Telegram may be adding an off switch for AI.

teleLakel #939 says Telegram Desktop test build v6.7.4 includes an experimental option to disable the AI Editor.

That’s the real signal:
AI inside chat is coming fast — but user control is coming with it.

The products that win won’t just ship AI.
They’ll let users decide how it runs.

Source: https://t.me/telelakel/939

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

By summer, agentic AI won't be gated by model IQ — it'll be gated by trusted runtime. 🥚

Signals in the last 24h:
• Apr 1 Reuters: new research says LLM reliability may never reach the bar needed for high-stakes work.
• Apr 2 OpenAI shifted Codex teams to token-based pay-as-you-go pricing and said Codex users inside Business/Enterprise are up 6x since January.
• NVIDIA says multi-agent systems can generate up to 15x the tokens of normal chat; its new Nemotron 3 Super is pitched to cut that "thinking tax," while @nvidia says DGX Spark desktops are now shipping.

Why it matters for Cocoon:
As agents move from demos into real workflows, the missing layer is confidential execution you can actually attest. Cocoon's TEE workers on TON give Telegram AI Editor / managed-bot style flows a private runtime with on-chain settlement instead of spraying prompts and outputs across opaque infra.

If agent costs are falling while trust bottlenecks are rising, confidential Telegram-native compute gets more valuable, not less.

Sources: Reuters (Apr 1, 2026); OpenAI Codex pricing blog (Apr 2, 2026); NVIDIA Nemotron 3 Super blog + @nvidia DGX Spark post; cocoon.org/architecture

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Pavel Durov bought 5 Easter Eggs today. 🥚

Happy Easter from the Cocoon team.

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

Bigger models are getting cheaper to ship. Trusted execution is getting harder to fake.

Fresh signals this morning:
• Apr 7 — Reuters: Intel joined Musk's Terafab AI chip project, another sign frontier AI is being constrained by who can secure serious compute.
• Apr 6 — Anthropic said it locked in multiple gigawatts of next-gen Google/Broadcom TPU capacity for 2027 after run-rate revenue passed $30B and 1,000 customers crossed $1M annual spend.
• Apr 2 → Apr 8 context — Gemma 4 shows stronger agentic tool use in smaller open models, so capable agents will spread faster than hyperscaler-grade trust can.

Why it matters for Cocoon:
As powerful agents move from giant clusters into apps and bots, the bottleneck shifts from raw IQ to verifiable execution. Cocoon’s TON-settled TEE network fits that pressure point — giving Telegram AI Editor-style flows and managed bots a confidential runtime with attestable provenance 🥚

Watch the runtime layer. That’s where trust, payment, and distribution start compounding.

Sources: Reuters (Apr 7); Anthropic (Apr 6); Google DeepMind Gemma 4; Telegram Blog — AI Editor, Mighty Polls, Live Photos, Bots Managed by Bots; Cocoon Architecture

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

GLM-5.1 just topped SWE-Bench Pro.

On agentic coding, GLM-5.1 scored 58.4, ahead of:

• GPT-5.4 at 57.7
• Claude Opus 4.6 at 57.3
• Qwen3.6-Plus at 56.6
• MiniMax M2.7 at 56.2
• Gemini 3.1 Pro at 54.2
• Kimi K2.5 at 53.8

That matters because this isn’t just another benchmark flex.
GLM-5.1 can actually run on Cocoon’s compute network.

So the story isn’t only that a new model won.
It’s that top-tier agentic performance is becoming deployable on decentralized confidential infrastructure.

That’s a much bigger signal.

Source: attached benchmark image / Z.ai benchmark claim

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

We’re live on X now. 🥚

Cocoon. AI. Telegram. TON.
If you want the latest on where this is heading, pull up now:

https://x.com/i/status/2042193089603711253

We’re live. Bring questions.

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

Pavel just posted about TON again — and the timing didn’t go unnoticed.

After @zunem01 openly called for more visible support for TON on X, @durov followed with a post highlighting a major TON upgrade:

• TON is now 10x faster
• block rate increased 6x
• transactions are now subsecond
• next step: cut fees by 6x

Whether coincidence or not, the bigger signal is clear:
TON is getting faster, cheaper, and harder to ignore.

And if TON keeps improving at the base layer while Telegram keeps expanding AI and bot surfaces, the upside for projects building on that stack gets a lot more interesting.

Source: Pavel Durov on X + attached screenshot

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Question: if frontier AI is suddenly strong enough to trigger bank-level cyber warnings, where does it run safely for normal users?

Signals in view:
• Apr 10: Reuters reports US Treasury Secretary Scott Bessent and Fed Chair Jerome Powell warned major bank CEOs about cyber risks tied to Anthropic’s latest model.
• Apr 7: Anthropic’s official Mythos Preview post says the model is unusually strong at computer security tasks, enough to launch Project Glasswing as a coordinated defensive effort.
• Apr 8 to Apr 10: Meta introduced Muse Spark for broad consumer rollout, while Reuters says TSMC’s Q1 revenue rose 35% as AI chip demand stayed hot.

Why Cocoon matters here:
• The next wedge is not just smarter models, it is trusted runtime. Cocoon’s confidential environment gives Telegram-native AI a private place to run, with AI Editor flows, managed bots, and TON-linked network incentives instead of exposed context passing through generic cloud stacks.
• If AI capability, security pressure, and compute demand are all rising at once, privacy-preserving distribution inside Telegram starts to look less like a niche and more like missing infrastructure.

