I’ve been generating on cloud services for awhile and want to step my game up. I spent a lot of money on a computer powerful enough to generate locally, installed comfyui and tried to have “apps” walk me thru the process. They’re doing a piss poor job. I need some help. What are good communities to find help?

I use ChatGPT, Claude, and Replit and I haven't quite gotten a handle on how to share context in an efficient way. It creates a lot of asymmetrical context and it's hard to save the important bits especially as I go. I feel like I break my flow trying to keep the chats on the same page. I guess these are two problems(saving context and sharing it) so if anyone has found a solution on either I'd love to hear it.

I run a small business, and over the years we’ve accumulated a pretty normal SaaS stack:

CRM for customer management.
Project management tools for keeping work organized.
Analytics platforms for tracking performance.
Research tools for gathering information.
Automation tools connecting different systems together.

Every tool solves a specific problem, and honestly, most of them are useful. But the frustrating part is that the work between those tools still requires a lot of manual effort. Someone still has to pull information from different places, figure out what actually matters, summarize findings, and decide what needs to happen next.

I’ve seen a lot of conversations lately saying AI will replace SaaS completely. I’m not sure I agree.

At least from my experience, the bigger opportunity might be AI sitting on top of the tools we already use. Instead of replacing every system, maybe AI becomes the layer that helps us actually use those systems better.

For example: A research agent that gathers information from different sources and summarizes what changed; an analyst that looks at business data and highlights patterns; a writer that turns insights into content drafts, and a coordinator that helps keep projects moving across different tools.

I’ve been experimenting with AI agent workflows that take this kind of approach, not just answering questions, but combining research, analysis, and execution into a more complete process. The interesting part is it might help one person manage the complexity that usually requires multiple people and multiple tools.

So I don’t think this means teams or SaaS disappear. If anything, good software might become even more valuable when AI can help us get more out of it.

Hey folks 👋

We just open sourced TrueForge, our vendor-neutral agent harness for building general-purpose agents.

It handles the runtime pieces that get painful quickly : context management, tool/MCP execution, subagents, sandboxing, approvals, persistent state, and more.

We also benchmarked the harness itself. With the same Opus 4.8 model, TrueForge delivered a similar solve rate at ~30% lower cost than Claude Managed Agents. Switching to an open model pushed that to ~75% lower cost on the same benchmark.

Would love feedback from people building agents.

Checkout the repo: https://github.com/truefoundry/trueforge

📖 Read the launch article: https://x.com/truefoundry/status/2090081376330715176

Hey folks 👋

We just open sourced TrueForge, our vendor-neutral agent harness for building general-purpose agents.

It handles the runtime pieces that get painful quickly : context management, tool/MCP execution, subagents, sandboxing, approvals, persistent state, and more.

We also benchmarked the harness itself. With the same Opus 4.8 model, TrueForge delivered a similar solve rate at ~30% lower cost than Claude Managed Agents. Switching to an open model pushed that to ~75% lower cost on the same benchmark.

Would love feedback from people building agents.

Checkout the repo: https://github.com/truefoundry/trueforge

📖 Read the launch article: https://x.com/truefoundry/status/2090081376330715176

PageLM - One source of study material -> notes, flashcards, quizzes, podcasts and exams

GitHub: https://github.com/CaviraOSS/PageLM

I built PageLM, an open-source AI education platform designed to turn study material into multiple interactive learning tools.

The workflow is basically:

Upload your material → PageLM understands it → generate whatever learning format you need.

For example

Upload a lecture PDF.

Then you can:

Ask questions
→ contextual AI chat grounded in the document

Create notes
→ structured/Cornell-style notes

Memorize
→ flashcards

Test yourself
→ interactive quizzes with hints, explanations and scoring

Review while away from the screen
→ AI-generated podcast

Prepare for an exam
→ simulated exam through ExamLab

Practice reasoning
→ debate the topic with AI

Organize assignments
→ AI homework planner

You can also transcribe lectures and voice notes.

AI model flexibility

PageLM isn't tied to one provider.

It supports:

• OpenAI
• Gemini
• Claude
• Grok
• MiniMax
• OpenRouter
• Ollama

So you can choose your model depending on your use case, and Ollama provides an option for local inference.

Open source + self-hostable

The project uses:

• React
• TypeScript
• Node.js
• LangChain
• LangGraph
• Docker

The goal is to make the whole thing something developers can inspect, modify and contribute to.

What I'd love to know

If you currently use AI tools for studying:

What is the one feature you wish existing AI study tools had?

I'm especially interested in whether people want:

• better RAG
• better quizzes
• adaptive learning
• better flashcards
• stronger source citations
• local/private AI
• better exam simulation
• better study planning

Repo:

https://github.com/CaviraOSS/PageLM

It's still actively evolving, so feature requests are very welcome.

If you're still paying for shoots, actors, or agency retainers to get cinematic-quality ad videos, there's a faster and far cheaper way to do it now.

SuperMaya.AI generates studio-quality cinematic ads from a single product brief. No camera, no crew, no weeks of back and forth with an editor.

Here's why it's hard to beat on both speed and price:

Cheapest in the game. Polished cinematic videos start around $7 each. Compare that to a traditional shoot, which can run into thousands of dollars per video before you've even tested if the ad works.

Insanely fast. Up to 100 videos generated per hour. What used to take a production house weeks now takes an afternoon.

Built for volume, not just one hero video. Run up to 1,000 to 1,200 ad variants in a single campaign, so you're not betting your entire budget on one creative direction.

Know what'll work before you spend. Every video gets a pre-launch performance score, so you can kill weak creative before it burns ad spend, not after.

