a checklist' projects. Before reaching for a model, audit whether process or training would solve the same pain at a tenth of the cost. The honest answer is sometimes yes. The wing-commander who finally writes a one-page SOP for their inspectors saves more time than a six-month LLM pilot.

2. 2

   Option one: a plain LLM call. Send a prompt, get an answer. Use when the knowledge needed is already inside the model's training data and the answer fits in one response. Drafting a standard memo, translating Urdu to English, summarising a publicly known company are all plain-LLM tasks. The architecture is one API call, the cost is pennies per call, and the build time is a day. The risk is hallucination on anything domain-specific. Plain LLMs do not know your internal data; do not ask them what is in your filing cabinet.

3. 3

   Option two: retrieval-augmented generation, or RAG. The model is paired with a search index over your own documents. When the user asks a question, the system first retrieves the most relevant passages from your documents, then asks the model to answer using only those passages, with citations. Use when the knowledge lives in your own corpus: every Pakistani internal policy library, every NEPRA tariff archive, every internal contract repository fits here. RAG keeps the model honest by anchoring it to evidence, and the citations let an auditor verify the answer. Build time is one to four weeks, depending on how clean your documents are.

The why-tree

Try this with Claude

AI-edge prompt to try with Claude or ChatGPT: 'My candidate problem is summarising 16 tax returns per day at the FBR policy wing. Evaluate plain LLM, RAG, and agent architectures. For each, give me a one-paragraph honest assessment of fit, two reasons to choose it, two reasons to avoid it, and a rough four-week build plan if chosen. Output in English with Urdu summary.' Challenge every claim.