Two years ago, a simple conversation set me on a path I did not fully anticipate.
Today, as I complete my EMBA and receive my postgraduate degree, I am not closing a chapter, I am opening a new one centered on growth, curiosity, and continuous learning (1/13)
The engineer who built Claude Code just dropped a 28-minute video on how to write prompts that actually work
I've seen $300 courses that don't cover what he shows in the first 10 minutes
CLAUDE.md files, memory shortcuts, parallel sessions, prompting patterns
all in one video and completely free works whether you're a developer, a beginner, or someone who's been using Claude for months.
๐จ Anthropic just showed a 27-minute workshop on how to actually do prompts for Claude.
Taught by the people who built it.
Free. No registration. No paywall.
I've seen $300 courses that don't cover what they teach in the first 8 minutes.
Watch it and bookmark it now.
FORGET PowerPoint.
Claude can build an entire presentation in minutes!
No templates.
No design skills.
No all-nighters before the big meeting.
Just 6 prompts that do the work for you.
๐
๐ Prompt 1. The Blueprint
"Act as a senior presentation strategist. Build a blueprint for [topic].
Give me:
- The ONE message they must remember
- Who the audience is + what they care about
- 3 angles that hook them emotionally
- The slide-by-slide flow
- Ideal slide count
Keep it tight. No filler."
๐ Prompt 2. The Structure
"Create a slide-by-slide outline for [topic].
For each slide:
- Title
- One-line purpose
- What the audience should feel
Make the sequence build like a story โ tension, then payoff."
๐ Prompt 3. The Story Frame
"Turn [topic] into a presentation built on narrative.
Hook โ grab attention in 5 seconds
Problem โ the pain they feel
Insight โ the part they didn't expect
Solution โ what to do about it
Proof โ one stat or example
Takeaway โ a single clear action
Cut anything that doesn't move the story forward."
๐ Prompt 4. The Visual Direction
"Act as a presentation designer. For each slide on [topic], recommend:
- A visual that carries the emotion (image, not clipart)
- The right format for any data (chart type, not a table dump)
- An icon or grid layout for lists
Suggest a clean 3-color palette and one font pairing."
๐ Prompt 5. The Content
"Write the full slide content for a [number]-slide deck on [topic].
Per slide:
- A punchy title (6 words max)
- 3โ5 bullets, under 10 words each
- One speaker note for delivery
Audience: [describe]. Tone: [professional/casual]."
๐ Prompt 6. The Build
"Now build it.
Create the full presentation on [topic] as a downloadable file.
[number] slides with bold titles, tight bullets, and speaker notes on every slide.
Clean layout, logical flow from open to close, ready to present."
Most people still build slides line by line.
Manually. Slowly. Painfully.
The shift isn't about saving time.
It's about showing up sharper than everyone in the room.
While they format bullet points, you're already prepping the meeting.
Do this:
1. Save this post (you'll come back to it)
2. Pick 1 prompt โ build your next deck with it
3. Send it to someone still fighting with templates
๐ Fast. Clean. No excuses.
1. Follow @coder_surya
2. Save the post.
3. Repost to your network.
4. Join AI Community: https://t.co/ioQEJKhR1q
____________________________
for anyone asking where to learn this stuff:
โข RAG โ https://t.co/4bzbUIwV5g
โข Agentic RAG โ https://t.co/IotOiGmV1Y
โข AI Agents โ https://t.co/nEeMnVJQbk
โข Multi-Agent Systems โ https://t.co/pavDPVJEFj
โข LangGraph โ https://t.co/3miEqqFzF0
โข LangGraph (code) โ https://t.co/v7kxHZXqba
โข MCP โ https://t.co/lKawRb4etX
โข Memory Systems โ https://t.co/LSaT2UaPAS
โข Evals โ https://t.co/vxChxa1kqQ
โข Context Engineering โ search "Context Engineering Survey" on arXiv
and please skip the "build an ai agent in 10 minutes" videos
build something, watch it fail, then figure out why.
Google just cooked something wild. ๐คฏ
They dropped an AI model that runs on your laptop. No internet. No subscription. No cloud. Just your machine.
It's called Gemma 4 12B. And here's what makes it different from everything else out there.
It handles text and images in one single model. Most models this size can only do text. Gemma 4 12B reads images, reasons through problems, and does multi-step thinking all at once.
