Devam Shah

CIO and CISO | Co-Founder - Bootstrapped

#innovations, #startuplife, #leanstartups, #informationsecurity, and #informationtechnology

[Paul Couvert @itsPaulAi]

Wow so Google has just open sourced a tool to automate ANY task on mobile

ARTEMIS turns prompts into automation:

- 99%+ success rate (!!)
- Integrates w/ Codex, Claude Code, Antigravity
- Automates workflows + captures logs

And the roadmap is VERY interesting:

They want to add an on-device VLM so basically local execution with lightweight edge vision models for privacy-first automation.

[Tech with Mak @techNmak]

A 118K-star GitHub repo is built around one painfully obvious idea:

Your coding agent should map the codebase once, not grep it forever.

Graphify turns an entire project into a queryable knowledge graph.

Functions, classes, files, SQL schemas, infrastructure, docs, PDFs, images and videos become connected nodes that an agent can traverse instead of repeatedly opening files and reconstructing the architecture.

So instead of:
→ search for authentication
→ open twelve files
→ follow imports manually
→ lose the trail as the context fills up

The agent can ask:
> What connects authentication to the database?
> Trace the path from UserService to DatabasePool.
> Explain RateLimiter.
> Which concepts does everything flow through?

Graphify returns the relevant subgraph and the path connecting the concepts, not another list of keyword matches.

For source code, this is not RAG:
→ No embeddings
→ No vector database
→ No LLM required
→ Code is parsed locally using tree-sitter
→ Calls, imports and inheritance become graph edges

Every relationship is also marked as EXTRACTED, INFERRED, or AMBIGUOUS, so the agent can distinguish what exists explicitly in the source from what Graphify resolved or guessed.

The cleverest part is what happens next.

Graphify can install hooks or persistent instructions for Claude Code, Codex, Cursor, Gemini CLI, Copilot and 20+ other assistants.

Before the agent starts blindly grepping or reading files one by one, it is nudged to query the existing graph first.

The graph can be committed to Git, automatically rebuilt after commits, shared across the team and exposed through MCP.

Long context windows help agents read more code.

A persistent knowledge graph helps them know where to look.

The next improvement in coding agents may not come from stuffing more files into the prompt.

It may come from making them stop rereading the repository.

Here's the GitHub Repo: https://t.co/4ify3X8urp

[Maxwell Orion @Orion_Vers7x]

50 legendary internet rabbit holes you can spend hours exploring👇

1. https://t.co/1Xl8gX5LAC — Watch the world via live satellite imagery
2. https://t.co/7hmmVh8I8T — See every plane currently in the sky
3. https://t.co/hCvocVzVWl — Track all ships at sea in real time
4. https://t.co/fT6ZeVPmyy — Live map of winds and storms
5. https://t.co/iSXlo7Hcmi — Watch lightning strikes hitting Earth in real time
6. https://t.co/jdhKHP1Jnu — Live list of recent earthquakes
7. https://t.co/XnmnCU49SH — Ocean cables carrying the internet
8. https://t.co/szocPJSOCd — Watch forests disappear from space
9. https://t.co/R5Sf8KQzi7 — The world's statistics, second by second
10. https://t.co/yyIvF0Cvbw — Current number of tweets and searches being posted
11. https://t.co/RcN3BikFkp — Compare the true sizes of countries
12. https://t.co/Bj8ljhy6Q1 — Maps from centuries ago
13. https://t.co/LiEwtbzHEp — Archive of 150,000 historical maps
14. https://t.co/DGLYEVUSmP — World map drawn by volunteers
15. https://t.co/MFZrwabt3a — Look out the window of a random person around the world
16. https://t.co/s8xnrn2yhS — Virtual walks through cities
17. https://t.co/v9XcGVXhIu — Teleport to a random spot on Earth
18. https://t.co/v2KjFxtksl — Catalog of the world's strangest places
19. https://t.co/VXMqctGQ9L — Interactive knowledge experiences
20. https://t.co/bKaGAMjC9o — Scale journey from atom to universe (Updated HTML5 link)
21. https://t.co/cS5Qiqvcb7 — Explore the solar system in 3D
22. https://t.co/ArOPduuvNd — Real sky map in your browser
23. https://t.co/2SojYezSct — NASA's astronomy picture of the day
24. https://t.co/ofFLe8FSCD — NASA's entire visual archive, free
25. https://t.co/chUiOsEgiu — Visual articles told through data
26. https://t.co/fTkQ0nf6oM — The state of the world with real data
27. https://t.co/xdN9xVrg8G — What we mistakenly think we know about the world
28. https://t.co/tBN6n8fkNu — Visualizing complex data
29. https://t.co/Yx0aGChBHI — World Bank's open data
30. https://t.co/Q0DQm9lMIu — Turkey's official statistics database
31. https://t.co/ggGbYwXWk7 — Archive of millions of books, films, and software
32. https://t.co/62yrhnzIkB — 70,000 free books whose copyrights have expired
33. https://t.co/w0AVoGIJ3H — Record of every book in the world
34. https://t.co/XMc5Ni97II — U.S. Library of Congress digital archive
35. https://t.co/nA8R2rZDKg — Europe's cultural heritage archive
36. https://t.co/ryDiJjXi0Q — America's digital library collection
37. https://t.co/lTzLH5u62I — Tour museums from home
38. https://t.co/iqEmnx3B9V — Download artworks in high resolution
39. https://t.co/oLbHeuw9of — Archive of 250,000 artworks
40. https://t.co/VOZeVrvhCK — Forgotten visual treasures of history
41. https://t.co/bRmrreJqey — Free archive of culture and education
42. https://t.co/wej39HzWrJ — Met Museum's open collection
43. https://t.co/pkf6Pe3flD — Family tree of music genres
44. https://t.co/di1Mjimco3 — Pick a country and decade to listen to that era
45. https://t.co/WPHVtByMIi — Turn Wikipedia edits into audio
46. https://t.co/itiU9B4m63 — Random knowledge well
47. https://t.co/c9Kf8gugOm — Time, sunrises, and sky events
48. https://t.co/elZYUt9UNx — Live stream of science news
49. https://t.co/dy5yfp5xBM — Free preprints of scientific papers
50. https://t.co/VBbQERnnJL — Visualize data with live code

