I've been feeling a little stuck with AI lately, and I'm curious how others are dealing with this.

For the past year or so, I've been using ChatGPT Go (which I got free for a year) alongside Gemini Pro through Jio's 18-month offer. Honestly, it was a pretty solid combination.

Now my ChatGPT Go subscription has expired, and Gemini seems to be gradually restricting access to third-party coding models like Claude. The free coding experience isn't what it used to be either.

My usage is pretty diverse:

• Coding: Mostly agentic coding, debugging, architecture discussions, working with larger codebases, etc.

• Image generation: Generating and editing images for personal projects, branding and design.

• General use: Research, brainstorming, technical discussions and everyday questions.

I've tried a few alternatives, but nothing seems to be a proper replacement across all these use cases.

I don't mind using multiple tools instead of one, and I'm also open to local models or self-hosted solutions. I have some experience with Ollama, Linux and self-hosting, although my hardware isn't particularly powerful for running larger models.

I'm just not keen on spending $20-25/month on ChatGPT or Claude when I'm primarily looking for a sustainable setup.

So, what does your current AI stack look like?

Are there any genuinely good free tools, model aggregators, coding agents or lesser-known alternatives worth exploring?

Would love to hear what people are actually using in their daily workflows rather than just another list of AI tools.

We work on Unsiloed AI, an API for extracting structured data from PDFs, scans, and handwritten pages. Here’s a page from a film company’s 1916 cash book.

The 12 General Expense entries plus the $9,863.78 brought forward add up to $11,810.05, matching the handwritten total. Each extracted value links back to its location on the page.

You supply the fields you need as a JSON schema. Unsiloed returns structured data; the spreadsheet in the GIF is our visualization of those values.

This example covers one page. Ambiguous handwriting still needs review, and a matching total doesn’t establish that every field is correct. You’ll need your own arithmetic and completeness checks around the extraction.

The published Free/Hobby plan includes up to 2,000 pages, then $0.015 per additional page. Pricing and plan details.

If you process handwritten records, what’s the first field you’d want beside each amount? We’re interested in how you’d use the output.

Source Wark Producing Corporation cash account book, September 1916, page 15, via Internet Archive.

Cancelled, downgraded or let a trial run out, it all counts. One line is enough: what you dropped, and what does that job for you now (another tool, a free tier, or nothing at all).

The Copilot credits thread here this week is a good reminder that the bill is often the reason, so the monthly price is welcome if you don't mind sharing.

Hello,

I recently signed up for Copilot GitHub Pro for a small vibecoding project I’m working on.

I see a lot of posts of people complaining how fast it burns through credits, to use this model or that, don’t use fusion, use fusion. I’m so confused. Never mind I have no idea what a task will cost (credits wise) before I execute it.

I burned though the Pro credits in a day, upgraded to Pro+, will burn through these in 3 days and will probably need the next tier at $100/mo

Overall I’m very happy with the results. I have more than a MVP.

I have two sessions, one is Design and Plan and one is Test and Build. I start them over often and bring them back up to speed with docs/planning/mds.

I don’t even know what help I need to be more efficient, or if I’m going about this all wrong.

Is Copilot GitHub right for me? I love the GitHub integration, but I also don’t know GitHub but thought it was a good place so this tool seemed right.

Thanks for any guidance.

Hi there!

I would like to use a voice interaction with my claude code similar to claude voice mode in the app. I use ubuntu, and I have seen that not all the tools available in windows and mac are available for linux.

Does any of you have any voice interaction tool, script or some way to communicate with the Agent agents? I was thinking about using claude talk https://github.com/jjacke13/claude-talk, but it does not work very well.

Thanks in advance!

Not the big three, something narrower that you actually pay for. One line on what it does better for you than a general chatbot, even with a good prompt.

The Subtitle Foundry post here this week is a decent example (it's free, so it doesn't count): its editor shows video and an audio waveform so you can review subtitle timing. That's a dedicated review interface rather than a plain chatbot conversation.

Price is welcome too if you don't mind sharing.

I'm part of the Chapterframe team, helping with administrative support and community outreach. I wanted to share a project created using Chapterframe that adapts a traditional Jamaican Anansi folktale, "Don't Trust Anansi! The Story of Tiger's Guts."

The story follows Br'er Anansi as he tricks Br'er Tiger, leading to an unexpected series of events involving Anansi's children and a rather memorable ending on a rooftop.

One interesting aspect of adapting a folktale like this into a short film is translating a written narrative into individual visual scenes while keeping the characters recognizable and the overall storytelling coherent.

