User
Write something
Pinned
🔁 Why AI Makes a Bad Second Opinion (And a Great First One)
There's a specific way a lot of people have started using AI that feels reasonable on the surface but tends to produce weaker outcomes than they expect: making a decision first, then asking AI to check it. "Does this plan make sense?" "Is this the right call?" "Can you sanity-check this approach?" These questions feel like due diligence. In practice, they're often asking AI to validate a decision that's already been made, and AI is structurally not very good at that particular job. The distinction that matters here is sequence. AI brought in before a decision is formed and AI brought in after a decision is formed produce genuinely different kinds of value, and most people default into the second pattern without realizing the first would usually serve them better. ------------- Context ------------- When AI is asked to evaluate a decision that's already been presented as the plan, it tends to find reasonable support for that plan, because the framing of the question shapes the response. Ask "does this make sense" about almost any coherent plan, and a capable AI model will generally find a way to say yes, with some caveats, because most reasonably constructed plans do make some sense, and the question as framed is oriented toward confirmation rather than genuine challenge. This isn't a flaw exactly. It's a reflection of how these tools respond to framing. A question asked in a confirmatory posture tends to get a confirmatory answer, unless the plan is genuinely and obviously flawed. The subtler problems, the ones that a good second opinion is actually supposed to catch, are much less likely to surface when the question is framed as "check this" rather than "help me think through this from scratch." Contrast this with AI brought in before a decision has formed, asked to help explore the problem itself: what are the options, what are the tradeoffs, what am I not considering. This framing produces a genuinely different quality of engagement, because there's no existing conclusion for the response to gravitate toward. The AI is helping construct thinking rather than validate a thought that's already complete.
🔁 Why AI Makes a Bad Second Opinion (And a Great First One)
Pinned
OpenAI Just Rebuilt ChatGPT
OpenAI put out a ton of new stuff this week including the public release of the GPT-5.6 family of models, the new ChatGPT Work app that will be merging Codex and ChatGPT capabilities, a new voice mode, improvements to the speech-to-text dictation, and more! I break it all down for you here, enjoy! Want to save time, get more leverage, and stop figuring this AI stuff out from scratch? I put the clearest map and support inside the AI Advantage Club
Pinned
Keep Going. You're Building Something Bigger Than You Think.
There's a season where you're doing everything right... You're showing up. You're putting in the work. You're staying consistent. And it still feels like nothing is changing. No momentum. No big breakthrough. No proof that it's working. This is the moment that separates people. Not because the work got harder... but because they mistake a lack of results for a lack of progress. What I've learned after decades in business is this: The invisible season is where everything important gets built. Your discipline. Your resilience. Your standards. Your identity. The results come later. Success rarely announces itself while it's being built. It compounds quietly... until one day everyone calls it an overnight success. If you're in that season right now, don't quit. The work you're doing today is building the life you'll eventually be grateful you didn't give up on.
I Was Asking AI the Wrong Questions
I thought I needed AI to help me build my business. Instead... It helped me redesign my life. For months, I kept asking AI questions like: How do I grow my community? How do I sell more books? How do I make more money? Then yesterday, AI kept asking me one question: "Is this actually the life I want?" I realized I had been designing my life around my business... ...instead of designing my business around my life. So I simplified everything. 🧡 One daily question in my community. 🎉 One weekly Figureoutable Friday Happy Hour. 📚 One book a month. 🎙️ One podcast conversation at a time. No checking royalties every day. No chasing a finish line. Just building a life I genuinely enjoy. The biggest lesson? AI is at its best when it doesn't give you answers. It's at its best when it helps you discover the question that changes everything. What's the most powerful question AI has ever asked you?
📰 AI News: Anthropic Wants to Make Building AI Agents 10x Faster
📝 TL;DR Anthropic just launched Claude Managed Agents, a new way for companies to build cloud-hosted AI agents without stitching together all the messy infrastructure themselves. The pitch is simple: less time wrestling with backend complexity, more time actually shipping useful AI products. 🧠 Overview Anthropic announced Claude Managed Agents, a new public beta product on the Claude Platform designed to help developers build and deploy production-ready AI agents much faster. Instead of spending months setting up sandboxing, permissions, session handling, and monitoring, teams can define the task, tools, and guardrails, while Anthropic runs the agent infrastructure for them. This matters because the real bottleneck in AI is no longer just model quality, it is getting reliable agents into production. 📜 The Announcement Anthropic introduced Claude Managed Agents on April 8, 2026 as a suite of composable APIs for building cloud-hosted agents at scale. The company says the platform includes secure sandboxing, authentication, long-running sessions, execution tracing, and built-in orchestration. It is available now in public beta, with some advanced features like multi-agent coordination and self-evaluating workflows still in research preview. ⚙️ How It Works • Managed infrastructure - Anthropic handles the backend pieces like secure execution, authentication, checkpointing, and tool use so developers do not have to build it all from scratch. • Long-running sessions - Agents can keep working autonomously for hours, with progress and outputs persisting even if the user disconnects. • Built-in orchestration - A native agent harness decides when to call tools, how to manage context, and how to recover from errors. • Scoped access controls - Teams can connect agents to real systems with permissions, identity controls, and execution tracing built in. • Multi-agent workflows - In research preview, agents can spin up and coordinate other agents to parallelize more complex work.
📰 AI News: Anthropic Wants to Make Building AI Agents 10x Faster
1-30 of 20,050
The AI Advantage
skool.com/the-ai-advantage
Founded by Tony Robbins, Dean Graziosi & Igor Pogany - AI Advantage is your go-to hub to simplify AI and confidently unlock real & repeatable results
Leaderboard (30-day)
Powered by