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

=== Assistant: Here are the big things I’d tighten up and fix, then I’ll give you a clean revised version. ===
Here are the big things I’d tighten up and fix, then I’ll give you a clean revised version.

==== a. Typos in your “STUFF” example ====

: 
* you ➜ your
* contact ➜ contract

I’d also smooth the structure a bit:

: 

b. Overstatement: “trained on nearly the entire Internet”

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For a legal audience, this may read as factually wrong and trigger IP / confidentiality alarms. I’d soften it:
* “trained on huge volumes of public and licensed text, including much of the public internet” or
* “trained on massive datasets drawn from the public internet and other sources”

c. Slightly misleading strength claim

: 

For lawyers who are already worried about overclaiming, this is a bit strong. Benchmarking ≠ dependable legal work. Easy fix:
* “These AIs are the ones often approaching or matching human-level scores on many benchmarks. That doesn’t mean they’re always right, especially in law, but they’re usually your best option for complex reasoning.”

d. Jargon that may lose non-AI folks

A few terms might land as inside-baseball unless you add a 3-word gloss:
* “LLM” – spell out once: “large language model (LLM)”.
* “model selector” – a quick parenthetical: “(the dropdown where you pick which AI model to use)”.
* “LMArena Leaderboard” – lawyers won’t know what this is. - Maybe: “Many people look at public leaderboards like the LMSys / Chatbot Arena ‘Text’ ranking…” - Or just: “Check independent leaderboards and evaluations if you want to compare models.”

Not fatal, but worth one line of clarification.

e. Minor clarity tweaks
* “AI has a limited memory per chat…” – technically “context window,” but your message is right. I’d tweak for accuracy without adding complexity: >
* “Give the AI top credentials, so it grasps the desired level of expertise” – I’d make clear this is about tone and depth, not pretending it’s actually licensed: >

==== You’re already doing a lot right: ====
* The ME / YOU / STUFF triad is sticky and easy to remember.
* The “⏫ Level-Up” call-outs are a nice way to speak to both beginners and more advanced users.
* The augmentation vs automation framing is very strong for a legal audience.

I’d mainly just tighten a couple of long sentences and fix the points above.

==== Use/ignore as you like; I’ve only changed where necessary or helpful. ====

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

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

☝️ ME — Tell the AI who you are (or give it a persona).

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

: 

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

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

Today’s large language models (LLMs) are trained on huge volumes of public and licensed text, including much of the public internet. You still need to guide the model on what’s important.

: 

⏫ Level-Up: Give the AI top-tier credentials as a persona, so it understands the level of rigor and tone you want:

: 

👌 STUFF — Give the AI what it needs to succeed. (“Context.”)

Instruct it clearly and attach any needed materials. But don’t overload it — AI has a limited “memory” (context window) per chat, so try to keep each thread focused on one discrete task.

: 

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

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

AI providers 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.).

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These models are the ones often approaching or matching human-level scores on many benchmarks. That doesn’t make them infallible, especially in law, but they’re usually your best bet for complex reasoning.

⏫ Level-Up: Be a multi-model user — with many strong LLMs available, why stick to one? If you’re curious, check public leaderboards (like the Chatbot Arena “Text” rankings) to see how models compare.

===== Many people focus on AI automation: handing the keys to AI and letting it drive a task to completion. =====

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

Instead, think AI augmentation. The human holds the wheel; the AI helps propel the work.

Take legal research. Start with AI jump-starting an inquiry. The human reads and processes, directs the AI down promising threads, and continues to analyze the results.

AI may surface sources more quickly than a human alone would have uncovered. Or it might find authorities that would have otherwise remained buried. Working in tandem can yield 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 each of those tasks.

🤖⚖️🎉

If you want, I can also help you trim this down to a more “mobile-scroll-friendly” version while keeping the ME / YOU / STUFF + augmentation framing intact.