I've spent my life reading rooms, people and patterns then years in cybersecurity and SecOps. I'm turning that into something you can actually train for personal security. HUMINT, OSINT, OPSEC, Situational awareness without the paranoia. This is the start → @DecodeTheAsset - Protect the Asset

We all tell LLMs what to do - research, implement, analyze. Something I started doing after first instruction/implementation is done is to have it assume it's all wrong. To use ever skill/agent/tool at its disposal with the assumption the initial implementation is wrong, outdated, doesn't make sense, inaccurate, lacks research and best practices. The point is to have it prove the initial implementation achieved the instructed goal. Works very well so far.

Today I built a demo for a prospect client from the live transcript as the meeting was in progress. I shared the link to the demo at the end. Ooenclaw Demo builder agent connected to my meeting app. I asked the prospect exactly what the builder will use making sure it has enough context for the demo, it suggests me questions through Telegram to make sure I get all necessary information for next steps. After the meeting is created a full product spec and further questions to clarify MVP are documented. Anyone can guess if I got the client?

I've intensively used Gemini-3, it's awesome for implementation, a bit weak for crafting documentation like PRD, technical documents, and brainstorming. Verdict so far: - Gemini 3 - For building - Claude Sonnet-4.5 & Opus-4.1 - for brainstorming and crafting docs.

Today I used Gemini to have a few “sales” calls (audio). It was actually very helpful. Although I can almost be certain it does not know how to interpret tonality and emotion, it allowed to hear myself, practice rebuttals, and overall tone of my voice. I incremented the “toughness” of the client role gradually. It provided good feedback and I enjoyed it a lot. You can always get better 🦾

Your team spends 40 hours/week on manual tasks. So you buy a $50K AI platform to "fix" it. 6 months later: same manual tasks, new AI tool nobody uses. The problem isn't the tools. It's the sequence: ❌ Automate → Hope it works → Wonder why it failed ✅ Remove friction → Standardize → THEN automate MIT says 95% of AI pilots fail. This is why. DM "FRICTION" - I'll show you the 2-week audit that finds $250K in waste.

AI engineers need to be more than that to have a successful relationship with a client. Being a good communicator and product manager (among other things) are paramount skills to have, otherwise you create friction. Most companies treat the development of these systems as regular software and it’s fine because this is all new (wanting to integrate AI). That is why absolute transparency and guidance is essential for being in the same page, and not to create distrust.

Let’s think about this for a second: AI is empowering every single individual that learns how to use it, yet why do companies struggle with AI fusion? You’ve been sold the idea that AI will just merge into your company without fixing the underlying inefficiencies. The true power comes from enhancing individuals, not by investing 100k/yr on sophisticated systems. - Just Remove the Friction

Every single AI system implementation is iterative. “When is the project going to be absolutely finished?” - Never The only goal is to make it good enough so we don’t care to improve anymore.

If you're just getting started with AI adoption, agents and automation might help specific use-cases—but they won't drive long-term transformation. Companies that succeed remove unnecessary tasks and processes FIRST. When they introduce AI, it's lean and value-focused. Remember: Optimized broken processes are still broken. - Just Remove the Friction

Everyone focused on trying to one-shot the entire AI company adoption without realizing the cost will be astronomical without a proper system. The trick is to Just Remove the Friction.

Your company’s AI adoption strategy is not to invest 100k on enterprise solutions. You don’t want AI for the sake of having it, you want ROI, but most companies try to brute force it to adjust to AI. AI can adapt to your company, it’s just a matter of following a clear Integration Framework. - Just Remove the Friction -

VibeCode can actually save your company: 1. Talk to your employees, they are in the frontlines. Ask what task(s) take them 2+ hours daily. 2. Write down the steps: enlist the steps to accomplish the task as is. 3. VibeCode a quick solution to empower your employee to accomplish the task faster and better. 4. Move on to next task/process/department and apply same steps. 5. Use the free space to analyze de current task process and identify why is needed. Find root cause and follow the trace to that task. Are all tasks necessary? 6. After the urgent tasks are taken care of, use that extra headspace to optimize your processes, but this time without disrupting operations. 7. Processes are optimized, NOW is time to automate. AI adoption is not a top-to-bottom implementation, it should be gradual and focused on what’s actually going to lead to efficiency, then you can bring in the big guns. ROI is first. - Just Remove the Friction -

VibeCoding is so underestimated. I’m been building software for over a decade. For me this is beyond creating apps, it opens a whole new window of possibilities it’s not even funny.

AI is like another tool: You use tools to accomplish a goal, not because it’s interesting or cool. The difference is AI can help you find the goal, then use it, but the goal is a requirement.

AI tools are useless if they don’t solve YOUR problems or improve your business/life. Stop focusing on tools and start becoming better identifying obstacles and bottlenecks. The name of the game is - Just Remove the Friction -