Save this. You’ll definitely need some of these later. 🔖

Follow @Orion_Vers7x for more useful websites, AI tools & tech resources.

[Marieanne @Meytrullers17]

Stop chat gpt!!

[Ashpreet Bedi @ashpreetbedi]

https://t.co/iI7EcwAQwm

[Granite @Granite0x]

Met a guy making $1.1 million a year as an agents engineer at Google Cloud.

Asked him how he gets agents 20x better without changing the model.

He sent me the exact thing he uses himself. A repo he open-sourced 2 days ago.

You won't find anything better about harness engineering, in the open.

Cloned it and pointed my agent at it last night.

Ryan Lopopolo. Google Cloud engineer.

'harness-engineering' - anthology + field guide + agent context bundle. You reference his docs from your CLAUDE.md.

633 stars. 48 hours old. MIT.

-> https://t.co/AOykHplNNX

bookmark this before it gets lost.

[Tanvir @anjum_ai]

JOB INTERVIEW:
"Can you explain this 8-month gap in your resume?"

Most candidates say:
"I took some time off to recharge, travel, and figure out my next career steps."

THE WINNING ANSWER:

[Oliver Prompts @oliviscusAI]

🚨 BREAKING: A solo dev just fired the entire SEO content industry with one GitHub repo.. 💀

It’s called SEO machine. one API key replaces the strategist, the writer, the editor, and the $5k invoice.

It is a fully autonomous pipeline from keyword to published post. zero humans. zero retainers.

[X @TheMsterDoctor1]

someone built an entire AI RED TEAM - multiple agents that coordinate HACKING ATTACKS together, ZERO human input

PentAGI, open source, one agent does recon, another scans, another exploits, another writes the report. they talk to each other and adapt based on what they find

it ships as one docker container with nmap, metasploit, sqlmap, hydra preinstalled. the AI decides which tool to use and when. you point it at a target and walk away

a red team engagement costs $30-50k and takes weeks. this is one docker command and API tokens

[NetworkChuck @NetworkChuck]

Do you open risky PDFs, Office documents, or images you can't trust? 🛡️

Use this tool that converts potentially malicious files into a perfectly safe PDF using a secure container process.

