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Zain Kahn

This guy from Cambridge plays with Claude Code like he owns it.

He talks about his workflow in 2026 and here's what's new: 

1. Video-Based Specification (Spec Phase)

> Screen Recording: 

Instead of writing a spec from scratch, find an existing product that is similar to your idea. Record your screen while using it and talking through your specific feature ideas and changes.

> Generate PRD: 

Upload this video to Gemini 1.5 Pro (referred to as Gemini 3 Pro/Free Pro in the video context) and ask it to generate a Product Requirement Document (PRD).

> Refine Spec: 

Use the "Ask User Question" tool in Claude Code. Prompt it to interview you about the generated spec to fill in missing details (e.g., "How should the emoji picker be positioned?").

> Package Discovery: 

Feed the refined spec into ChatGPT with "Heavy Thinking" (likely OpenAI's o1/o3 models) to search for and recommend specific, well-maintained GitHub packages (e.g., for a WYSIWYG editor) to avoid building complex components from scratch.

2. The Orchestrator Role

> Design Feedback Loops: 

Your primary job is not to write code but to design loops where the agent can build, fail, and learn.

> Monitor & Update: 

Watch the agent’s reasoning. If it makes a mistake, don't just fix the code—update the claude. md (project instructions file) to prevent that specific mistake from happening again.

> High-Level Decisions: 

Make the architectural decisions the agent can't, such as choosing the database or specific tools.

3. Model Choice & Tools

> Model Selection: 

Use Opus 4.5 for building large-scale features and GPT-5.2 for architecture and debugging (specific future models mentioned in his 2026 context).

> Voice Dictation: 

Use HyperWhisper to dictate prompts significantly faster than typing.

4. Execution & "Parallel Vibe Coding"

> Parallel Agents: 

For small, well-defined tasks (like extracting hard-coded strings for translations), spin up multiple sub-agents to work on different parts of the project simultaneously.

> Avoid Conflicts: 

Do not use parallel agents for large features within the same project to avoid complex merge conflicts ("meshing issues").

> Sub-agents for Multi-Project Fixes: 

If a bug exists in a template used by multiple projects, spin up one sub-agent per project to fix them all in parallel.

5. Review & Maintenance

> Planning Mode: 

Use Claude Code’s "Planning Mode" to prevent Architectural Drift, ensuring the agent sticks to the original design vision over time.

> Shape of Diffs: 

Inspect the "shape" of the code changes (diffs) to ensure they are manageable and align with expectations before accepting them.

> Forking for Learning: 

If the agent does something surprising or complex, fork the session. In the forked session, ask "Why did you do that?" or request diagrams to understand the code without polluting the context of the main working session.

Get more tutorials here: https://lnkd.in/e64Jvdrt

Follow me to learn how you can leverage AI to boost your productivity and accelerate your career. Scaled products to 10 Million+ users.

Traditional computer science degrees can't keep up with this pace.

Here are the 15 engineering blogs that actually teach real-world scale:

1 → THE CODE
Scale at global level.
Teaches you how to code with AI and AI Agents
https://lnkd.in/e64Jvdrt

2 → Airbnb Tech Blog
Product engineering done right.
User focused systems.
https://airbnb.tech/blog/

3 → Meta Engineering
Billions of users infrastructure.
Performance at extreme scale.
https://engineering.fb.com

4 → AWS Architecture
Cloud design patterns revealed.
Production ready blueprints.
https://lnkd.in/gqjh88PS

5 → Netflix TechBlog
Streaming at massive scale.
Chaos engineering explained.
https://lnkd.in/gNE8Cs6Z

6 → Discord Engineering
Real time systems mastery.
Handling millions of connections.
https://lnkd.in/gea6kSwt

7 → Google Research
Cutting edge tech breakthroughs.
Tomorrow's solutions today.
https://lnkd.in/gjzDu8wp

