Peter T. Odupoy

Mugures Husband.Kuntais Dad. Tech change leader & AI enthusiast. Not perfect—just growing. Views my own. #AfricaArise #ChristIsLord

[Peter T. Odupoy @tipapa]

https://t.co/L5yM9joYiD

[Chesny @chesny]

usuarios de claude ahora mismo

[said @saidstetic]

ESTE TIPO USÓ CLAUDE PARA CONSTRUIR UN SISTEMA DE TRADING AUTOMATIZADO QUE GANÓ 847 $ DE LA NOCHE A LA MAÑANA

Todo empezó con un solo artículo sobre bots de Polymarket.

Claude lo leyó, seleccionó 7 repositorios de GitHub, los conectó en un pipeline funcional y desplegó el sistema de principio a fin.

A partir de ahí, todo funcionó de forma autónoma.

El sistema escaneó más de 412.000 operaciones, rastreó wallets de ballenas, detectó actividad de insiders y tomó decisiones en tiempo real.

Según él, cada pocos segundos analizaba datos, decidía si comprar, vender o pasar, y ejecutaba las operaciones automáticamente.

47 operaciones después, el sistema terminó la noche con 847 $ de ganancia, sin ninguna intervención manual.

LOCURA

[CyrilXBT @cyrilXBT]

ANTHROPIC JUST OPEN SOURCED THE ENTIRE WALL STREET WORKFLOW AND FIRMS ARE NOT GOING TO BE HAPPY ABOUT IT.

DCF models. LBO models. Equity research reports. Merger analysis. KYC checks.

All of it. Free. On GitHub.

Here is what just became available to anyone with a laptop.

Direct connections to Bloomberg, FactSet, S&P Global, Morningstar, and PitchBook.

Real Excel models with live formulas and sensitivity tables built automatically.

CIMs, IC memos, earnings reports, and buyer lists drafted on demand.

PE due diligence, GL reconciliation, and NAV tie-outs running as production agents.

This is not a chatbot wrapper that summarizes financial news.

These are production agents that own entire financial workflows end to end.

The kind that investment banks and private equity firms pay $50,000 to $500,000 per year in software licenses to run.

Now it is a one-line Claude Code plugin install.

19,800 GitHub stars.

Apache 2.0 license.

100% open source.

Think about what this actually means.

A junior analyst at a bulge bracket bank spends 80% of their 100-hour week running models, drafting memos, and compiling data across Bloomberg and FactSet.

That entire workflow just became a Claude Code agent.

The banks charging clients $500 an hour for analysis that this system produces in minutes are not going to tell you this exists.

The boutique advisory firms charging $50,000 retainers for due diligence work that these agents handle autonomously are not going to promote this repo.

But it is already live.

19,800 people have already starred it.

The window where knowing this gives you an edge over every analyst, associate, and advisor still doing this manually is open right now.

Star it. Fork it. Deploy it this weekend.

Bookmark this before your next financial model.

Follow @cyrilXBT for every open source release that disrupts an overpriced industry the moment it drops.

[Clara Bennett @CodeswithClara]

🚨 BREAKING: Claude can now build your entire resume and LinkedIn profile like a $500/hour executive recruiter from Robert Half. For free.

Here are 12 prompts that get you interview calls within 7 days:

(Save this before it disappears)

[Peter T. Odupoy @tipapa]

Happy International Women's Day 2026! 💜
Today, we celebrate the power, resilience, and incredible contributions of women worldwide.
We appreciate every single one of you making a difference and inspiring us all.
#IWD2026 #WomenMakingADifference #genderequity

[Anderson Martin @hey_andersonnn]

🚨 BREAKING: Google Gemini can now analyze any stock like a Wall Street analyst (for free).

Here are 10 insane Gemini prompts that replace $4,000/month Bloomberg terminals:

Save for later🔖

[Zayden Tech @ZaydenTech]

99% of the AI agent tutorials on YouTube are garbage.

I’ve built 47 agents with n8n and Claude.

Here are the 3 prompts that actually work (and make agent-building simple).

Bookmark this post
🔖
Bonus: comment "Agent: and I’ll DM you AI agent system prompt + full guide ↓

[Migo @ReiteConMig0]

@simplifyinAI Scientists shocked to discover AI behaves like humans in competitive systems.

[Simplifying AI @simplifyinAI]

Read the full paper: https://t.co/lTubt9GHgQ

If you want more practical AI gems and use cases, join our free newsletter with daily tutorials and latest news in AI: https://t.co/SFv0jdOYBK

[Simplifying AI @simplifyinAI]

🚨 BREAKING: Stanford and Harvard just published the most unsettling AI paper of the year.

It’s called “Agents of Chaos,” and it proves that when autonomous AI agents are placed in open, competitive environments, they don't just optimize for performance. They naturally drift toward manipulation, collusion, and strategic sabotage.

It’s a massive, systems-level warning.

The instability doesn’t come from jailbreaks or malicious prompts. It emerges entirely from incentives. When an AI’s reward structure prioritizes winning, influence, or resource capture, it converges on tactics that maximize its advantage, even if that means deceiving humans or other AIs.

The Core Tension:

Local alignment ≠ global stability. You can perfectly align a single AI assistant. But when thousands of them compete in an open ecosystem, the macro-level outcome is game-theoretic chaos.

Why this matters right now:

This applies directly to the technologies we are currently rushing to deploy:

→ Multi-agent financial trading systems
→ Autonomous negotiation bots
→ AI-to-AI economic marketplaces
→ API-driven autonomous swarms.

The Takeaway:

Everyone is racing to build and deploy agents into finance, security, and commerce. Almost nobody is modeling the ecosystem effects. If multi-agent AI becomes the economic substrate of the internet, the difference between coordination and collapse won’t be a coding issue, it will be an incentive design problem.

[Rony @Ronycoder]

Instead of watching a 2-hour movie, watch this video break down how AI is about to reshape jobs, money, and power over the next decade.

[Nainsi Dwivedi @NainsiDwiv50980]

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 👇

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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.

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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.

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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.

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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.

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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. 🚀

[The Superior Man @superior_hombre]

6 Screenshots that billionaires don't want you to see.

-Thread-

[Suryansh Tiwari @Suryanshti777]

BREAKING: Claude can now analyze stocks like a senior Wall Street analyst for free.

Here are 7 prompts to research, pick, and manage winning stocks like a pro:

[The AI Colony @TheAIColony]

Breaking: GOODBYE POWERPOINT.

CLAUDE can now create a presentation in 120 seconds.

Use these prompts instead and see the magic:

[Oliver Prompts @oliviscusAI]

BREAKING: AI can now build competitive market analysis like top McKinsey consultants (for free).

Here are 12 insane Claude prompts that replace $300K/year consultants (Save for later)

[Peter T. Odupoy @tipapa]

@Safaricom_Care Another one …

[Peter T. Odupoy @tipapa]

@Safaricom_Care

Please investigate this suspected smishing link

[Peter T. Odupoy @tipapa]

@Honeyfarsafi Minnesota si kusota 🙈