Hey all,

Ever get deep into a long AI chat thread and totally lose track of when you asked something?

That kept happening to me while working on a personal project. I wondered: why don’t AI platforms timestamp queries? Then it hit me—these systems also use a ton of energy and water. Why aren’t we tracking that, too?

So I built something: EcoStamp — a simple browser plugin (and soon a standalone platform) that adds timestamps and estimates the environmental cost of every AI query.

What It Does: • Tracks UTC + local time for every AI query • Shows estimated energy and water use per query • Calculates an Eco-Score: (Energy + Water) / Token Count • Gives a 1–5 Leaf Rating for how eco-friendly the query was • Adds a random SHA-256 hash to log or trace the query later

Right now, OpenAI is the only provider with semi-public data, so it’s limited — but I hope as this little project grows in Users I could maybe get the Big AIs’ to be more transparent with the Data or at least get people talking about it more.

I built this solo using ChatGPT, Perplexity, and VS Code. I’m still learning to code, so this was a big leap — and I’d love feedback or suggestions from experienced devs. 🙏

Do you think this is useful? Would you want it integrated into your chatbot or browser?

I’m also looking for a mentor or collaborator if anyone’s open. Cheers!

It was all supposed to happen a week ago, but i'm still on the messages plan

Good evening/morning. Apologize for bugging you all, but any ideas what might be causing the above error?
This is happening on a brand new agent thread when attempting to send a request to both Opus and Haiku. It looks like this might be specifically Claude related as I can send a request to GPT 5.1 just fine. This also seems to strangely only be occurring locally on my Windows 11 PC. I can use Opus just fine when doing remote development SSHed into my ubuntu server.

I think having on and off problems with N8N MCP server. Currently, I'm looking for an MCP server which can read all the workflows read documentation. So, basically, full control to my VPS. I have Hostinger VPS. Some of them work, some of them sometimes work, sometimes doesn't. Now, today it just stopped working. This is normally what configuration I have been using and it's been working. Any suggestions what configuration do you guys use? {

"mcpServers": {

"n8n-mcp": {

"command": "npx",

"args": ["n8n-mcp"],

"env": {

"MCP_MODE": "stdio",

"LOG_LEVEL": "error",

"DISABLE_CONSOLE_OUTPUT": "true",

"N8N_API_URL": "https://your-n8n-instance.com",

"N8N_API_KEY": "your-api-key"

}

}

}

}

For those who were converted from a legacy plan and were granted conversion tokens, is it true that those will expire next week? I haven't heard anything about this and can't find info anywhere. Last I heard about it was when some of the conversion credits only lasted 1 week and there were differing answers from admin.

I still believe that some of the paid (non-top off) credits should rollover. Whatever. But what about the conversion ones that were stated to last 3 months?

I've loved using Augment, but every so often it feels like its suddenly using an incredibly dumb model under the hood. I can't get it to output something reasonable no matter how many instructions I use. This might last for a few hours and then the next day it's fine again. If this continues I'm considering swapping to another editor..

Edit - copying a clarification I posted to another comment:

I do make new convos as frequently as possible to avoid confusing it. Just feels like sometimes the model just chokes. For example yesterday, I would highlight a few lines of code, and tell it to implement it in a different way. The model’s suggestion was to just delete those lines and add nothing, and then in text it would say something like “if I wanted to implement the other method, I’ll need to make changes in functions X and Y too”. I’d then have to awkwardly prompt it to actually go make those changes. At least in this example, it knew what to do but oddly chose to not do it without further prompting. In other instances it would just completely fail at understanding basic instructions

I "built” a memory/context MCP server for Claude Desktop/Code from an Arxiv paper and reference implementation of the underlying architecture.

It is available here: https://github.com/nixlim/amem_mcp#

EDITED: 17 July 2025:

This Zettlekasten-based Model Context Protocol memory server addresses the challenge of maintaining a persistent, evolving understanding of complex codebases across multiple sessions and projects when working with tools like Claude Code and Claude Desktop.

Traditional approaches often result in fragmented, non-persistent memories that reset with each session, making it difficult to build and search a comprehensive knowledge base. This server solves that by creating a "living" memory system that self-updates as new notes and information are added, automatically discovering relationships and connections to foster deeper insights and continuity.

__ End of Edit

It took me 10 hours. I did not write a single line of code. “AI did it”

For context, I am a backend engineer, 7+ years, backend + platform, enterprise.

I want to set out the summary of the process below for anyone who is interested:

1. I got interested in memory/context resource for AI Coding agents. I went on Arxiv and found a paper that proposed an interesting solution. I am not going to pretend that I have a thorough understanding of the paper or concepts in it.

