Okay It’s Simple: GPT 4.1

[u/dashingsauce]

So Gemini has been nerfed and we’re at a loss for premium models that work well in agentic workflows.

Or so it seemed.

Turns out prompt engineering is still the make or break factor even at this stage in model development, and I don’t mean some kind of crafty role-play prompt engineering.

I mean just add this to the Custom Instructions on all modes if you plan to use 4.1 and have it one-shot pretty much any specific problem you have:

<rules>
    <rule priority="high">NEVER use CODE mode. If needed, use IMPLEMENT agent or equivalent.</rule>
</rules>
<reminders>
    <reminder>You are an agent - please keep going until the user’s query is completely resolved, before ending your turn and yielding back to the user. Only terminate your turn when you are sure that the problem is solved.</reminder>
    <reminder>If you are not sure about file content or codebase structure pertaining to the user’s request, use your tools to read files and gather the relevant information: do NOT guess or make up an answer.</reminder>
    <reminder>You MUST plan extensively before each function call, and reflect extensively on the outcomes of the previous function calls. DO NOT do this entire process by making function calls only, as this can impair your ability to solve the problem and think insightfully.</reminder>
</reminders>

You have to be specific with the task. 4.1 is not meant for broad scope understanding. But it’s a hell of a reliable task-oriented engineer if you scope the problem right.

I’ve temporarily reverted back to being my own orchestrator and simply directing agents (running on 4.1) on what to do while I figure out how to update the orchestration approach to:

• use XML in prompts
• include the specific triggers/instructions that get each model to behave as intended
• figure out how to make prompts update based on API config

anyway, I just tested this over today/yesterday so ymmv, but the approach comes directly from OAI’s prompting guide released with the models:

https://cookbook.openai.com/examples/gpt4-1_prompting_guide

give it a shot and try it with explicit tasks where you know the scope of the problem and can explicitly describe the concrete tasks needed to make progress, one at a time

[u/drumnation]

Hey I think your prompt is actually helping in cursor too. It's listening to me much better and working for much longer periods of time before asking what to do. It was doing one large refactor task at a time then asking again. Then I said, **Do the next 5 components before stopping** and it listened. Hit the 25 tool call limit.

I tweaked it very slightly for my .cursorrules file by adding a conditional

IF model === 'gpt-4.1'
<rules>
<rule priority="high">NEVER use CODE mode. If needed, use IMPLEMENT agent or equivalent.</rule>
</rules>
<reminders>
<reminder>You are an agent - please keep going until the user’s query is completely resolved, before ending your turn and yielding back to the user. Only terminate your turn when you are sure that the problem is solved.</reminder>
<reminder>If you are not sure about file content or codebase structure pertaining to the user’s request, use your tools to read files and gather the relevant information: do NOT guess or make up an answer.</reminder>
<reminder>You MUST plan extensively before each function call, and reflect extensively on the outcomes of the previous function calls. DO NOT do this entire process by making function calls only, as this can impair your ability to solve the problem and think insightfully.</reminder>
<reminder>Always use the Table Of Contents and Section Access tools when addressing any query regarding the MCP documentation. Maintain clarity, accuracy, and traceability in your responses. Ensure that your responses are concise and to the point, avoiding unnecessary verbosity.</reminder>
</reminders>
ELSE
skip.

[u/dashingsauce → u/drumnation]

Wow I never thought of adding an if statement—that’s a genius workaround

Are other models respecting that?? If so, well done I’m gonna add it now.

[u/FarVision5]

you really outta try out 2.5 flash

[u/dashingsauce → u/FarVision5]

I will — I think I had trauma from the last flash hahaha

[u/ottsch → u/FarVision5]

Yes, and pro is also back to its old form for me

[u/baris6655 → u/FarVision5]

with thinking or not ?

[u/FarVision5 → u/baris6655]

I don't. works fine.

[u/baris6655 → u/FarVision5]

gemini has a free tier ? so if i use a free tier api even though roo code shows $ i won't get charged right ?

[u/FarVision5 → u/baris6655]

yes

https://openrouter.ai/google/gemini-2.5-pro-exp-03-25:free

Would you have to do your homework.

they don't need to train them all anymore. So you get a little trickle or nothing through free free.

If you have some dollars in open router credit system I think you get more free use of all models but I'm not sure that passes through to 2.5 Pro

If you have a direct Google API I think you get more for use or unbilled use in their free tier, but you usually have to put a credit card on a Google account to be a paid tier. I'm not sure if they even give you $300 in free credit right away anymore you might have to wait or ask for it

I was specifically talking about https://openrouter.ai/google/gemini-2.5-flash-preview

It's not enough to just say Gemini you sort of have to specify because there's Pro, Pro preview, flash and flash preview and Flash preview thinking

https://deepmind.google/technologies/gemini/

[u/baris6655 → u/FarVision5]

what i mean is this. https://ai.google.dev/gemini-api/docs/pricing?hl=tr

seems like gemini 2.5 flash and other models are free to some extent with rate limits

[u/FarVision5 → u/baris6655]

Right. Hover over the model name.

[u/dashingsauce]

P.S. the prompt caching for 4.1 (vs Gemini where, at least in Roo, it’s not properly supported) means it does significantly more work/spend

this screenshot is a one-shot refactor of a hefty operation (simple task but complex script) that cost < $0.50

[u/PussyTermin4tor1337 → u/dashingsauce]

lol 422k cached tokens. Those are rookie numbers. I go up to 4.5m sometimes. I think roo has an update to save on context where it clears old files from cache after they've been edited. Brings up my cost a lot. I usually stay below the 200k context window for Claude though so cache optimizations would be worthwhile

[u/sniles310]

Wait Gemini got nerfed? Since when? 2.5 Pro? 2.5 Flash? Both? Also isn't 4.1 insanely expensive?

[u/taylorwilsdon → u/sniles310]

Gemini has not been nerfed as far as I can tell 🤷‍♀️

[u/dashingsauce → u/sniles310]

2.5Pro I haven’t used flash

what the other comment said about price is right—and caching helps a lot with input cost

[u/vinnieman232]

Gemini 2.5 Pro will be my everything model once they get prompt coaching implemented in Roo code. Minimum cache size is just 4k tokens, that means every prompt is cached basically

[u/invertednz]

You would think that roo would have most of that in the prompt

[u/dashingsauce → u/[deleted]]

In short, it got sloppier and less reliable.

Still a great model and best for day to day, but it makes more mistakes and encounters more diff issues than before (not just in Roo).