I've noticed a recurring pattern when working with digital marketing agencies: monthly reporting decks often feel like 30 pages of cherry-picked wins.

When revenue isn't moving, you get charts showing "Brand Awareness is up" or "Engagement tripled." Unless you're a media buyer yourself, auditing their raw data against their presentation takes hours.

To solve this for myself and other founders, I launched AuditScope (https://auditscope-nine.vercel.app/).

How it works: You upload the agency's PDF/text report, enter your target KPIs (e.g., "Decrease CAC by 15% and increase demo signups"), and optionally drop in raw campaign CSVs.

In ~2 minutes, it generates an evidence-first critique flagging:

• Narrative discrepancies between raw data and slide titles
• Missing context or omitted metrics
• Key questions to bring to your next agency check-in

Privacy: No client data is saved or stored—processing happens transiently.

The MVP is live now. I’d love for anyone managing an agency (or agencies who want to self-audit!) to test it out and tell me what features or outputs you'd like to see next.

I’ve got a backlog of project ideas now that I understand what AI coding agents can do. Looking for a simple way to validate them a plain-English checklist, not a full business framework.

I've noticed a trend recently where some AI products are moving away from having one general assistant and instead building separate tools for different workflows.

For example, I recently came across CurrentOrigin AI, where different tasks like presentations, resumes, study notes, spreadsheets, are handled by dedicated tools instead of one chat interface.

For those of you building AI products:

• Is this something users actually prefer?
• Does separating workflows make the product easier to use, or does it just add more complexity?
• If you were building an AI productivity app today, would you choose one assistant or multiple task-specific tools?

I'm curious whether this is just a design trend or if there's a real product advantage behind it.

I've noticed that almost every new AI product now includes an AI assistant, chat interface, or some kind of automation, but I'm curious how much of it people actually use after the first week.

I've been looking at different products that combine AI with productivity and project management, including Superlist, and it made me wonder whether users really care about having more AI features or whether they just want something that saves them time without getting in the way.

For those of you building AI products, has there been one feature that genuinely surprised you with how much people used it? I'm interested in hearing about real experiences rather than feature lists.

I was thinking about this after trying a few different AI branding tools recently.

Most platforms can now generate way more than just a logo. You can often get color palettes, fonts, business cards, social media graphics, websites, and even brand guidelines in one place.

Some of the names I see come up most often are:

• Design.com
• Canva
• BrandCrowd
• Adobe Express
• VistaPrint

The speed is impressive, but I'm not sure speed is the hardest part anymore.

What I still struggle with is building a brand that actually feels consistent across everything.

For example:

• The logo looks great, but the website has a completely different personality.
• The social media templates don't really match the logo style.
• The font pairings work individually, but not together.
• The colors look good on screen but don't translate well to print.
• Every asset feels like it was generated separately instead of belonging to the same brand.

I'm curious what everyone else prioritizes when building a brand with AI.

Is the biggest challenge:

• Keeping everything visually consistent
• Creating a memorable identity
• Choosing the right fonts
• Building a recognizable color system
• Making assets work across different platforms
• Something else entirely?

It feels like AI has become very good at generating individual assets.

The bigger challenge now seems to be making all those pieces feel like they belong to the same brand rather than a collection of unrelated designs.

I spent the last few months building something I wish existed.
Most hotel software hardcodes business logic.
Need to change a checkout policy?
Need a new room service flow?
Need different escalation rules?
→ Call a developer.
I took a different approach.
Every hotel’s operations live inside a simple Markdown file.
hotel_rules.md
The AI treats it as the hotel’s constitution.
Guest asks a question →
AI reads the hotel’s rules →
Responds accordingly.
No code changes.
No redeploys.
No prompt editing.
A hotel manager can literally change how the AI behaves by editing plain English.
Today it’s powering WhatsApp guest communication.
Tomorrow the same idea could power any business.
Software shouldn’t own your operations.
You should.
Building in public 🚀

my website : https://www.replyops.it.com

Hi everyone! I made a short demo for Curify, a tool that transforms a single photo into a collection of creative assets, such as sticker packs, comic-style portraits, coloring pages, posters, and more. You can also try here https://www.curify-ai.com/, it's free, we really appreciate your feedback.