#Cybersecurity #DangerZone #Infosec

[huihui.ai @support_huihui]

Due to the leakage of Claude Code, the following projects were generated:

https://t.co/X0mjbcgijF, Star 94.3K, Fork 88.5k
https://t.co/XfgaTYFPQJ, Star 5.7K, Fork 7.2k
https://t.co/IVNycYT1gi, Star 2.4K, Fork 930k
https://t.co/z2dADKBHXV, Star 1.8K, Fork 2.4k
https://t.co/GNKinPOI6k, Star 1.7K, Fork 2.5k

[Sarvesh Shrivastava @bloggersarvesh]

SEO consultants realizing their entire playbook just leaked:

[Charlie Hills @charliejhills]

GOODBYE to $20,000/month marketing agencies forever.

Claude just replaced an entire marketing team in 10 minutes, completely free.

Here are 10 prompts to take any business from zero brand presence to a full-blown marketing machine (save this):

[Hridoy Reh @hridoyreh]

📂 SaaS SEO
┃
┣ 📂 Keywords
┃ ┣ 📂 Keyword Research
┃ ┣ 📂 ICP Keywords
┃ ┣ 📂 Funnel Keywords
┃ ┣ 📂 Competitor Research
┃ ┗ 📂 Roadmap
┃
┣ 📂 Pages
┃ ┣ 📂 Feature Pages
┃ ┣ 📂 Use Case Pages
┃ ┣ 📂 Industry Pages
┃ ┣ 📂 Integration Pages
┃ ┣ 📂 Location Pages
┃ ┗ 📂 Persona Pages
┃
┣ 📂 Content SEO
┃ ┣ 📂 TOFU Content
┃ ┣ 📂 MOFU Content
┃ ┣ 📂 BOFU Content
┃ ┣ 📂 Blog SEO
┃ ┣ 📂 Case Studies
┃ ┣ 📂 Comparison Articles
┃ ┗ 📂 Alternatives Pages
┃
┣ 📂 Programmatic SEO
┃ ┣ 📂 Template Pages
┃ ┣ 📂 Tool Pages
┃ ┣ 📂 UGC Pages
┃ ┗ 📂 Dynamic Content
┃
┣ 📂 Technical SEO
┃ ┣ 📂 Crawling
┃ ┣ 📂 Page Speed
┃ ┣ 📂 Schema Markup
┃ ┣ 📂 Canonical Tags
┃ ┣ 📂 Hreflang
┃ ┗ 📂 Log File Analysis
┃
┣ 📂 On-page SEO
┃ ┣ 📂 Title
┃ ┣ 📂 Descriptions
┃ ┣ 📂 Header Structure
┃ ┣ 📂 Keyword Placement
┃ ┣ 📂 Internal Linking
┃ ┣ 📂 Image Optimization
┃ ┣ 📂 NLP Optimization
┃ ┗ 📂 Entity SEO
┃
┣ 📂 Topical Authority
┃ ┣ 📂 Pillar Pages
┃ ┣ 📂 Cluster Content
┃ ┣ 📂 Content Hubs
┃ ┣ 📂 Semantic SEO
┃ ┣ 📂 Entity Mapping
┃ ┗ 📂 Internal Linking
┃
┣ 📂 Link Building
┃ ┣ 📂 Guest Posting
┃ ┣ 📂 Digital PR
┃ ┣ 📂 SaaS Directories
┃ ┣ 📂 HARO
┃ ┣ 📂 Backlink Outreach
┃ ┣ 📂 Linkable Assets
┃ ┗ 📂 Partnerships
┃
┣ 📂 Product Led SEO
┃ ┣ 📂 Free Tools
┃ ┣ 📂 Templates
┃ ┣ 📂 Embed Widgets
┃ ┣ 📂 UGC Content
┃ ┗ 📂 Public Dashboards
┃
┣ 📂 Conversion SEO
┃ ┣ 📂 CTAs
┃ ┣ 📂 Free Trial
┃ ┣ 📂 Demo Booking
┃ ┣ 📂 Lead Forms
┃ ┗ 📂 CRO
┃
┣ 📂 Analytics
┃ ┣ 📂 Search Console
┃ ┣ 📂 Google Analytics
┃ ┣ 📂 Rank Tracking
┃ ┣ 📂 Traffic Growth
┃ ┣ 📂 Funnel Tracking
┃ ┗ 📂 SEO Reports
┃
┣ 📂 Scaling
┃ ┣ 📂 Content Updates
┃ ┣ 📂 Content Expansion
┃ ┣ 📂 Internal Link Scaling
┃ ┣ 📂 Topic Expansion
┃ ┗ 📂 Content Consolidation
┃
┣ 📂 Brand SEO
┃ ┣ 📂 Branded Keywords
┃ ┣ 📂 Reputation Management
┃ ┣ 📂 SERP Domination
┃ ┗ 📂 Knowledge Panel
┃
┣ 📂 Distribution
┃ ┣ 📂 Content Repurposing
┃ ┣ 📂 Social Distribution
┃ ┣ 📂 Newsletter Traffic
┃ ┗ 📂 Communities
┃
┣ 📂 International SEO
┃ ┣ 📂 Hreflang
┃ ┣ 📂 Multi Language
┃ ┣ 📂 Localized Pages
┃ ┗ 📂 Global Expansion
┃
┣ 📂 AI SEO
┣ 📂 Generative Engine Optimization
┣ 📂 LLM Visibility
┣ 📂 AI Content Scaling
┗ 📂 AI SERP Features