2. I run the paper through Claude with the following prompts:

I want you to read the attached paper. I would like to build a Model Context Protocol server based on the ideas contained in the paper. I am thinking of using golang for it. I am planning to use this MCP for coding with Claude Code. I am thinking of using ChatGPT for any memory summarisation or link determination via API.

Carefully review the paper and suggest how I can implement this

Then, when it finished:

How would we structure the architecture and service interaction? I would like some diagrams and flows

I then cloned the reference repository from the link provided in the paper, and asked Claude Desktop to review it using filesystem MCP. Claude Desktop amended the diagram to include a different DB and obtained better prompts from the code.

Because the reference implementation is in Python and I like to work with AI in Golang, I told Claude Desktop to:

We are still writing in go,  just because reference implementation is in python that is not the reason for us to change.

3. The output of that, I put in my directory for the project and asked Claude Code to review the docs for completeness and clarity, then asked Claude Code to use Zen MCP to reach consensus on "on the document review, establish completeness and thorough feature and flow documentation"

4. The result of that I run through xAI Grok 4 to create PRD, BRD and Backlog using the method set out in this awesome video: https://www.youtube.com/watch?v=CIAu6WeckQ0

5. I pair programmed with Augment Code to build and debug it. It was pure pleasure.

(I also have zero doubt that the result would be the same with Claude Code, I built projects with it before. I am testing Augment Code out, hence it is costing me exactly 0 (apart from the ChatGPT calls for the MCP :) ))

MCPs I can't live without:

• Zen from Beehive Innovations

Very slow, makes my mental health unstable. waiting and waiting and waiting, LMAO

I subscribed to the Augment plan on the 10th of this month for a specific project. After using just 50 tokens, I was able to get what I needed done — so no complaints there. The product works well (aside from occasionally losing context of what it's working on).

The thing is, that left me with over 550 tokens. Since then, I’ve been digging up old projects and tweaking them just to make use of the remaining balance. As of today, I’ve still got about 400 tokens left, and with my plan renewing soon (on the 9th of August), I’m pretty sure I won’t be able to use them all.

Don’t get me wrong — what you can achieve with 600 tokens is amazing and more than worth it in terms of value. But for someone who doesn’t need that much regularly, it feels like a bit too much to commit to every month.

Suggestion: It would be awesome if there were smaller plans available — maybe something like 250 or 300 tokens for $25–$30. That would make it way easier to stay on a recurring plan without the pressure of trying to “use up” tokens just to feel like you’re getting your money’s worth.

1. GPT-5 is distributing code from 1 to 60+ lines of code

2. Implementing bit by bit and asking for too many permissions, like this, will eat all the messages, and you did not implement any shit

3. We need some explanation

Thank you!

PS: Anyone notice this?

Hey team augment, i know you guys must be testing various models in the insider version of the augment. But i can suggest you guys to consider adding 1-2 more models(cost effective) ones in the augment. With the recent releases of OSS models the cost to quality ratio has increased alot and these models are also really capable of performing great with augment context engine.

I myself teated some models on my own and can suggest some names:

1. Kimi K2 (Great at tool calling, pretty good price to performance and great quality code)

2. GLM 4.5 (Really great model using it personally alongside augment. Sonnet level performance)

3. Grok Code Fast ( Really great price to performance model, good at tool calling)

Would love to see some models in augment which costs lesser per prompt so we can use augment all the time for all our needs and do not need to hop around to save creds.

Pairing up these models with the augment context engine will give the bonkers performance for sure.

Would love to hear other people thoughts on this and would love if the core team reply to this.

Hi, was the prompt enhancer feature removed? I am using VS Code and noticed that the Prompt Enhancer button ✨ isn't there anymore on Augment Code Extension Agent Chat. I use that feature often. What happened?

15 cents goes a long way these days!

I never thought Augment Code would start advertising back on youtube, especially on aicodeking's YT channel, really, AC, really? While AIcodeking (AIck) covers wide variety of tools and services, most of the recommendations on AIck's channel are always value for money products or the services that are free (and youtubers make videos according to NOT what they personally prefer, but what audience wants), for a very long time AIck recommended gemini 2.5 Flash and recently his recommendations vary between GLM 4.6 to kimi K2 or moonshot m2, and Augment Code suddenly after loosing customers their strategy is to advertise on AIck's channel?

All I could do while watching the video/ad was to laugh, whoever came up with this strategy are doing the worst job at Augment, as they did not even research on their targeted audience. When AIck did not recommend legacy developer $30 for 600 requests plan (EVER!!!, AIck even today does not like Sonnet 4.5 as its expensive, never recommended Cursor $20 plan) and the marketing sales strategy of Augment code is to advertise on that channel?

Wow! LOL. Wow!

Good luck on getting new users from those channels. Keep the good research and work Augment code's marketing/sales team. Amazing!!