It performs almost as well as models twice its size. But needs less than half the memory to run.
If your laptop has 16GB, you can run it right now. No setup headaches works with LM Studio, llama.cpp, and every major local AI tool out of the box.
And Google released it under Apache 2.0 the most open license possible. Use it for personal projects, commercial products, anything you want.
Most people are paying $20/month to use AI through a browser.
Google just made a version you can own on your laptop and never pay for again.
Weights are live on Hugging Face. Go grab it.
IT Service companies say things like " a bridge is needed for AI transformation and we are the bridge" or that "AI is moving from pilot to industrialization" etc and that AI implementation projects may take time but this transformation cannot be done without them.
In the meantime, run rate for Anthropic revenue is US$ 50 billion and US$ 30 billion for OpenAi already, with most of it coming from enterprises. IF Anthropic IPO has to happen this yr, next year's run rate will need to be perhaps US$ 100 billion plus for it alone, for its IPO to go through.
My question: How come IT services companies are still waiting for AI implementation projects and at the same time enterprises will soon be spending US$ 100-200 billion on these 2 model companies alone. Who assisted these enterprises so that they are comfortable spending so much already (for it sure does not look like IT service companies saw anything substantial)? May be you don't need the amount of help that IT service companies think will be needed.
Logically, more help should be needed at this stage where models may be less developed and users are less familiar- and still they are presumably doing this on their own.
You tell me- I dont have the answers
Claude Code just crossed the line from โAI coding assistantโ โ โAI operating system.โ
And most developers still think itโs just autocomplete.
The March 2026 update changed everything.
Hereโs the complete Claude Code cheatsheet every AI engineer should know ๐
โก ๐๐ก๐ฆ๐ง๐๐๐
Mac
โ brew install claude-code
Windows
โ winget install Anthropic.ClaudeCode
npm
โ npm i -g @anthropic-ai/claude-code
๐จ ๐ง๐๐ ๐๐๐ ๐ ๐๐ฅ๐๐ ๐ฎ๐ฌ๐ฎ๐ฒ ๐จ๐ฃ๐๐๐ง๐
โ Opus 4.6 is now the default model
โ 1M token context window
โ Voice mode across 20 languages
โ /loop for recurring autonomous tasks
โ Remote control from your phone
โ Computer Use for desktop automation
โ HTTP Hooks for event-driven workflows
โ โultrathinkโ mode for maximum reasoning depth
This is no longer just โAI helping you code.โ
Itโs becoming an autonomous engineering environment.
๐ ๏ธ ๐๐๐๐๐๐ฅ ๐๐ข๐ ๐ ๐๐ก๐๐ฆ
/compact
โ compresses context by ~80%
โ huge token savings
/effort low|med|high
โ dynamically control reasoning depth
/plan
โ generates execution steps before coding
/voice
โ push-to-talk development workflow
/loop
โ recurring scheduled automation inside sessions
/rewind
โ undo code OR conversation state
/diff
โ inspect every code change Claude made
/btw
โ ask side questions without polluting context
Most devs only use prompts.
Power users operate Claude like an IDE-native agent system.
๐ง ๐ง๐๐ ๐ฅ๐๐๐ ๐ฃ๐ข๐ช๐๐ฅ = ๐๐ซ๐ง๐๐ก๐ฆ๐๐๐๐๐๐ง๐ฌ
Claude Code now has an entire ecosystem layer:
โ Skills
Reusable AI workflows auto-invoked at runtime
โ Subagents
Isolated context workers for parallel tasks
โ Hooks
Deterministic commands triggered on events
โ MCP
Universal protocol connecting tools + agents
โ Plugins
Package and distribute entire agent capabilities
This is the beginning of composable AI engineering.
๐ ๐๐๐๐จ๐๐.๐ ๐
Possibly the most underrated file in modern software engineering.
Claude reads it EVERY session.
Teams are now encoding:
โ architecture rules
โ repo maps
โ coding standards
โ deployment workflows
โ testing conventions
โ engineering philosophy
directly into the agent workflow.