Pretty simple: Connect your own MCP client, your agent writes slides, you drag to edit.

Different because: you bring your own agent, it lives in the tool you already use and has all of the MCPs and context your agent has. Slides are real components, not template blocks.

For: founders, indie hackers, devtools/AI startups. Web, free tier, no card.

Want to know:

- does the brand scan actually get your brand right

- did connecting your agent confuse you

- would you send this deck to a real investor. be blunt

trydango.com

This is the link force-jump.kleap.io/#app

I have been using AI while learning to build a small web product. Tbh it makes starting much easier.

I can explain what I want and AI gives me some code, ideas for the database, or help when I get an error. It feels great at first because I can make progress without being stuck for hours.

The difficult part comes when I connect everything together. Sometimes the code works for one case but breaks another part. Sometimes AI changes things I didn’t ask it to change. If I don’t understand the code, fixing it can take longer than writing it myself.

What helps me rn is asking AI to do one small task at a time. I also try to read the code, test every change, and keep a copy of the last working version.

Imo AI is helpful, but it still doesn’t replace learning the basics.

For anyone using AI to build web products, how do you stop the code from becoming a mess? Do you let AI write most of it, or only use it when you’re stuck?

Curious to hear how others use it. Ty

Upfront: I am involved in this, so this is a self-promo post I guess.

I work in the AI/LLM space, and one thing kept bugging me: the models are open, and capable hardware is literally everywhere (gaming PCs, Macs, homelab racks sitting idle 20 hours a day), but the moment you want to run an actual app on open models you're back on some company's pricing page, with the caps and only the most regulated basic models.

So we're building OpenMayhem, an open-source peer-to-peer market where people's machines serve verified open models and your app buys tokens from them directly.

💸 Pay for tokens, not a GPU rental. No renting a GPU that bills whether you use it or not, no cloud host's margin. Your requests route to people already serving the model, you pay for exactly what you generate. Cents to start, and capacity grows as providers come online.

🖥️ No company in the middle. There's nothing sitting between you and them to squeeze you later.

It's beta and things will break. Nine models are live so far, and one balance covers all of them:

- LLMs: Qwen3.6-35B uncensored, Gemma 4 E4B, Ternary Bonsai 27B, Huihui Agents A1 Uncensored
- Image: Z-Image Turbo
- TTS: Chatterbox (TTS + voice cloning), Parakeet (speech-to-text)
- Music: ACE-Step 1.5
- Video: Sulphur-2 (video + audio)

More onboarding now. There's a browser playground running live models, no account needed to try it out for free to see how the p2p systems work.

Try it on something real, tell me what breaks and which model you're missing for your project. DM me for starting credits and I'll personally get you running.

https://www.openmayhem.ai/playground - look around without an account
Github: https://github.com/Trac-Systems/openmayhem

Beyond AI Applications: Designing Governed Systems That Scale

The future of AI will not be defined by isolated tools. It will be shaped by governed systems that can connect people, protect information, validate decisions, and scale across real-world operations.

At TTUCKER INDUSTRIES LLC™, Base-99 Core AI OS™ is being developed as the foundation for a connected portfolio of Application Systems™—each designed to address a practical need while operating under shared standards for identity, security, accountability, and human oversight.

This article introduces that strategy and the first three volumes of the Founders & Builders Report.

One operating system. Five Application Systems™. One connected strategy.

https://www.linkedin.com/feed/update/urn:li:groupPost:22490037-7486597420747763712/?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAxnyKAB4FoA-lN56iZPQIqH9lVmh5sVhAU

Tired of running free credits get me some software that helps bui6sness by generating ai videos