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You don’t need to be a coder (or a mind reader) to actually know what’s people are saying inside your custom GPT conversations. You just need the right system—and a little bit of “let’s figure this out together” energy. Here’s the big shift: In my latest video, I showed you how to automatically send your customer's GPT conversations (with permission!) straight into an Airtable database. It’s a permission-based workflow that lets you see what your audience is asking, collect leads, or even power up your course support—without burning out or getting lost in the weeds. Why does this matter? Because if you’re a solo creator, coach, or digital service provider, you’re probably tired of guessing what’s working or what your people need. Missed the video? Drop NEWSLETTER in the comments and I’ll send over the next video (when it goes live) in your inbox. Deep dive video (newsletter audience got it first), here you go: https://lnkd.in/eCuzx6-f Link in bio to get all the tools we recommend to 3000+ Knowledge Creators who are automating their business 📩

Forget “prompts.” Now Claude runs Skills... Tiny folders packed with expertise. Each skill = your playbook: instructions, scripts, workflows. Claude loads only what’s relevant. Excel formulas? Brand voice? Data parsing?... Done. It’s like giving Claude a mini-MBA in your company. → Build once, use everywhere (Claude apps, Code, API). → Combine skills like LEGO. → Even run code when words aren’t enough. This is where AI shifts from “assistant” → “specialist.” If you’re serious about AI workflows, start building Skills. They’re how you turn Claude into your in-house expert. Check out this video in which I share how to start using "Skills" and include a simple example of automating Watermarks for ROAS PIG

Messy inputs=slow decisions. BB’s Daily Byte: turn chaos into clear, actionable summaries in minutes. Use the SCALE loop while you watch: S — Summarize: Paste notes/emails/docs → 5 bullets + 3 actions. C — Craft: Set role, task, context, constraints, and output format. A — Iterate: Ask 3 versions; have AI self-critique; apply one improvement. L — Launch: Format for your channel; assign an owner + due date; track one KPI. E — Evolve: Template the prompt; automate the handoff; weekly review; log ROI + next sprint. Register for our Nov 20 “AI in Business” conference — Link in first comment. Question: Which step is hardest in your org right now, and how do you keep the human handoff crisp?

🌟 The Engineer’s New Toolkit Modern engineers are no longer defined by how many tools they know but by how they think with them. Old playbook: 🧰 Learn frameworks, memorize syntax, repeat solutions. New playbook: 🤖 Use AI to explore possibilities. ⚙️ Automate what slows you down. 🧠 Understand context like business, users, and systems. 💬 Communicate with clarity across teams. The next generation of engineers will not stand out by being tool experts. They will stand out by being strategic thinkers who turn complexity into clarity. #FutureOfEngineering #AIInTech #SystemThinking #EngineeringLeadership #InnovationMindset

Think specs are dead? Not quite. They’re just evolving 👇 As we've been toying more with prototypes in tools like Reforge build, I can see the hand-off from product to the rest of the org changing slightly. The power of "show, don't tell" is strong with prototypes and they bring your ideas to life in a much neater way. But this doesn't mean the PRD is dead. 🧾 Short specs for strategy and edge cases. 🧩 Forkable prototypes for experience and fast feedback. This way, words still give direction. But prototypes provide the core vision. I wrote about how AI tools are making this combo the new normal, and why it’s finally time to stop writing docs nobody reads (Link in the comments) 👇

Most businesses are drowning in repeat work they don’t even see. Here’s my quick 3-minute audit to find automation gold: 1️⃣ Write down every task you’ve done twice this week. 2️⃣ Circle the ones that follow a pattern. 3️⃣ Ask: does this task require judgment or just repetition? If it’s repetition → automate. If it’s judgment → support it with AI.. Try this today and you’ll spot at least 3 hidden time drains. What’s the most repetitive task on your plate right now?