CLAUDE.md is becoming:
โinfrastructure-as-context.โ
๐ธ ๐๐ข๐ช ๐ง๐ข ๐ฆ๐๐ฉ๐ ๐ ๐ข๐ก๐๐ฌ
โ /effort low for repetitive tasks
โ use Haiku for mechanical workflows
โ /compact aggressively
โ Batch API gives ~50% savings
โ Prompt caching cuts costs massively
Most people optimize prompts.
The best teams optimize context architecture.
The biggest shift nobody is talking about:
Developers are no longer just writing code.
Theyโre designing systems of agents.
Thatโs the future of software engineering.
Save this cheatsheet.
Youโll reference it a lot over the next year. ๐
What feature are you most excited about?
#Coding #DeveloperTools #ClaudeCode #AIEngineering #AgenticAI #LLM #SoftwareEngineering #Anthropic
Claude Code is (actually) easy.
The 12-step roadmap in plain English:
If you're totally new to Claude Code:
Beginner: https://t.co/2dPKJnEZMQ
Intermediate: https://t.co/HHtZFTfpq2
Advanced: https://t.co/tLKItVJZGR
PHASE 1: Context (what Claude knows about you)
Step 0: Install the CLI
One terminal command gets it running:
"npm install -g @anthropic-ai/claude-code"
Step 1: Projects
- Give Claude its own folder.
- Everything you build stays tied to it.
"I'm creating a new folder for my [project]. Create it for me and set it up so I can start working in it."
Step 2: claude .md
- Claude reads this before every chat.
- Role, voice, defaults. Set once, it sticks.
"Help me build my CLAUDE.md from scratch. Use Boris Cherny's CLAUDE.md as a starting template. Ask me about my business, voice, banned words, output defaults, and how I want you to work. Save the final file to ~/CLAUDE.md."
Step 3: Memory
- Every correction becomes a saved lesson.
- Same mistake never lands twice.
"From now on, whenever I correct you, save it as its own .md file at ~/.claude/projects/{project}/memory/, prefixed feedback_, user_, project_, or reference_. Index everything in MEMORY.md."
PHASE 2: Fire (how you trigger work)
Step 4: Skills
- Wrap a workflow in one keyword.
- Fire it from any chat, any folder, any time.
"Turn this workflow into a skill called /[name]. Set it up so I can fire it from any chat."
Step 5: /commands
Type the name and Claude fires the workflow.
"Save this prompt as a /[name] command. Set it up so I can run it any time."
Step 6: /plan
- Type /plan before starting any task.
- Claude lays out the steps. You approve it.
"/plan I want to [your task in plain English]."
PHASE 3: Extend (wire it to your stack)
Step 7: Hooks
- Auto-run something the moment an event fires.
- You never have to trigger it manually.
"Set up a hook that runs [thing you want] every time I [event]. Wire it up for me."
Step 8: MCP
- Plug Claude into Slack, Notion, Gmail, etc.
- You get live data from the tools you use.
"Connect Claude to [tool]. Set it up for me and walk me through it."
Step 9: Plugins
Install skills, agents, and MCPs in one command.
"/plugin install [plugin-name]"
PHASE 4: Scale (delegate and autopilot)
Step 10: Subagents
- Send out parallel workers.
- Get three jobs done at once.
"Use subagents to handle [task A], [task B] and [task C] in parallel."
Step 11: Agent Teams
- A pipeline of specialist AI agents.
- Each owns one job, hands off to the next.
"Build me an agent team for [process].
Step 12: Routines
- Schedule your agent team on the cloud.
- You set it once, walk away forever.
"/schedule [agent or skill] every [schedule]."
That's Claude Code from zero to autopilot.
12 steps with no coding background needed.
Repost โป๏ธ to help someone in your network.
Cc : Charlie
You type a prompt.
~400ms later, an answer appears.
Most people think the LLM โjust runs.โ
Reality?
A full infrastructure pipeline fires before the response reaches you ๐
1๏ธโฃ API Gateway
โ Auth
โ Rate limits
โ Billing starts
2๏ธโฃ Load Balancer
โ Routes traffic across clusters
3๏ธโฃ Tokenization
โ Text becomes tokens
โ Tokens become math
4๏ธโฃ Model Router
โ Sends request to the right model/GPU cluster
5๏ธโฃ Inference Engine (95% of latency)
โ Prefill
โ KV Cache
โ Decode tokens one-by-one
This is where the real compute happens.