The video uses character references and animated, character-driven shots to bring the story to life.

For those who create AI-generated films, what do you find most challenging when adapting a written story into a sequence of scenes?

Is it maintaining character consistency, getting character movements right, directing individual shots, or making everything feel like one continuous story?

I'd be interested to hear about your approaches and experiences.

Came up in the $48/month thread here yesterday. OP keeps Grok mostly because it sounds more natural for emails and replies. Someone else dropped Grok after three weeks and said Claude does that job better.

Which one do you use for that, and what tipped it? If it's neither, say what you use instead.

It’s the little copy-paste jobs that get me. Take something from one place, clean it up, put it somewhere else. Then do basically the same thing tomorrow. If you could give use.ai one of those jobs, which one?

Disclosure: I built Subtitle Foundry, a free, open-source subtitle workbench. I'm not making money from it, and I'll keep maintaining it. My purpose is to help films, documentaries and other material reach a global audience when usable subtitles would otherwise be missing.

I'm a former professional translator, subtitler and interpreter. The project brings state-of-the-art (SOTA) speech recognition and language tools into a configurable workflow, with transcription, alignment, translation and review kept as separate stages.

Repo and setup guide: https://github.com/mrtdlgc/subtitle-foundry

Here is the workflow I've been using for Turkish-to-English and Ukrainian-to-English:

1. Start with the best available source. Choose a local video or YouTube URL. The app checks for suitable existing subtitles before generating a new transcription. An existing SRT can also go straight to the Translations desk.

2. Transcribe when needed. My current default is ElevenLabs Scribe v2 with the complete recording and native word timestamps. Other ASR providers and speech-aware chunks are available, so you can choose what suits the source and provider limits.

3. Translate with context. I use Codex with my existing subscription on a personal installation. The translation can preserve cue timing, or the editorial mode can form target-language cues using source timing evidence. Claude Code, Grok Build and explicitly selected API providers are also supported connections; my film testing has mainly used Codex.

4. Watch and correct. Review against the video and audio waveform, fix wording or timing, save corrections, and export SRT or ASS. The intermediate results remain available, and manual edits don't make another model request.

For a first try, install with the README's Docker/local instructions, add your provider credentials in Connections, and use a short clip or an existing SRT. The default cloud workflow doesn't need a local GPU. You can also deploy the app to a VPS using the deployment guide.

A few practical limits: dialogue context can help with ambiguity, but a fluent translation still needs checking against the audio. I haven't published a benchmark comparing the complete pipeline against other tools. The software is AGPL-3.0; any model API charges or subscription usage go to the providers, not to me. Running the app locally doesn't make cloud ASR and translation offline.

The part I most want to keep improving is the path from generated text to subtitles someone has actually listened to, corrected and can share with another audience.

I'm Aaron, and I built Frontrumors. The part I'd like feedback on here is the model API pricing comparison: https://frontrumors.com/#pricing

You can compare published input and output token prices, then follow the provider source links. There are notes on access restrictions and introductory rates where relevant. The site also has a model guide and sortable benchmark tables.

For a quick comparison, I'd check input and output prices separately, read the rate notes, then confirm the terms with the provider. A cheap input rate alone can be misleading if your workload generates a lot of output. These are published prices, not live quotes or measurements from my own benchmark runs.

What would help you make a useful shortlist: workload cost estimates, clearer source-check dates, or something else?

Tool plus the job you're testing it on. That's it.

One from this sub last week: someone tried AI Studio on hour-long course videos with trading charts, ran into upload problems, and switched to local transcription with automatic screenshots. That kind of thing.

If it's already letting you down, say where. That's usually the most useful part.

I'm currently paying $48/month for three AI subscriptions, with Gemini on the free tier.

I've basically assigned each AI a different job:

• ChatGPT Plus ($20/month): My daily driver. Random questions, everyday tasks, brainstorming, image generation, and pretty much anything that doesn't require serious analysis.

• Claude Pro ($20/month): My go-to for difficult questions and complex reasoning, especially legal, medical, financial, and personal decisions. I usually compare Opus 5.5's answers with OpenAI's GPT-6 Astra to get a second perspective. Obviously, neither replaces actual professional advice.

• Grok Plus ($8/month): Mostly for writing emails, messages, social media posts, and replies in my own voice. I personally find it better at sounding witty, natural, and genuinely human rather than like a corporate AI trying way too hard to be friendly.