[Sarvesh Shrivastava @bloggersarvesh]

📂 $100k/month -> SEO + Claude
┃
┣ 📂 Google Business Profile
┃ ┣ 📂 Primary Category
┃ ┣ 📂 Secondary Categories
┃ ┣ 📂 Attributes
┃ ┣ 📂 Services Section
┃ ┣ 📂 Business Description
┃ ┗ 📂 GBP Posts
┃
┣ 📂 Trust Signals
┃ ┣ 📂 Backlinks
┃ ┣ 📂 Review Velocity
┃ ┣ 📂 Review Responses
┃ ┣ 📂 Photo Strategy
┃
┣ 📂 Content Strategy
┃ ┣ 📂 Service Area Pages
┃ ┣ 📂 Blogs
┃ ┣ 📂 Stats Pages
┃ ┣ 📂 Opinion Content
┃
┣ 📂 Backlinks
┃ ┣ 📂 Guest Posts
┃ ┣ 📂 Local Links
┃ ┣ 📂 Sponsorships
┃ ┣ 📂 Newspaper links

Every prompt to execute this with Claude is in the article below.

[Vishakha Singhal @vishisinghal_]

Most people think using Claude Code is about writing better prompts.

It’s not.

The real unlock is structuring your repository so Claude can think like an engineer.

If your repo is messy, Claude behaves like a chatbot.

If your repo is structured, Claude behaves like a developer living inside your codebase.

Your project only needs 4 things:

• the why → what the system does
• the map → where things live
• the rules → what’s allowed / forbidden
• the workflows → how work gets done

I call this:

The Anatomy of a Claude Code Project 👇

━━━━━━━━━━━━━━━

1️⃣ CLAUDE.md = Repo Memory (Keep it Short)

This file is the north star for Claude.

Not a massive document.

Just three things:

• Purpose → why the system exists
• Repo map → how the project is structured
• Rules + commands → how Claude should operate

If CLAUDE.md becomes too long, the model starts missing critical signals.

Clarity beats size.

━━━━━━━━━━━━━━━

2️⃣ .claude/skills/ = Reusable Expert Modes

Stop repeating instructions in prompts.

Turn common workflows into reusable skills.

Examples:

• code review checklist
• refactoring playbook
• debugging workflow
• release procedures

Now Claude can switch into specialized modes instantly.

Result:

More consistent outputs across sessions and teammates.

━━━━━━━━━━━━━━━

3️⃣ .claude/hooks/ = Guardrails

Models forget.

Hooks don’t.

Use hooks for things that must always happen automatically.

Examples:

• run formatters after edits
• trigger tests after core changes
• block sensitive directories (auth, billing, migrations)

Hooks turn AI workflows into reliable engineering systems.

━━━━━━━━━━━━━━━

4️⃣ docs/ = Progressive Context

Don’t overload prompts with information.

Instead, let Claude navigate your documentation.

Examples:

• architecture overview
• ADRs (engineering decisions)
• operational runbooks

Claude doesn’t need everything in memory.

It just needs to know where truth lives.

━━━━━━━━━━━━━━━

5️⃣ Local CLAUDE.md for Critical Modules

Some areas of your system have hidden complexity.

Add local context files there.

Example:

src/auth/CLAUDE.md
src/persistence/CLAUDE.md
infra/CLAUDE.md

Now Claude understands the danger zones exactly when it works in them.

This dramatically reduces mistakes.

━━━━━━━━━━━━━━━

Here’s the shift most people miss:

Prompting is temporary.

Structure is permanent.

Once your repository is designed for AI:

Claude stops acting like a chatbot...

…and starts behaving like a project-native engineer. 🚀