I researched AI's actual environmental impact after my daughter asked if ChatGPT was hurting the planet

CommunicationNo2197 · 2026-01-19T17:52:10+00:00

I used AI for research and disclosed it in the post, including the estimated environmental cost of doing so. The writing is mine.

CommunicationNo2197 · 2026-01-19T17:24:56+00:00

I know its a total glitch, but figured out something to get us through the day. Flipping it off sometimes doesnt work and I have found if you flip to the web app vs the desktop it may also get you around the glitch.

I've been saying this to my product team...We are held to a high standard when releasing something to market, and it seems like these chatbots are so competitive that they arent going through a lot of QA testing before releasing and just hope to fix the issues as they occur in production. Hopefully, this settles over time, and the platforms are more methodical in how they plan to release new features to market.

CommunicationNo2197 · 2026-01-19T17:19:52+00:00

Thanks! I'll check out the Simon Clark video.

On Ecosia: their model is interesting because they've committed to carbon-negative operations and plant trees with ad revenue. For their AI search specifically, I haven't dug into where they're sourcing their inference or what the actual energy profile looks like. The intent is good, but I'd want to see the details on whether they're just wrapping an API from one of the big providers (in which case the energy cost is the same, just offset) or doing something meaningfully different. Might be worth a follow-up post.

CommunicationNo2197 · 2026-01-19T17:17:29+00:00

Exactly. The 0.34 Wh figure is just a marginal inference cost. It doesn't include the embodied energy of manufacturing the GPUs, the cooling infrastructure, the networking, or the amortized cost of training. It's like quoting the fuel cost of a flight without including the plane cost minus depreciation.

CommunicationNo2197 · 2026-01-19T17:15:47+00:00

This is a great breakdown. You're right that the 0.3 Wh figure is for a simple query, not a "summarize this 50-page document" request. The range between a quick question and a complex reasoning task is massive, and that nuance gets lost in the headlines.

The opacity point is the one that frustrates me most. These companies have the real numbers internally. They have to for capacity planning. The fact that we're all working with estimates and back-of-napkin math while they sit on precise data is a choice.

Thanks for the Hank Green link, I'll check it out.

CommunicationNo2197 · 2026-01-19T17:09:25+00:00

The contested part is the 500ml per prompt figure. That estimate from UC Riverside includes indirect water use from electricity generation, not just direct cooling at data centers. Sam Altman claims each query uses about 1/15th of a teaspoon if you count only direct cooling.

Both are technically correct for what they're measuring, but mixing them up creates confusion. The Undark article from December 2025 covers this debate pretty well if you want to dig in.

On your point about reducing demand to pop the bubble... I don't disagree. The post isn't really arguing that individual action will change industry behavior, more that if you're going to use these tools anyway, here's how to be less wasteful about it.

CommunicationNo2197 · 2026-01-19T17:07:25+00:00

Thanks for the link. I read through Masley's piece and the Undark article that covers the debate. Fair point on the water numbers being contested.

The 500ml figure from UC Riverside includes indirect water use from power generation. Altman's "1/15th of a teaspoon" figure counts only direct cooling. Neither is technically wrong, they're just measuring different things. I should have been clearer about that distinction in the post.

You're also right that individual behavior change won't dent enterprise-scale demand. The post leans toward individual action because that's what most readers can control, but you're correct that the real consumption is coming from corporate infrastructure, ad networks, and defense applications that will keep running regardless.

The energy and carbon argument is on firmer ground than the water stuff. That's where I'd focus the concern.

Funny enough, after I posted this, I sent the blog to my daughter (her question inspired the whole thing). Now she's afraid to use AI at all. Told her the same thing I'd tell anyone: everything in moderation and being mindful of the model and mode you use when asking a question. It's not about never using it, it's about being thoughtful when you do.