8 → NVIDIA Developer
GPU powered computing insights.
AI infrastructure secrets.
https://lnkd.in/dt_BW7qF

9 → Slack Engineering
Collaboration platform internals.
Distributed systems at scale.
https://slack.engineering

10 → Cloudflare Blog
Internet infrastructure deep dives.
Security and performance wins.
https://lnkd.in/gqa-HE6h

11 → Figma Tech Blog
Collaborative design systems.
Browser performance magic.
https://lnkd.in/g2KF_eX9

12 → Shopify Engineering
E-commerce at scale.
Black Friday traffic handled.
https://lnkd.in/g7DVzRAc

13 → Stripe Engineering
Payment systems that work.
Financial infrastructure explained.
https://lnkd.in/gfMr-jEr

14 → Microsoft Engineering
Enterprise scale solutions.
Developer tools insights.
https://lnkd.in/g3Mi8XES

15 → GitHub Engineering
Code collaboration at scale.
Developer platform secrets.
https://lnkd.in/gPHaD6AC

16 → Bonus
System design deep dives.
https://lnkd.in/g-tP7eEc

Save this for later.
Repost ♻️ for aspiring engineers.

Follow me for more AI playbooks and engineering resources.

Claude Code is only as good as your orchestration workflow.

I spent 6 months testing it so you don't have to. 

[ P.S. You can get my Ultimate Claude Code guide for engineers here at no cost: https://lnkd.in/e64Jvdrt ]

So Boris Cherny (the creator of Claude Code at Anthropic) recently shared the internal best practices his team actually uses daily. 

Someone brilliantly distilled those threads into a structured CLAUDE .md file you can drop straight into any project root.

It acts as a system prompt. Turns Claude into a far more autonomous, rigorous engineering partner.

Here's what it does:

→ 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: Mandates "Plan Node Default" for any task over 3 steps. Uses subagents liberally to keep the main context window clean.

→ 𝗦𝗲𝗹𝗳-𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁 𝗟𝗼𝗼𝗽: This is the real magic. After ANY correction, it updates a tasks/lessons .md file. You're building a compounding system where the mistake rate drops over time because it actively learns from your feedback.

→ 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗕𝗲𝗳𝗼𝗿𝗲 𝗗𝗼𝗻𝗲: Can't mark a task complete without proving it works. Diffs behavior. Runs tests. Checks logs. The bar? "Would a staff engineer approve this?"

→ 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗕𝘂𝗴 𝗙𝗶𝘅𝗶𝗻𝗴: Zero hand-holding. Point it at failing CI tests or error logs... it just goes to work. No constant context switching from you.

→ 𝗦𝘁𝗿𝗶𝗰𝘁 𝗧𝗮𝘀𝗸 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Forces a "Plan First" approach written to a todo .md with checkable items before any implementation starts.

And perhaps the most important part?

It forces the AI to prioritize simplicity, find root causes instead of temporary fixes, and minimize the blast radius of every change. Senior developer standards. Not shortcuts.

If you're spending hours a day in the terminal with AI, setting up a strong .md instruction file like this isn't optional anymore. It's the difference between AI that drifts and AI that compounds.

It takes time to set up. But if you do, you're ahead of almost everyone else.

Lemon is the most powerful tool I've used since ChatGPT.

You literally say things with your voice and it does it for you instantly.

Pure magic.

Alex Banks

Building a better future with AI

Alex Banks is a founder, creator and investor. He reaches over 1 million people on social media each week with insights into the world of artificial intelligence (AI).

He is the founder and writer of The Signal, a weekly newsletter that cuts through the AI noise to over 55,000+ readers.

Alex is also an active early-stage investor and advisor to startups across the AI and technology landscape.

👉 All partnerships, enquiries and speaking engagements: contact@noisemedia.ai

Writer

Unitree's G1 humanoid undergoes brutal stress testing.

And I can't stop watching.

