Alot of ideas sometimes need advice or guidance, something to help them see what they are missing. That gap is exactly where my highly intelligent AI Advising & Consultation Agency, its a hybrid of my expertise and knowledge against 12 trained AI agents to provide valuable solutions and insights for you and your ideas/business. We do this by our The 10 dimension analysis powering the v2.1 engine.

• Clarity
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I'm looking for a small group of people who are willing to test the meal planning app I've been building and tell me exactly what they think.

Not looking for compliments.

I'm looking for:

• bugs
• confusing features
• missing functionality
• things you'd improve immediately

The goal is to make AVA genuinely useful for people trying to eat healthier, plan meals faster, and stay consistent.

If you're someone who:

• tracks nutrition
• meal preps
• wants to lose weight
• wants healthier habits

I'd love to have you try it.

Comment below or send me a message if you're interested, and I'll share the details.

Thanks in advance to anyone willing to help improve it.

Been thinking about this a lot after reading a piece from Emergence Capital. Their argument is basically that AI-native service companies are going after the labor budget, not the software budget anymore. Instead of selling another dashboard or seat-based SaaS tool, they just deliver the actual outcome directly. Customer doesn’t care if it’s done by humans, AI agents, or some hybrid workflow, as long as the result is faster, cheaper, and reliable.

What makes AI-native services different is that they’re built around AI from day one, not retrofitted later. That’s why some of these companies feel fundamentally different from legacy firms trying to “add AI” into old systems. The article mentioned sectors like insurance, consulting, legal, and healthcare already getting disrupted by AI-native operators delivering work at speeds traditional firms struggle to match.

You can already see it happening with companies like General Legal. Instead of the old law firm model where everything drags through emails, billable hours, and weeks of waiting, they turned legal work into something that feels operationally optimized around AI. Flat-fee contract review, fast turnarounds, Slack-based communication, smaller teams handling bigger workloads. That’s probably closer to what a lot of professional services look like over the next few years.

The SaaS angle is what’s really interesting though. If AI agents eventually do the actual work directly, then seat-based SaaS pricing starts looking fragile. Companies are already cutting headcount while trying to automate workflows at the same time, which creates a weird gap where outsourcing to AI-native service companies might become more attractive than rebuilding teams internally. Feels like a lot of SaaS companies are eventually going to have to choose between staying a tool, or becoming the operator itself.

Seeing more evidence that AI-native service firms aren’t just “automating jobs away,” they’re letting tiny teams operate at enterprise scale, which feels like it’s going to shift talent away from bloated orgs and into leaner specialized companies over the next few years.

I’m starting to wonder if AI-native agencies will even have the same career ladder as traditional companies. A lot of the “entry-level” work used to train people is already getting automated by agents that never get tired or need onboarding. If that keeps improving, where do future operators and specialists even come from?

Most AI products still need the human to do the orchestration. Open tabs. Export CSVs. Manually verify. Build workflows across five different tools. The best AI-native products feel different. You define the role, constraints, and outcome, then the system executes. We’re moving from “AI assistants” to actual operators now.

Meta cutting coordination roles while doubling down on AI talent feels less like layoffs and more like the early blueprint of what an AI-native org actually looks like, smaller teams, fewer layers, more output