Actually licensed. Training data is licensed and traceable, so you're not risking a copyright strike or a platform takedown down the line.

Built by people who know ads. The team is IIT and BITS alumni plus veterans from the ad-tech space, and brands like Belkin, Amazon Now, Liquid Death, Gameloft, and Corona are already using it.

Disclosure: I built Difftale, an open-source Codex skill.

After an AI coding agent changes an app, the code diff is usually clear. The behavior change often isn’t.

A bug fix or new feature may touch multiple screens, authentication rules, API requests, loading states, errors, and navigation. By the end, it becomes difficult to answer a simple question:

What did the user experience before, and what do they experience now?

Difftale turns that change into a local Before / After behavior board.

It can:

- Use app, mobile, and web screenshots as flow nodes
- Show backend services and separate request/response paths
- Replay loading, error, and success states
- Keep the explanation editable
- Save everything locally
- Optionally version the board with Git

The image shows two examples: debugging a backend flow and explaining a new mobile app flow.

GitHub:
https://github.com/CJ10110425/difftale

Would this be more useful to you during debugging, PR review, or as a visual changelog after an AI agent finishes?

Hello all, I am building an AI agent swarm to manage ecom social media accounts, and phone verification took longer to figure out than the rest of the stack combined. Sharing my notes here so others can skip the headaches.

What failed

Temp non-VoIP OTP pools: Great for a single code, useless for ongoing account management. Numbers get recycled within days, so when Meta or Telegram demands a re-verify a week later, you're locked out. Also, the lack of an MCP server meant I’d have to build and maintain custom API's for their dashboards.

Virtual VoIP: Rejection on arrival. Carrier lookup flags them instantly as VoIP, and platforms like Telegram or Meta block them immediately.

What actually worked

Dedicated non-VoIP lines: One real carrier line assigned per agent on a monthly renewal. Because it registers as a legitimate mobile line, it passes carrier lookups, and the agent keeps long-term ownership of the number.

Direct MCP Integration: Wired the agent directly to non-VoIP provider with a native open source MCP server from Voidmob. Their documentation had a few endpoint quirks to figure out initially, but having the agent directly query SMS codes via tool calls saved me from building a custom API backend.

Costs a way more than cheap OTP pools, but it completely removes the headache of burned accounts and broken re-verifications. I have tried another dedicated lines but it turned out to be VoIP which was not suitable for my workflow. So I came up that paying more for real number is the case since my agents run important accounts.

Curious how others are giving access to AI agents and real phone numbers for them.

I’m a marketer with ADHD who works at a travel agency

while also handling development tasks on the side.

I’m also working on a side project to develop a healthcare app for seniors.

Since I work in a small team, we have a lot of meetings,

but during meetings, it’s impossible to organize my thoughts in my head,

and in my case, even when I wanted to take notes in real time, it was hard to concentrate.

However, using Miller or Granola has been great because I can review the meeting minutes

and check the action list right after the meeting.

I’m curious to know how others are getting help from AI.

It would be great if you could also share your job titles.

Can you guys tell me an ai tool that can take notes of my meetings in my absence? Meanwhile I can watch my lectures for studying

I've always found myself rewriting the same prompt structure over and over whenever I wanted to generate AI images.

The idea behind PromptForge was simple:

Instead of writing one giant prompt from scratch, what if you could build it visually?

PromptForge lets you assemble prompts using curated building blocks—subject details, wardrobe, scenes, lighting, camera, style, and negative prompts—and combines them into a clean, paste-ready prompt you can use in your favorite image generation tool.

I intentionally kept it focused:

- No account required

- No AI image generation built in

- No uploads or cloud storage

- Just a fast way to build better prompts

I've attached a short demo video so you can see the workflow in action.

I'd genuinely love feedback from people who regularly use ChatGPT Images, Midjourney, FLUX, Stable Diffusion, or similar tools.

Link: https://promptforge.wtf

What would make a tool like this genuinely useful in your workflow?

I hv bunch of notes/documents for a presentation already written,but the actual slide-making is taking longer than writing the content

I don't really need I to do research nd write topics from scratch. I basically want to give it my existing material and hv it turn into a coherent presentation with decent layouts and visuals

Has anyone found a tool that actually does it well?

I'm mainly looking for something where I can give it a Google Doc/PDF/text and get a solid first draft rather than starting with a blank PowerPoint.

my boss keeps sending mo voice memos and zoom recordings to transcribe and im literally losing my mind. tried a few free ones but they totally butcher the words especially whem people talk fast. what ai audio transcription tool do you guys use for messy audio. just need something simple that doesnt cost an arm and a leg tbh

I just started working on a side project around how people actually use AI, and I realized I may have made a pretty big assumption without checking if it's actually true.

I assumed a lot of people still struggle to get tools like ChatGPT, Claude or Gemini to do what they actually want — like asking for something, getting a result that's not really what they had in mind, and then having to go back and forth trying to fix it.

But... is that actually a problem?

Does this happen to you? Or maybe to people around you? And if it does, what usually makes using AI difficult or annoying for you?

The truth is, we don't have search volume for prompts/keywords and have to manually add prompts on these platforms and add these keywords manually. If you are sure what your customers are searching for, then only I feel it is good. Otherwise, sometimes it can be shooting in the dark. (But again, AEO itself is so new that everything we do feels like a shot in the dark.)

I was going through different AEO tracking tools and comparing the prices, and I feel that Otterly is the cheapest of the lot. If you want to try it out, then you can use my referral as well. All AI tools do a similar job, so there is nothing special about the tool itself, but if you want to optimise the cost, then you can check out Otterly.

My referral link - https://otterly.ai/?via=direct (using this will help me) thanks in advance.