6๏ธโฃ Post-Processing
โ Safety filters
โ Detokenization
โ Response packaging
7๏ธโฃ Response + Billing
โ Stream result back
โ Attach token usage + costs
Calling an LLM API isnโt โrunning a model.โ
Itโs orchestrating networking, distributed systems, GPUs, memory, routing, and billing โ in milliseconds. โก
The interesting question:
Where does โthe modelโ actually begin?
At inference?
Or at tokenization โ the moment language becomes math? ๐ค
#AI #LLM #MachineLearning #Infrastructure
Anthropic just dropped a 31-page prompting guide.
Here's everything you actually need (in 10 rules):
1. You write "review this contract" and pray.
Fix: Name every output. "Review this contract. Flag risks per clause. Rate severity 1-5. Return as a table."
2: You say "summarize this" on a 40-page report.
Fix: 4.7 sizes the answer to the input. Cap it: "5 bullets. Each under 15 words. Start each with an action verb."
3: You write "don't use jargon. don't be salesy."
Fix: Negative instructions don't stick.
Flip them: "Write in plain English a 16-year-old could read aloud."
4: You type "can you help me with the email?"
Fix: Each verb ships something. For example: "Go to Gmail. Find [contact]. Write the send-ready reply. Under 90 words. Tone: confident, casual."
5: You wait for Claude to web search on its own.
Fix: Claude opus 4.7 calls fewer tools than 4.6.
Force it: "Use web search aggressively. Verify every claim with at least 2 sources."
6: You miss the warm tone from old Claude.
Fix: Claude opus 4.7 is direct. Almost zero emojis. Paste 2-3 sentences in the voice you want.
Tell Claude to match the rhythm.
7: You ask for "a landing page" & get bare minimum.
Fix: Drop this one line on every creative task
โ "Go beyond the basics."
It's from Anthropic's own doc.
8: You forget Claude 4.7 doesn't reason by default.
Fix: They call it "adaptive thinking."
Add this at the end: "Think before answering (maximum reasoning)." Free upgrade. Every time.
9: You rewrite the same prompt 14 times a week.
Fix: A skill is a command with instructions pre-built.
Write the same prompt twice? Make it a skill.
10: You assume Claude knows what you meant.
Fix: Old Claude 4.6 guessed.
New Claude 4.7 does exactly what you typed.
Spell it out. Output. Order. Length. Tone. Format.
If you don't say it, you don't get it.
To go even further & download my .md files directly:
Step 1. Go to https://t.co/psB7XxB2Y4.
Step 2. Subscribe for free. Don't pay anything.
Step 3. Open my welcome email (most skip this).
Step 4. Hit the automatic reply button inside.
Step 5. Download my .md files from my Notion.
Bonus. Enjoy my best copy-paste prompts, too.
93% of Claude users have never gone past Layer 1.
They are competing against the 7% running all 7.
Here is every layer, and exactly what each one unlocks: ๐
The businesses leading in 2026 have not found a better AI.
They have gone deeper into the one everyone already has.
Here is the full 7-layer breakdown:
โ๏ธ 1. Claude Chat
โ Simple task assistance, quick Q&A, and daily text summaries.
โ Text reformulation, tone adjustment, and general knowledge on demand.
โ This is Layer 1. Most people never leave it.
โ๏ธ 2. Artifacts
โ Preview code outputs instantly and render SVG and UI components
โ View real-time data charts and draft web wireframes directly.
โ Everything visual that used to require a separate tool now lives here.
โ๏ธ 3. Claude Skills
โ Standardize your brand voice in .md files and hardcode SOPs.
โ Create repeatable content templates and set rules for text analysis.
โ Claude stops guessing your standards and starts executing every time.
โ๏ธ 4. Claude Cowork
โ Read and edit local text files, analyze complex spreadsheet data, and refine presentation decks.
โ Work directly within project folders and share code changes.
โ Claude becomes a collaborator inside your actual files.
โ๏ธ 5. Claude Design
โ Draft CSS styling rules, and generate functional HTML mockups.
โ Design work that used to take a full day gets done in a single session.
โ Get color palette recommendations, compose UI component libraries, and build custom app themes.
โ๏ธ 6. Claude Code
โ Debug logic errors in the terminal, refactor legacy codebases, and generate new project scaffolds.