The robot in question is the Unitree G1 humanoid:

• 1.32m tall, 35kg build
• 23 degrees of freedom for human-like movement
• 2m/s walking speed
• Advanced 3D LiDAR and sensors
• 2-hour battery life
• $16,000 price tag

It’s even available to buy at Walmart.

G1 has now learned an "Anti-Gravity" mode.

This means that stability is greatly improved under any action sequence.

Even if it falls, it can quickly get back up in under 2 seconds.

The robot has essentially learned to “hack” physics.

You can see in the video that it uses the inertia from bouncing to perform some action.

Knock over the average human and we’ll be on the ground for at least a couple of minutes.

My takeaway:

Whilst “violence tests” are fun for attention.

I’m more interested in seeing real demos that people actually care about, like doing the dishes, vacuuming, laundry, etc.

Control for body mechanics is mostly solved right now.

But fine motor skills, specifically hand dexterity, are the real bottleneck.

When we achieve this and understand how to scale manufacturing, the future is unlocked.

Follow me Alex Banks for daily AI highlights and insights.

I cover the most important AI developments each week in my newsletter.

Subscribe here: https://lnkd.in/ePSZP6KF

P.S. He forgot to sweep the leg…

The gloves are off.

Anthropic just spent $8M to troll OpenAI. And it’s genius.

Their new Super Bowl ad announces one thing: Claude will remain ad-free.

They're using the most expensive ad platform on Earth to differentiate on being anti-ads.

None of the ads call out ChatGPT by name. But the target is obvious.

OpenAI confirmed last month that ads are coming to ChatGPT for free and lower-tier users.

Why this matters:

→ AI chatbots are becoming our most trusted advisors
→ We ask them about health, finances, relationships, career decisions
→ The moment ads enter that conversation, trust erodes
→ Your AI stops working for you and starts working for advertisers

My takeaway:

This is genuinely brilliant positioning.

Spending $8M on ads to say you don't do ads is the kind of irony that proves exactly why the ad model is so powerful.

It reminds me of Black Mirror's "Common People" where a brain surgery patient becomes a walking billboard due to a synthetic neural implant.

We laughed at that episode. Now we're watching the first chapter play out in real time.

First ads will make their way into AI chatbots.

When brain-computer interfaces roll out in the 2030’s and 2040’s where does humanity stand?

But perhaps the more immediate question:

Does 90% of Super Bowl spectators actually have a clue what these companies are fighting about?

I’ll be exploring this idea further in my newsletter this weekend.

Subscribe here: https://lnkd.in/ePSZP6KF

And follow me Alex Banks for daily AI highlights and insights.

Anthropic said no to the Pentagon.
OpenAI signed the deal hours later.
Here's what happened:

Anthropic drew two red lines with the Department of War:

1. No mass domestic surveillance
↳ AI can now analyse bulk data the government buys on Americans at scale
↳ Currently legal, but only because the law hasn't caught up

2. No fully autonomous weapons
↳ AI isn't reliable enough to automate selecting and engaging targets
↳ No oversight framework exists for removing humans from the loop

For context:

→ Anthropic was the first AI company on the classified cloud
→ Deployed across intelligence, cyber ops, and combat support
→ Forfeited hundreds of millions cutting off CCP-linked firms
→ These two red lines represent ~1% of use cases

The Pentagon gave Anthropic a 3-day ultimatum.

Anthropic refused.

The response:

→ President Trump: "Their selfishness is putting AMERICAN LIVES at risk"
→ Secretary of War Pete Hegseth: Anthropic is a "supply chain risk"
→ Trump ordered every federal agency to cease all use of Anthropic's technology

Then OpenAI entered.

On Friday morning, Altman publicly backed Anthropic's red lines.