=============================== CHAIN OF THOUGHT PROMPTS 🧠✨ =============================== WHAT IT IS: → A way to guide AI step by step instead of asking for the final answer directly. → Example: Add “Let’s think step by step” to your prompt. WHY IT MATTERS: → Helps the model *reason* instead of guessing. → Boosts accuracy for math, logic, planning & multi-step problems. WHEN TO USE IT: → Problem-solving (math, code, logic puzzles) → Breaking down complex ideas → Decision-making (pros & cons, analysis) EXAMPLES: ❌ "What’s 27 x 46?" ✅ "What’s 27 x 46? Let’s think step by step." ❌ "Write a marketing plan." ✅ "Let’s think step by step and create a marketing plan with clear goals, channels, and timeline." PRO TIP: Chain of thought = slowing AI down to get *smarter* answers. 🔑

You’re not inconsistent. You’re imitating systems that don’t fit your grace. The DDB Framework teaches: ➡️ Disrupt: Stop following blueprints not built for your assignment ➡️ Dismantle: End the pressure to perform like others. ➡️ Build: Create systems customized for your capacity. My AI Tip: “Design a daily structure based on my current workload and energy level.” The Oct 21st Masterclass helps you build your own blueprint.... not copy someone else’s.

Choosing the wrong AI lever wastes time and money. Use this simple rule to pick between Prompting, RAG, and Fine‑tuning. Quick definitions: - Prompting = better instructions. You change the words, not the model or data. - RAG (Retrieval‑Augmented Generation) = plug in your knowledge base. It fetches the right snippets from your docs and gives them to the model. - Fine‑tuning = teach patterns from many examples. It improves style and consistency, not new facts. When to use which: - Start with Prompting for tone, format, and one‑off tasks (emails, summaries, form fills). - Use RAG when answers depend on your private policies, SKUs, contracts, or SOPs—and those change often. - Consider Fine‑tuning only if you have thousands of clean, labeled examples and need consistent output at scale (support macros, underwriting notes, code style). Cost/Speed trade‑offs: - Prompting: fastest to ship; fragile on edge cases. - RAG: small setup (index your top 50 docs); cuts hallucinations; updates in minutes. - Fine‑tuning: upfront time/cost; cheaper per call later; retrain as the business shifts. Mini‑playbook (run in 14 days): 1) Pick one workflow worth $1k+/mo. 2) Build a 10‑question test set that a human can grade. 3) Baseline with Prompting; measure Correct Answer Rate and Time‑to‑Action. 4) If private info is needed or <80% correct, add RAG. 5) If style/consistency is still off and you have 1k+ examples, plan a Fine‑tune. Operational next step: This week, do steps 1–3. Next week, ship a small RAG pilot. BaseAim can co‑pilot the triage and deliver a working workflow in 14 days.

Choosing the wrong AI lever wastes time and money. Use this simple rule to pick between Prompting, RAG, and Fine‑tuning. Quick definitions: - Prompting = better instructions. You change the words, not the model or data. - RAG (Retrieval‑Augmented Generation) = plug in your knowledge base. It fetches the right snippets from your docs and gives them to the model. - Fine‑tuning = teach patterns from many examples. It improves style and consistency, not new facts. When to use which: - Start with Prompting for tone, format, and one‑off tasks (emails, summaries, form fills). - Use RAG when answers depend on your private policies, SKUs, contracts, or SOPs—and those change often. - Consider Fine‑tuning only if you have thousands of clean, labeled examples and need consistent output at scale (support macros, underwriting notes, code style). Cost/Speed trade‑offs: - Prompting: fastest to ship; fragile on edge cases. - RAG: small setup (index your top 50 docs); cuts hallucinations; updates in minutes. - Fine‑tuning: upfront time/cost; cheaper per call later; retrain as the business shifts. Mini‑playbook (run in 14 days): 1) Pick one workflow worth $1k+/mo. 2) Build a 10‑question test set that a human can grade. 3) Baseline with Prompting; measure Correct Answer Rate and Time‑to‑Action. 4) If private info is needed or <80% correct, add RAG. 5) If style/consistency is still off and you have 1k+ examples, plan a Fine‑tune. Operational next step: This week, do steps 1–3. Next week, ship a small RAG pilot. BaseAim can co‑pilot the triage and deliver a working workflow in 14 days.