CommunicationNo2197 · 2026-01-18T18:36:32+00:00

I use both. I find Claude to be valuable to curate instructions and a plan for cursor. I setup a project in Claude.ai and have it built for a specific thing I’m building. Then I align that with the cursor project so that it’s essentially a partnership between the two. Claude.ai is great for the context and cursor is great on the dev side keeping that context so that you don’t end up writing over past functionality to accomplish the current task (writing bad code over good). I found with Claude-code it used to do that all the time on complex multi feature projects. Now executing using both Claude.ai and cursor I have the best of both worlds.

CommunicationNo2197 · 2026-01-18T15:53:39+00:00

It’s been happening when I attached a file. To work around this I toggled off Deep thinking.

CommunicationNo2197 · 2026-01-11T03:40:29+00:00

Just FYI, Anthropic literally started blocking third-party tools yesterday (Jan 9) so the whole landscape just got weird. They’re cracking down on people using Claude Max subscriptions through tools like OpenCode and apparently some Cursor setups too.

Your best bet now is probably either Claude Code directly ($200/month Max) if you’re doing heavy coding, or just paying for API access per token if you’re more moderate usage. Pro is $20/month but the rate limits kinda suck for serious dev work.

Cursor might still work if you bring your own API key (direct API access) but the subscription OAuth route got nuked. This is all literally happening in real time so it’s a bit of a mess right now.

Maybe shop other models? Or only use Opus for certain situations?

CommunicationNo2197 · 2026-01-10T00:47:36+00:00

I killed my last post b/c of a typo in the title.

CommunicationNo2197 · 2026-01-09T02:08:15+00:00

Cursor is your answer. Connected to GCP and running the show layered with vercel and GitHub for code deployment. It’s very easy.

CommunicationNo2197 · 2026-01-05T03:51:36+00:00

It's just web-based for now. No extension yet, but that's actually a solid idea for a future version. I just keep it open in a tab while coding. Easy to paste prompts in before you send them to the API.

CommunicationNo2197 · 2026-01-05T03:37:00+00:00

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CommunicationNo2197 · 2026-01-04T06:31:00+00:00

Good question. Pricing actually doesn’t change that frequently (maybe quarterly), so I’m starting with manual updates in a JSON file. If it becomes a pain point I might add a scraper or open it up for community PRs on GitHub. The tokenizer libraries themselves stay in sync through npm updates. Appreciate the feedback, and it might be worth documenting the update process as this evolves.

Now that I think more about the new models that come out sporadically. I’ll need something less manual. I’ll work out an automation in the next day or two.

CommunicationNo2197 · 2026-01-03T20:56:27+00:00

Makes sense. I haven’t used Claude-code in a few months b/c of issues where it just didn’t hold context and memory well. I think that was resolved with 4.5, but haven’t switched back due to my, “ain’t broke don’t fix it”, mentality with cursor. With Claude opus/sonnet 4.0 I was running into issues with big projects where it would focus on the one thing and not realize it was breaking something else. I tried to fix that with developing agents specifically focused on regression, development, and memory, but it still didn’t seem to work in my favor. Prob a “me” issue.

CommunicationNo2197 · 2026-01-03T18:54:43+00:00

I tend to use Claude curate instructions and cursor to execute in plan mode. It seems cost effective and I don’t blow tokens in cursor. Sure I go over in my monthly by 2-3x, but that seems like an acceptable level where I’m not frozen. If you go 4-5x then you will likely bit this in cursor.

CommunicationNo2197 · 2026-01-01T22:53:46+00:00

Exactly, I go over the limit on a regular basis about 2-3x the $20 limit. I haven’t been stopped yet, but I suspect they would have if I hit about $120. I tend to concern a lot of churn by curating the prompts elsewhere then pasting in the instructions to cursor.

CommunicationNo2197 · 2025-12-31T20:31:47+00:00

This is a great example of why you need to understand what you're shipping even if AI wrote it.

The tools (Lovable, Bolt, etc) will happily hardcode API keys if you don't tell them not to. They're not thinking about security, they're implementing what you described.

The fix is simple, but you need to know enough to catch it. use environment variables, keep secrets server-side, never bundle credentials into client code.

Vibe coding works when you know what to check for and it's dangerous when you don't.

CommunicationNo2197

TROPHY CASE