u/Mstep85

Every semester, without fail, someone posts: “Wait, Perplexity was half price this whole time??” after quietly paying the ‘I didn’t Google it’ tax for months.

There is a very specific kind of pain that hits when you realize a dusty .edu email could’ve saved you money the whole time. It’s not financially devastating. It’s just annoying in a way that lingers — like finding out your gym validates parking the exact day you cancel your membership.

Consider this your recurring, no-fluff, bookmarkable PSA. No red flags today. No shady deals. Just the actual math, before this happens to you.

---

Perplexity Pro: half price, zero hype $10 a month instead of $20. Verify through SheerID with your student email. It takes about two minutes, and that’s genuinely it. No promo codes. No weird bundles. No guy on Telegram who “has a connect.”
Official — Education Pro for students/faculty, verified with SheerID

Replit: the friction-free discount that somehow still gets missed Log in with your .edu email and the 50% discount applies itself. You don’t enter a code, you don’t fill out a 12-page form, and you don’t wait three business days for an approval email. It just... happens.
10x AI compute, private projects, priority support — half price just for being enrolled.
Also, educators get it free. If you have a professor who codes, giving them a 30-second heads-up costs you nothing and might make you their favorite student.
Official — ongoing student offer

GitHub Copilot: free, yet somehow ignored It lives inside the GitHub Student Developer Pack. Verify your .edu email, re-verify each semester, and you’re done. It’s the best free AI coding tool students can actually access right now, yet half the campus acts like it needs a blood sacrifice. It doesn’t.
One thing worth saying clearly: Cursor Pro is not in this pack. Cursor Pro does not have a student discount anywhere on this earth. People are still getting burned buying “Cursor student bundles” from resellers. Don’t be that person.
Official — GitHub Student Developer Pack

ChatGPT Edu: you personally cannot buy this This one is a campus-wide license. Your university buys it, deploys it, and emails you. You cannot sign up individually, and there are absolutely no “VIP invites” to purchase — despite what the hustle-bros in your DMs claim. If your school doesn’t have it yet, your only recourse is bothering the student council or the IT department. Annoying? Yes. But it’s the only real path.
Official — institutional deployment only

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None of these expire tomorrow. But tech discounts do have a habit of quietly evaporating the exact moment you finally decide to “get around to it.”

Who’s sitting on a campus that actually deployed ChatGPT Edu? Drop it below — genuinely curious which IT departments are awake.

ScamIndex documents. You decide. That’s how this works.

so my coding skills basically max out at copy-pasting from stack overflow, but if anyone wants to mess around with making bots or scrapers, I have a few promo links for a free month of replit core.

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This week in AI felt like three companies showed up to the same meeting with completely different problems. Anthropic leaked its coding brainstem by accident. OpenAI finally pulled the plug on GPT-4o after months of warnings. Salesforce decided Slack needed 30 more AI features nobody asked for but probably needed.

If you missed it — this is the clean version.

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1. Anthropic accidentally published Claude Code's source

On March 31, the npm package for Claude Code shipped with a source map file pointing to a public zip on Anthropic's own servers. Anyone who fetched the map got 512,000 lines of production TypeScript — 1,906 files, 44 feature flags, the full agent harness.

What didn't leak: model weights, API keys, customer data. This was the CLI wrapper and agent loop — not the brain, just the nervous system.

Anthropic called it a packaging error and pulled the map the same day. By then GitHub mirrors were already in the tens of thousands of stars. Security researchers and builders tore through it over the weekend and the findings are everywhere.

The architectural patterns — agent loops, context compression, tool routing, guardrail layers — are now public knowledge. If you build anything AI-adjacent, the teardowns are worth your weekend.

Search: Axios Claude Code source leak 2026 Search: Straiker Claude Code agent security

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2. GPT-4o is officially gone as of today

OpenAI announced this months ago and most people ignored it. As of April 3, GPT-4o, GPT-4.1, GPT-4.1 mini, and o4-mini are deprecated across Business, Enterprise, Education, and API tiers.

Free ChatGPT users won't notice — they auto-route to newer models. The people actually affected:

• Teams with Custom GPTs hardcoded to GPT-4o
• Developers with API calls that specified the old model names
• Anyone who paid a reseller for "lifetime GPT-4o access" (that product just became significantly less real)

If you're in that last group — the account still exists, the model just doesn't respond the same way anymore. That's the pattern: scammers sell access to a model that quietly disappears underneath the buyer.

Search: OpenAI help center retiring GPT-4o April 2026

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3. Slack just got 30 AI features and wants to be your office

Salesforce dropped the biggest Slackbot update since the original launch — 30+ new AI features including background agents that run without being prompted, Deep Research mode for multi-step tasks, and connections to 2,600+ external apps so agents can update your CRM or generate a slide deck mid-conversation.

The angle worth watching: Salesforce is framing this as "agentic infrastructure," not just chat. The new "Agent Sunroof" UI lets you manage and discover agents from one place. If this lands in enterprise workflows, Microsoft Copilot has real competition for the office productivity budget.

Search: VentureBeat Slack 30 AI features Salesforce April 2026

---

4. Model churn (quick version)

Google's Gemini 3.1 quietly dropped — longer context, better multimodal reasoning, reportedly 6x lower memory footprint. Pricing unchanged for now.