โ Scan for security vulnerabilities, optimize performance, and configure database schemas and migrations.
โ Automate documentation, database schemas, and migrations without touching them manually.
โ๏ธ 7. Connectors
โ Link Google Drive and automate Slack notifications.
โ Sync Google Sheets data, and integrate Asana or Jira projects.
7 layers. Most teams are running 1.
The gap between Layer 1 and Layer 7 is not a skill gap.
It is a knowledge gap.
By the way, I wrote the complete step-by-step guide on how to build Claude Skills, Layer 3, from scratch.
It is the layer that compounds the fastest, and the one that most people set up wrong from day one.
Read it here โ https://t.co/IA6mhKbVhy
For more Claude breakdowns like this: ๐
โ Go to https://t.co/XZmlWQ3gEs
โ Subscribe to my free newsletter (don't pay anything)
โ Get more free and daily cheatsheets
Which layer are you currently stuck at? Drop the number below. ๐คฏ
โป๏ธ Repost to give your network an unfair advantage.
Become a Claude Certified Architect
Here are all the required resource in one place: (save it)
Training courses: https://t.co/kBXCuOrprM (13 free courses)
Cookbook: https://t.co/SLnSUT703t
Exam Guide: https://t.co/A2pbDcy8GC
Practice questions: https://t.co/90eXwUwL8i (free)
MCP documentation: https://t.co/SbwZI0eM61 (free)
API documentation: https://t.co/9rmnLWxRHE (free)
Partner Network: https://t.co/diT5OE5H0b (free to join)
Link to join: https://t.co/OXQyTmf4wD
Personal Playbook someone created after the exam: https://t.co/qhXan3XnBK
You install Claude Code and stop there.
Here are 24 things (actually) worth adding:
If you're totally new to Claude Code:
Start here: https://t.co/anqXrH7023
Then read: https://t.co/rLIC8yh90e
Plug-Ins (bundled tools, agents, and commands)
gstack โ 23 specialist dev tools in one install
Install โ https://t.co/vuqqtNf2tr (82.7kโ )
superpowers โ complete dev methodology, 14 skills
Install โ https://t.co/x2Jz14cYY8 (192kโ )
codex-plugin-cc โ OpenAI's official Codex plugin
Install โ https://t.co/iCSxJ0glm5 (8.9kโ )
financial-services โ IB, PE, equity, wealth
Install โ https://t.co/jPb9r63pMN (23kโ )
claude-for-legal โ legal workflows, every practice area
Install โ https://t.co/bCzJdc8WzM (6.6kโ )
claude-skills โ 263+ skills across every platform
Install โ https://t.co/62p22Wd18G (5.2kโ )
marketingskills โ 40 marketing tools, full growth ops
Install โ https://t.co/FPY9dXG929 (28.8kโ )
social-media-skills โ my content OS. Posts, reels
Install โ https://t.co/DOc68CfxJa
Skills (specialist instruction Claude loads on demand)
frontend-design โ kills generic AI UI
Install โ https://t.co/fRegzmoq96 (277k installs)
hyperframes โ write HTML, render video, agent-native
Install โ https://t.co/tvY90QlFJL (18.6kโ )
ai-second-brain โ Karpathy-style wiki, AI history
Install โ https://t.co/mebUAilN9u
notebooklm-skill โ Claude queries your research
Install โ https://t.co/sAxeEGpzyy
humanizer โ strips AI writing tells from any draft
Install โ https://t.co/zadJrx1BVe (2.9kโ )
claude-seo โ GEO-first SEO skill, built for the AI era
Install โ https://t.co/8mhcDiM7uq (4.5kโ )
antfu-skills โ Vue and Vite core team skills
Install โ https://t.co/mmdjG21aJ5 (3.5kโ )
caveman โ cuts 65% of tokens, talks like caveman
Install โ https://t.co/WruteJgNW4 (59.2kโ )
MCP Servers (live connections to your apps)
granola โ meeting notes fed to Claude
Install โ https://t.co/P6nWgUShBA
slack โ reads channels, posts updates
Install โ https://t.co/USdCGuACdH
notion โ reads and writes your docs
Install โ https://t.co/4z1XL34D3c
kondo โ triages your LinkedIn DMs
Install โ https://t.co/CjPiBbvdmX
zapier โ 9,000+ apps, one connection
Install โ https://t.co/pyxD0brsoi
higgsfield โ cinematic video from a prompt
Install โ https://t.co/X0y90vVW4B
perplexity โ live web search for Claude
Install โ https://t.co/hpDE0w2rR0
agent-browser โ browser automation, fewer tokens
Install โ https://t.co/AKqEWoENFX (22kโ )
Save this. Come back when you set up Claude Code properly.