By Friday evening, he'd signed the Pentagon deal himself:

→ OpenAI claims the same red lines as Anthropic, plus a third
→ OpenAI asked the Pentagon to offer identical terms to all AI labs
→ Multiple OpenAI employees signed an open letter supporting Anthropic
→ Altman admitted the deal was "definitely rushed" and "the optics don't look good"

The consumer backlash was immediate:

→ "Cancel ChatGPT" went viral across Reddit and X
→ Claude hit # 1 on the App Store, overtaking ChatGPT
→ Claude is now # 1 in Germany, Canada, and other markets

My takeaway:

Not only have I seen my workflows fully transition from ChatGPT to Claude over the last year, but the consumer mass-market is catching up.

I think it’s also important to point out that correlation doesn’t necessarily mean causation here.

Claude didn’t just hit # 1 in the app store as a result of ChatGPT accepting the DOW deal.

Anthropic has simply built a better product where the timing of adoption happened to coincide with this viral uproar of the company denying use of their products for the surveillance of Americans and operation of autonomous weapons.

Ethical positioning now has direct commercial consequences.

Values are becoming a competitive moat.

I covered this idea yesterday in my newsletter.

Be the first to receive it by subscribing today.

Read it here: https://lnkd.in/e898z7SG

Use this system prompt in Claude to write humanised content.

Paste it directly into custom instructions.

1. Go to New chat
2. Add files, connectors, and more
3. Use style
4. Create & edit styles
5. Create custom style

This catches most issues before they happen.

But for text that's already written (or when you need to clean up existing AI content).

You’ll want to use the “master humaniser prompt”.

It walks the AI through a systematic humanisation process.

Access it here: https://lnkd.in/eE7ArSCx

The people building AI keep walking away from it.

And they're not leaving quietly.

In the past week alone:

1. Mrinank Sharma, Anthropic's Safeguards Research lead, resigned with an open letter declaring the world is facing "interconnected crises."
2. Zoë Hitzig, an OpenAI research scientis,t published a New York Times op-ed warning about user manipulation through ChatGPT's emerging ad strategy.
3. Two more xAI co-founders left (half the founding team is now gone)

Rewind further and the list grows:

→ Ilya Sutskever, OpenAI's co-founder, left to start a safety-focused company (May 2024)
→ Jan Leike, co-lead of OpenAI's Superalignment team, resigned saying safety had taken a backseat (May 2024)
→ Miles Brundage, OpenAI's senior advisor for AGI readiness, warned that no lab is prepared for what's coming (October 2024)

Every industry has turnover.

But this isn't normal turnover.

These are researchers who spent years building the most advanced AI systems ever created.

And something about what they saw made them walk away.

If the people who understand this technology best can't reconcile building it with their own conscience, what does that tell the rest of us?

Or are they partnering with national publications to generate clicks while leaning into the "fear AI" angle to drive demand for their next venture?

Only time will tell.

Follow me Alex Banks for daily AI highlights and insights.

I explore ideas like this weekly in my newsletter The Signal.
Subscribe here: https://lnkd.in/ePSZP6KF

Everyone's focused on Google, Claude, and OpenAI. 

Amazon is AI's sleeping giant.

They just quietly dropped Nova Act. It builds browser agents for you.

→ Navigate websites autonomously
→ Fill forms and extract information
→ Handle bookings and purchases
→ Deploy to production with one command

How it works:

1. Prototype in their online playground (no setup needed)
2. Build in your favourite IDE (VS Code, Cursor, Kiro)
3. One CLI command deploys to AWS
4. Monitor performance through the console

Built-in human escalation means when the agent hits something it can't handle, it asks you, then continues.

My takeaway:

This reminds me of Google in early 2023.

Everyone counted them out after a few fumbled launches.

Now they're leading the AI race.

Amazon has something most AI companies don't:

→ Massive distribution (hundreds of millions of customers)
→ Unmatched logistics and data infrastructure
→ AWS already powers most of the internet
→ Deep pockets to play the long game

By the end of 2026, Amazon will be a very real contender in AI.

The quiet ones are often the most dangerous.

You can try Nova Act today at https://fandf.co/4p5DHrn

Big thanks to Amazon for partnering with me on this.

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