Editing Openai/692c52e8-5230-800f-b92b-de25a0fe8d7e (section)

=== User: Critique my near-final draft of my latest LinkedIn post, especially identify any major errors. ===
Critique my near-final draft of my latest LinkedIn post, especially identify any major errors. This is for a legal audience that's not well acquainted with AI. I'm covering tips that (just between you and me) I'm surprised I'm still having to share with people, but folks tell me these are eye-openers.

3 AI Tips for ChatGPT’s 3rd Birthday! 🤖🎂

#1️⃣ PROMPTING FUNDAMENTALS

The 3 simple elements I’ve used for prompts since early 2023:

☝️ ME — Tell the AI who I am, or feed it another persona (like that I’m opposing counsel).

How can AI assist without knowing who it’s assisting?

»Example: “I’m Kyle Bahr, and I help legal professionals make AI work for them.”

⏫ Level-Up: Read prompting guides. Good prompts are structured, similar to well-formed contracts and briefs.

✌️ YOU — Tell the AI who it is, and list its areas of expertise.

Today’s LLMs were trained on nearly the entire Internet. Guide the model on what's important. 

»Example: “You're an expert at Gen AI, prompt engineering, and all related topics.”

⏫ Level-Up: Give the AI top credentials, so it grasps the desired level of expertise: “You’re a tenured Harvard Law professor in....”

👌 STUFF — Give the AI what it needs to succeed at the task. (AI folks call this “context.”)

Instruct, and attach any needed materials. But don’t overload it — AI has a limited memory per chat, so keep a thread to one discrete task.

»Example: “Use you expertise to carefully draft an optimized prompt for AI to help a lawyer analyze a contact based on the attached playbook.”

⏫ Level-Up: Learn about “context engineering,” which focuses on providing context to get better AI responses.

#2️⃣ MODEL MATTERS

When someone says they used ChatGPT, Claude, Gemini, etc., I ask: “Which model?”

The AI makers build and release multiple LLMs, resulting in a confusing — but important — jumble of numbers, letters, and labels (like 4o, Sonnet-4.5 Extended Thinking, 2.5 Flash, etc.).

»Pick the “thinking,” “reasoning,” or “pro” models in your AI app’s model selector.

These AIs are the ones showing human-level capabilities in the benchmarking reports. 

⏫ Level-Up: Be a multi-model user — with many great LLMs available, why stick to one? Many look at the LMArena Leaderboard’s “Text” ranking to identify the best models.

#3️⃣ EFFICIENT ENHANCEMENT

Folks seem to be focused on AI automation, which hands the keys to AI, letting it drive a task to completion.

The problem: AI isn’t perfect. It moves efficiently, but the results may not be reliable, with hidden errors. Consistent reliability takes building, testing, and iterating.

Instead, think AI augmentation. The human holds the wheel, and the AI helps propel by enhancing the work. 

Take legal research. Start with AI jumpstarting an inquiry. The human reads and processes, directs the AI down threads — and continues to analyze the results.

AI may surface sources more quickly than the human alone would have uncovered. Or it might find authorities that would have otherwise remained buried. Working in tandem yields equal or better results, more quickly, if done right.

⏫ Level-Up: Process-map your work. Unpack a workflow (say, contract review or drafting a brief) into discrete tasks. Then determine if — and to what extent — AI can assist with any of those tasks.
🤖⚖️🎉