Repost โป๏ธ to help someone in your network.
P.S. Which one are you installing first?
๐๐ ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐บ๐ฒ๐ป๐ ๐ถ๐ ๐ผ๐๐ฒ๐ฟ๐ต๐๐ฝ๐ฒ๐ฑ. That is what I told myself when I first started working on AI products. Turns out, I had no idea what an AI PM really did.
After spending years watching world-class AI PMs, building AI products at scale, making 100s of bad decisions, I have a much better definition of the role.
But, sadly, even today, most PMs trying to work on AI are in the same boat: confused and clueless about "what does an AI PM actually do."
Here's the simplest mental model to think of an AI PM's role:
An AI PM is responsible for finding answers to these 7 questions.
1. What problem should we solve to maximize impact?
2. Does this need AI?
3. Do we have the right data?
4. How do we turn data into something useful?
5. How will users experience it?
6. How do we know it works before launch?
7. How do we keep making it better?
Let's understand in detail:
๐ช๐ต๐ฎ๐ ๐ฝ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ ๐๐ต๐ผ๐๐น๐ฑ ๐๐ฒ ๐๐ผ๐น๐๐ฒ The problem must be specific, validated with real users, and solution-agnostic. If you get this wrong, the model does not matter.
๐๐ผ๐ฒ๐ ๐๐ต๐ถ๐ ๐ฟ๐ฒ๐ฎ๐น๐น๐ ๐ป๐ฒ๐ฒ๐ฑ ๐๐ This is the most important question an AI PM asks. And the answer is usually no. Saying no to AI when the situation does not call for it is not a failure. It is the job.
๐๐ผ ๐๐ฒ ๐ต๐ฎ๐๐ฒ ๐๐ต๐ฒ ๐ฟ๐ถ๐ด๐ต๐ ๐ฑ๐ฎ๐๐ฎ "We have data" is not a strategy. An explicit data plan that includes what data we need, what we have, and what is missing is the right strategy. AI is only as good as the data behind it.
๐๐ผ๐ ๐ฑ๐ผ ๐๐ฒ ๐๐๐ฟ๐ป ๐๐ต๐ฒ ๐ฑ๐ฎ๐๐ฎ ๐ถ๐ป๐๐ผ ๐๐ผ๐บ๐ฒ๐๐ต๐ถ๐ป๐ด ๐๐๐ฒ๐ณ๐๐น Simple prompt, ML model, RAG, or agents. Each has a different use case, cost profile, and failure modes. The PM who skips this hands those decisions to engineering.
๐๐ผ๐ ๐๐ถ๐น๐น ๐๐๐ฒ๐ฟ๐ ๐ฒ๐ ๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ถ๐ Users need trust, control, and recovery. Design for when the AI fails, not only for when it works.
๐๐ผ๐ ๐ฑ๐ผ ๐๐ฒ ๐ธ๐ป๐ผ๐ ๐ถ๐ ๐๐ผ๐ฟ๐ธ๐ ๐ฏ๐ฒ๐ณ๐ผ๐ฟ๐ฒ ๐น๐ฎ๐๐ป๐ฐ๐ต There is no binary pass/fail. Build an eval framework. Define good, bad, and edge cases. Ship only when the product clears your threshold.
๐๐ผ๐ ๐ฑ๐ผ ๐๐ฒ ๐บ๐ฎ๐ธ๐ฒ ๐ถ๐ ๐ฏ๐ฒ๐๐๐ฒ๐ฟ ๐ฎ๐ณ๐๐ฒ๐ฟ ๐น๐ฎ๐๐ป๐ฐ๐ต AI products degrade in production if you stop watching them. Sample live conversations. Add new failure modes to your test set. Never stop monitoring.
--
Want to ship your first AI product? I just launched a free Claude Code course taught inside Claude Code. (Link below)