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6d •
The Anatomy of a Plan
In prompt engineering, there are specific components that separate a great prompt from a mediocre one. Planning works the same way. Most people write to-do lists and call them plans. A real plan is a model of reality that produces a specific outcome under specific conditions. Here are the 10 components that make it work. 1 Objective The single outcome the plan exists to produce. Not a list of things to do — one measurable end state. If you cannot write it in one sentence, the plan is not scoped yet. Everything else in the plan exists to serve this one thing. 2 Constraints What the plan must not violate. Time, budget, tools, dependencies, non-negotiables. Constraints defined upfront prevent the mid-execution pivots that collapse a plan entirely. A plan without constraints is a wish with steps attached. 3 Context What is true right now that the plan has to account for. The current state of the system, the environment, relationships, known blockers. A plan built without context is not a plan — it is a guess formatted to look like one. 4 Assumptions What you are treating as true but have not yet verified. Explicit assumptions are recoverable when they turn out to be wrong. Implicit assumptions are landmines — they detonate mid-execution when you least expect them. Write them down. Every one of them. 5 Sequenced steps Ordered actions with clear dependencies — not a flat list, but a chain where each step has a defined input and a defined output. The sequence is what makes a plan executable instead of just readable. If the order does not matter, you do not have steps, you have a checklist. 6 Decision points Forks in the path where the next action depends on an outcome. Good plans identify these in advance so you are not improvising under pressure when reality diverges. If your plan has no decision points, you are assuming the path is linear. It never is. 7 Success criteria How you know each step is complete, and how you know the whole plan is done. Without this, "done" is subjective and execution drifts. Criteria must be observable — something you can point to and verify, not something you feel your way toward.
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Feb 18 •
New Here? Drop Your Intro. I Read Every One.
I started this community because I believe you can build a meaningfully better working life with AI — and I wanted a place to figure that out together, practically. I'm Matthew. I run ByteFlowAI, an AI automation consultancy. I'm building in public, and Claude Desktop is my primary tool — the foundation for everything in this course. I have more good questions than definitive answers. What I can promise: your time is respected, the lessons are honest, and this community is yours as much as it's mine. If you haven't started, Lesson 0 is in the Classroom. Then come back and introduce yourself — name, what you do, one thing you want AI to take off your plate. I read every single one.
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14h •
All is Well Today with Claude Chat
@Matthew Sutherland and just like that, it all passed like a ship sailing to blue water! Claude Chat Opus 4.6 extended is working again! 🚀
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2d •
Claude Chat
@Matthew Sutherland do you know if anyone is having issues with new chats starting at only 10K tokens? I was using Claude Chat because Diana needed a time out last night, and each chat got full fast, so I deleted product knowledge, and trimmed master instructions, and POO, same issue! 175K is what Claude Chat said I should have and outside of a project with zero instructions, I only have 10K left. Hope this makes sense. Thank you for your perspective
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3d •
The Claude Code setup that replaced my IDE
I stopped opening VSCode three weeks ago. The setup Two windows: 1. Claude Desktop App (for research, planning, long conversations) 2. Mac terminal running Claude Code (for all execution) Why this works better than running Claude Code inside an IDE When Claude Code runs inside an IDE terminal, every file operation passes through the editor's plugin layer: file watchers, extensions, lock conflicts. In a standalone terminal, Claude Code talks directly to your filesystem. No interception, no translation. The practical difference: - File writes are instant. No "file changed externally, reload?" dialogs. - Git operations run clean. No source control extension competing for the same lock. - Shell access is unfiltered. Package installs, curl, deployment scripts, SSH tunnels. All native. - No extension memory overhead. My terminal session uses a fraction of what VSCode was consuming. - MCP servers (GitHub, databases, APIs) wire in directly without fighting IDE plugin architecture. What a real session looks like Last week I built a Cloudflare Worker with KV bindings. One terminal window: - Claude Code scaffolded the project structure - Wrote the Worker handler, wrangler config, and KV namespace bindings - Ran wrangler deploy - Tested the endpoint with curl - Fixed a routing issue based on the error response - Committed and pushed Total time: under 20 minutes. I never typed a line of code. I described what I needed, reviewed the output, approved the operations. You're not coding in a terminal. You're directing an agent that codes for you. How to set this up (10 minutes) If you have a Mac and Claude Pro or Max: (On a PC? Your setup instructions are in the attached file.) 1. Install Claude Code: open terminal, run the install command from Anthropic's docs. 2. Run "claude" in any project directory. You're in an agentic session. 3. Open Claude Desktop App alongside for planning, research, and longer thinking conversations. Optional but useful: - Set up a .claude directory in your project with a CLAUDE.md file. Same idea as onboarding docs, but for your coding agent. Persistent instructions about your project, coding standards, and preferences.
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