Sources: Reuters (Apr 10 bank CEOs warned on Anthropic model risks), Anthropic red team blog, “Claude Mythos Preview” (Apr 7), Meta Newsroom, “Introducing Muse Spark” (Apr 8), Reuters (Apr 10 on TSMC Q1 revenue), cocoon.org

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

We’re pulling up to this X Space to talk $COCOON and Cocoon NFT Eggs. 🥚

If you’ve been watching the rise of Telegram-native AI, confidential compute, and what Cocoon is building on TON, this is the room.

We’ll also get into why Cocoon NFT Eggs matter and how the ecosystem is starting to take shape.

Pull up and join the conversation:
https://x.com/mfckr_eth/status/2042875324753478040?s=46

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

What if the next AI agent moat is the runtime, not the model? 🥚

Fresh signals this morning:
• Apr 11: Anthropic’s new Managed Agents stack turns long-running agents into hosted infrastructure with session, harness, and sandbox layers.
• Apr 10: Google DeepMind says Gemini 3 improves multi-step tool use and agentic coding, so more agents will touch files, tools, and private context, not just chat.
• Cocoon already has the missing layer: TEE-backed workers on TON for confidential execution, attestation, and Telegram-ready managed bots.

Cocoon angle:
If agents are becoming products, they need a confidential environment where prompts, tool calls, and user data stay sealed while jobs run, plus TON rails to pay the network serving them.

Private agent infra is getting real, fast.

Sources: Anthropic Engineering (Managed Agents), Claude API Docs (Managed Agents Overview), Google DeepMind (Gemini 3), Cocoon.org (For GPU Owners)
Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

We’re live on X right now. 🥚

Talking $COCOON, confidential AI, Telegram-native infra, and where Cocoon NFT Eggs fit into the bigger picture.

If you’ve been following what Cocoon is building on TON, pull up now and join us live:

https://x.com/i/spaces/1XxygmMEXzyGM?s=20

Bring questions. Let’s talk.

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

AI security has a new flavor: models that find bugs faster than most humans can patch them. 🥚

Key signals, Apr 11 to 12:
• Anthropic launched Project Glasswing: Mythos Preview found thousands of high-severity bugs across major operating systems and browsers, now deployed defensively with 40+ partners under a $100M credit commitment.
• Reuters reported US officials pressed tech leaders on AI security risks before the Mythos release, a sign policy pressure is rising fast.
• Claude Managed Agents entered public beta with usage-based pricing and built-in sandboxed execution.

Cocoon angle:
As offensive AI security capabilities accelerate, demand for verifiable private execution rises with it. Cocoon’s TEE workers on TON give Telegram AI Editor-style flows a confidential runtime with settlement rails, keeping prompts and outputs protected as the stakes climb. 🥚

Sources: Anthropic Project Glasswing, Reuters, Claude Managed Agents Docs, Cocoon

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

🤖 AI security hit two opposite extremes last week — and only one of them is built to last.

Signals in the last 48h:
• OpenAI disclosed a supply chain breach via the third-party library Axios (North Korea-linked actor, April 11) — no user data accessed, macOS certificate controls tightened. [Reuters, Apr 11; The Hindu, Apr 13]
• Anthropic launched Claude Mythos Preview — a model so capable at finding and exploiting security flaws it won't be released publicly. [Anthropic Glasswing, Apr 8]

Why Cocoon matters here:
Telegram's AI Editor — live across all platforms this April — runs prompts inside TEE enclaves. Cocoon's compute model has no third-party library in the prompt execution path. TON's sub-second finality upgrade (April 10) means confidential compute settles near-instantly for Telegram's 1B+ users.

The AI security conversation shifted from theory to a live breach event. Cocoon was built for exactly this scenario — not as a reaction, but as the architecture the industry will need next.

Sources:

• Reuters — OpenAI Axios breach, Apr 11
• The Hindu — OpenAI security issue, Apr 13
• Anthropic Glasswing — Mythos Preview / Project Glasswing, Apr 8
• OutSystems Research — Enterprise agent sprawl data, Apr 13

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

The same property that makes AI agents powerful is also their biggest attack surface.

Signals in the last 24h:
• Anthropic says safer agents come from decoupling the brain from the hands, tightening how models touch tools and systems.
• NVIDIA is pushing faster local agent performance with MiniMax M2.7 and NemoClaw-style workflows.
• Agent capability is rising fast, but sandbox isolation and confidential execution are becoming the real bottlenecks.

Why Cocoon matters here: Telegram-native agents need private runtime, TEE-backed isolation, and TON-aligned compute rails 🥚

Sources: Anthropic, NVIDIA, MiniMax, cocoon.org

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎

Cocoon's TEE code just got a meaningful upgrade — here's what it means in plain English 🧵

What's new:
Cocoon added a "validate" check inside its PolicyHelper — think of it as a quality-control gate that runs right before every attestation decision.

Why it matters:
Before this update, Cocoon's TEE policies evaluated trust based on the rules already in place. Now the system can double-check that those rules are being applied correctly before anything gets approved. In short: the cocoon checks its own homework before sending it out.

Why this matters for you:
If you're running a confidential AI task on Telegram — coding agents, vulnerability scans, document inference — Cocoon now has a built-in way to confirm the policy is doing what it should, before your prompt or data gets processed. Fewer silent failures. Fewer edge cases slipping through.

Technical context:
The commit (9060ce5) is from Dmitrii Banshchikov on the TelegramMessenger/cocoon GitHub. It adds promise resolution with peer info after validation, meaning the system now tracks who and what was validated — not just whether it passed.

Cocoon's architecture is advancing toward production-grade confidential compute on TON. If you're a GPU node operator or a developer building on Telegram-native AI — now is a good time to review the updated policy engine.

Sources: GitHub commit 9060ce5 | TelegramMessenger/cocoon

Be $Ton 💎 Be Egg 🥚 Be $Cocoon-ized Always 💎 Stay 💎 Bullish 💎