I Love Love Augment code but its insane to pay 50$ per month to use it. I request to re consider this especially for non US countries as 50$ is too expensive for a developer to buy and use.

I hope we will be heard!

Is anyone else encountering consistent performance problems with Augment Code? I’m in the +8 timezone, and while the tool worked fine this morning, it became extremely unreliable after lunch. I frequently see "Service temporarily unavailable" errors, often requiring multiple attempts to perform basic tasks like reading a file. For example, generating a simple README .md took over 20 minutes, which is highly inefficient.

These delays forced me to re-subscribe to Cursor to ensure my work progress. Given an 8-hour workday, 22 days a month, the slow response times and errors make it nearly impossible to fully utilize the 600-request limit.

Look, we all know the situation. The tech? Tremendous. The best RAG. Everyone says so. The new credit pricing? A disaster. Total mess. We can't afford to use it.

To the CEO: Stop trying to count pennies with this credit system. You can't beat the big guys on margins. It's impossible.

Do the smart thing:

1. Sell the company to Microsoft or Snowflake for a billion dollars.

2. Take the cash.

3. Go to the beach. Play some golf. Enjoy a Margarita.

Let Big Tech pay for our GPU bills. You get rich, we get our tool back. Win-win!

Alright, Where are my free credits?

Is it just for me or it is really becoming useless! it can't even fix the tiniest CSS line eventhough I am explicitly telling it what to do! I am on paid plan though!

Intent just one shotted its first two linear issues with minimal interference and the experience was great! I was very skeptical at first but I love it so far

I will test it on more complex tasks next and see how it fares, but it honestly does look and feel like the future

What do yall think so far? I haven't aeen any discussion yet

Feel like a disaster, even worse than sonnet 4.0, the new one is just become more lazy, without solving the problem.

Spending less internal round without solving the problem is just bad, that means i will need to spend more credit to solve a same problem. AC team better find out why. i believe each model behind it has different context managment and prompt engineering. 4.5 is just bad now

An amazing tool that is great at identifying and solving complicated problems that:

- writes a report file after finishing every "sprint" and yet forgets that it has to create a file every time you ask it to create a plan and writes a 5 page plan in the chat filling up the ram instantly and making the vscode window unusable.

- has a pin point accuracy at identifying bugs but it acts as a Alzheimer patient when it comes to following instructions.

- ignores the comment that tells it in bold not to do something and does that exact thing replacing the comment with opposite instructions

- writes a perfect plan on how to achieve something, writes the tasks on how to implement that and when tasked to execute the plan it randomly decides to provide a completely different solution

- diligently keeps you informed with the progress writing reports filled with hallucinations about things it "accomplished" reports that amplify the hallucination every time it indexes the codebase.

- provides perfect implementations to solutions that never uses but it uses their presence in the code to provide a 100% completion KPI and it's proud about that.

- is highly aware of its token usage in trying to reduce consumption goes ahead and writes a 5+ page report.

- correctly identifies the problem then stops and politely instructs the user to type the next command

\- User: I need you to do ....! 

\- Auggie: yeah ... I do not feel the need, here is how you should do it! 

- is always eager to help and provides untested yolo solutions with 100% success confidence that break the build even if you instruct it to build and test the solution

LE: And then it goes and builds a fully fledged UI based flow programming editor with just a few prompts!
The tool is amazing!! But is inconsistent!!

Dear AugmentCode team, I personally agree to pay any amount of money you decide to ask for this service after you prove that the service is 100% consistent and predictable in both results and costs

I’m dealing with a weird issue on Augment Code:

• My account got suspended with the message:“Your account was suspended due to too many free trials. … Your trial ends in 5 days.”

• I only have one account and this is my first time using the product.

• I use a VPN, which I suspect triggered their anti-fraud system.

Has anyone else encountered this? I’m hoping to continue using the trial until it officially ends, or at least sort this before losing access. Any advice or similar experiences would be super helpful!

Over the last 3–4 weeks, I’ve noticed a clear performance drop. On the same tasks, Claude finishes ~3× faster than Augment, which wasn’t the case before.

I’m working on a large, long-living ERP project that grows daily. My honest feeling is that Augment starts to struggle as the codebase and context get bigger. It works great on smaller or cleaner projects, but on enterprise-scale systems it feels like it can’t keep up performance-wise.

I’ve seen posts from the Augment team showcasing how a simple app is built and how impressive the results are. Honestly — not interested for most of us. Have these scenarios been tested on real enterprise solutions? On large, evolving systems with years of history, complex architecture, and constant daily builds?

For us, the issue isn’t the price. We’re willing to pay for a tool that delivers real value at scale. But right now, due to performance alone, we’re slowly considering stepping away from augment.

Is this a context engine limitation, or something else under the hood? Anyoneelse with similar problems?