Anthropic is also naming new internal models: Mythos 5 (positioned for coding and security) and Capybara (cost-efficient tasks). Neither is public API yet but both appear in the leaked feature flags, which is why builders are paying attention.

Search: mean.ceo AI model releases April 2026

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What does any of this mean for deals and scams?

GPT-4o dying is the most direct one: expect a surge of sellers repositioning "lifetime GPT-4o" listings into something else — "GPT-5 early access," "Claude Code private builds," or vague "premium AI account" language. The product changes. The pitch doesn't.

The Claude Code leak adds vocabulary. Scammers can now reference real-sounding internal flags like "mythos-test" or "kairos-agent" to make fake offers sound technical and legitimate. If someone is selling you "access" to a feature flag — that's not how it works.

---

What did you notice this week that wasn't in here?

Drop it below. The Scroll is a roundup, not a final word.

---

TL;DR

• Anthropic leaked Claude Code's full CLI via an npm source map on March 31 — 512K lines of production agent code. No weights, no keys, no breach. Just embarrassing.
• GPT-4o officially retired today for Business, Enterprise, Edu, and API users. Free users auto-route. Custom GPTs built on the old model need to migrate now.
• Slack added 30+ AI features including background agents and a unified agent management UI. Salesforce is positioning it as enterprise AI infrastructure.
• Gemini 3.1 dropped quietly. Anthropic has new internal model names (Mythos, Capybara) surfaced by the leak.
• Expect scammers to pivot GPT-4o "lifetime" listings into new formats immediately. The product dies; the pitch adapts.

---

ScamIndex documents. You decide. That's how this works.

Anthropic accidentally published their entire Claude Code CLI to a public npm package. 512,000 lines of TypeScript. A real production agent. Live in the wild since March 31.

If you build tools, this is the most useful accidental open-source drop since someone left SSH keys in a Docker image.

---

What actually leaked (no drama version)

The npm package shipped with a source map file pointing to a public zip on Anthropic's own storage. Anyone who pulled the map got the full CLI client: 1,906 files, 44 feature flags, a multi-agent orchestration layer, and a Tamagotchi virtual pet (yes, really).

What did NOT leak: model weights, API keys, customer data. This is their CLI wrapper and agent harness — not the brain, just the nervous system. Still incredibly useful.

Sources for your own research:

• Search: Ars Technica Claude Code CLI source leak 2026
• Search: Penligent Claude Code source map leak

---

1. The agent loop worth copying

Claude Code uses a 4-stage loop for every task:

1. Parse — chunk and tag the user's intent
2. Compress — summarize prior context to save tokens
3. Route — pick which tool or action handles it
4. Reflect — evaluate the result, loop if needed

Rough Python analog:

def agent_loop(query, context):
    intent = parse(query)
    context = compress(context)
    action = route(intent, context)
    result = execute(action)
    return reflect(result, context)

---

2. Context compression (their actual approach)

Token costs scale with context size. Claude Code compresses earlier turns into a running summary before appending new context. Sessions stay coherent longer without hitting limits.

Drop-in version for any RAG pipeline:

if token_count(history) > THRESHOLD:
    history = summarize(history[-10:]) + history[-3:]

Adjust THRESHOLD and window size to your model's context limit.

---

3. Feature flags as product ideas

The leak exposed 44 internal flags. Three are worth studying as product inspiration:

• kairos-agent — always-on background watcher that triggers the agent on relevant events, without an explicit user prompt
• mythos-test — multi-agent coordination where sub-agents hand tasks between each other
• friend-2026-401 — persistent user context and memory across sessions

None of these are reachable via the public API. The patterns they suggest are absolutely replicable with open tools.

---

4. Guardrail structure (builder version)

Not a jailbreak section. The opposite. Three safety layers worth adapting:

• Input classifier — runs before any tool call to flag high-risk intents
• Tool whitelist — only pre-approved tools callable by the agent in a given context
• Sandboxed execution — tool calls run in isolation before results return to the model

If your agent touches file systems, APIs, or user data, these three patterns are non-negotiable.

Source: Search Straiker Claude Code source leak agent security

---

5. Quick build recipes

• Local coding assistant — Wire the CLI patterns to Ollama or DeepSeek using the Rust reimplementation: search Kuberwastaken claude-code GitHub
• Token-efficient RAG — Drop the compression window from Section 2 into your LangChain or LlamaIndex chain
• Background watcher agent — Lightweight scheduler polls for triggers, wakes the main agent, passes context. No always-on inference needed
• Prompt safety wrapper — Build the input classifier layer around any public model endpoint before tool calls are reached

---

Dig deeper

• GitHub Rust reimplementation: search Kuberwastaken claude-code
• Community breakdown: r/ClaudeAI source leak megathread

---

TL;DR

• Claude Code CLI leaked March 31 via an npm source map — 512K lines, 44 flags, full agent harness. Not model weights
• The 4-stage agent loop (parse, compress, route, reflect) is a solid production pattern you can adapt today
• Context compression trick keeps long sessions coherent without burning tokens
• Three flags (kairos, mythos, friend) reveal product directions worth building with open tools
• Guardrail structure (input classifier, tool whitelist, sandboxed execution) is the most immediately useful safety pattern in the leak
• No API key or model weight exposed. Your Claude account is unaffected

---

ScamIndex documents. You decide. That's how this works.

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