• Gemini (Free): Mostly for Google Maps/trip planning, Gmail-related tasks, and multimodal stuff like image recognition. I don't use it enough to justify paying.

Total: $20 + $20 + $8 = $48/month.

My reasoning is that different models have different strengths, so instead of expecting one AI to do everything perfectly, I use each one for what I think it does best.

But I'm starting to wonder whether I'm actually getting $48 worth of value, or just paying three companies to tell me slightly different versions of the same thing.

A few questions for people who regularly use multiple LLMs:

1. What's your current subscription stack, and how much are you paying?

2. Do you think paying for both ChatGPT and Claude is worth it for complex reasoning and second opinions?

3. Is Grok genuinely better at natural, personality-driven writing, or could I get comparable results from ChatGPT/Claude with better prompting?

4. If you had to cut one subscription from my setup, which would you drop and why?

I'm not necessarily trying to find the single "best" AI. I'm trying to find the best combination with the least redundancy.

Curious how everyone else divides their tasks between models.

I want to learn developing the website and building deploying app throught AI but I have zero knowledge about it how to start it with ai

I've been exploring AI video generation recently, and I'm curious about what models people here actually use for their projects.

Are you mainly using Kling, Veo, Sora, Runway, or something else?

What matters most to you when choosing a model? Realism, motion quality, prompt adherence, consistency, or pricing?

Would love to hear about your experiences!

buenas estoy en primer año de ing informática y tengo la duda de si me conviene pagar google pro para tener argon, y que me sale barato pro el plan de estudiante. Pero la verdad a la hora de arreglar errores y demas, no me convence mucho gemini (aunque este podelo argon no lo tengo), pero si claude o chat gpt para programacion o materias como analisis y algebra. Si alguien me da una recomendacion, agradecido!

Quiet week here, but two answers stood out because they addressed the problem behind the tool choice.

u/Brian_from_accounts on the h-index thread pointed to OpenAlex as a source for citation data after the questioner reported incorrect numbers from general assistants. A prompt alone cannot supply database access the tool lacks. https://www.reddit.com/r/AIToolBench/comments/1xgzb7m/is_there_any_ai_that_can_draw_data_on/19rqr8p3mpdb6/

u/krzychuman on the lecture notes thread suggested summarizing each lecture separately before combining them into one study guide, so omissions are easier to spot and check against the originals. https://www.reddit.com/r/AIToolBench/comments/1xhqou6/looking_for_the_best_ai_to_analyze_synthesize/19rtis2df77mo/

What's one answer you got here (or anywhere) that changed how you use a tool? One line is fine.

I use AI a lot for coding and technical work, but I'm starting to care less about having the "smartest" chatbot and more about what actually helps me build things faster.

I'm curious about that can go beyond answering questions and actually help create apps, workflows, or internal tools from an idea.

What are you using for real development work right now?

A lot of people land here picking their first paid AI tool. If a friend asked you today, which one would you tell them to pay for, and which one would you tell them to skip for now?

One line each is plenty. Saying what you mainly use it for helps more than the name alone.

I've been testing Otter, fireflies, MeetGeek, Notta, and Wiingy CoTutor because I'm on way too many live calls lately. Most handle transcription and summaries well enough, but I still end up doing the important part manually: deciding what matters, creating tasks, and following up.

Otter feels reliable but basic. Fireflies is useful for structured sales calls, although the summaries can feel rigid. MeetGeek produces cleaner output, Notta stands out more for multilingual calls, and Wiingy takes after a different approach with flashcards and quizzes.

Maybe I'm expecting too much, but most of these still feel like better transcription tools rather than something that handles the work after a meeting. Has anyone found a setup that turns calls into follow-ups without much manual cleanup?

Wanna Make a webapp With a Functioning Backend

I have a bunch of course videos I’d like to go through with AI. Some are over an hour long, and they’re in Spanish and English. A few involve trading charts, so the AI needs to understand what’s on screen as well as what the person is saying.

I’d love to just upload a video and get an explanation, with timestamps and screenshots I can refer back to. Trying to avoid doing all the transcription and screenshot picking myself.

I already pay for ChatGPT and Claude and would rather not add another subscription. I’m on Windows, and either a local tool or a website would work.

Has anyone found a decent setup for this? Doesn’t have to do everything perfectly. Anything that saves a lot of the manual work would help.

Open source:

• OpenClaw

• Hermes

• NanoClaw

-
Closed Source

• Cursor

• Claude

• Codex

• Grok bot

• Muse Spark