🤖 AI Terminal

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Model benchmarks, AI infra moves, and real-world deployment intelligence — extracted from 8 channels, not press releases.

📰 8 AI newsletters𝕏 @karpathy @emollick +18🎙 4 AI podcasts

🏆 Benchmark Leaderboard

Top models · Mar 26
Frontier model intelligence scores from tracked newsletters. Source: The Neuron + TLDR IT + Bay Area Times +5 more
ModelCompanyScoreBest ForSource
Claude Mythos PreviewAnthropic95vulnerability detection, exploit generation📰 TLDR
Gemini 3.1 ProGoogle93general AI tasks📰 Bay Area Times
Claude 4.6Anthropic92coding, long-context analysis📰 TLDR AI
Kimi-K2.6Moonshot AI92agent swarm orchestration, coding📰 AlphaSignal
Claude Opus 4.5+Anthropic92agentic deployment, non-technical generalist use cases📰 SaaStr
TalkieDavid Duvenaud & Alec Radfordhistorical text analysis, pre-1931 domain reasoning📰 The Neuron
o4-miniOpenAIcode generation📰 TLDR IT
Kimi K2.5Moonshot AI (Kimi)coding, AI agent base models📰 Bay Area Times
🏗 AI Infrastructure Moves
Ethereum
blockchain infrastructure for persistent onchain games
12×
📰 12
x402
Creating agent-ready API toolkits with standardized access a…
9×
📰 9
AWS
Cloud infrastructure
9×
📰 9
MiniMax M2.7
core agent tasks like fill operations, tool use, and instruc…
3×
📰 3
Google AI Studio
AI model development and access
3×
📰 3
DeepSeek
AI language model for on-device use
2×
📰 2
🧪 Real-World AI Deployment
What founders are actually experiencing — merged from 4+ leaders across newsletters and X

World Markets on MegaETH represents the long-awaited gold standard of going bankless — a feature-complete exchange with an entirely onchain codebase and no servers.

David Hoffman📰

Zyfai's report that its agents successfully avoided KelpDAO losses should be taken with a grain of salt as it is the company's own account.

David Christopher📰

Agents' most plausible near-term value in DeFi is defensive monitoring and capital protection, not yield optimization or novel strategies.

David Christopher📰

Many B2B software companies still have moats, but moats alone are no longer sufficient for long-term survival as AI agents can replicate features rapidly and customer expectations are evolving faster than incumbents can adapt.

SaaStr📰

🛠 AI Tool Adoption Tracker

ToolMentionsCategoryUse Case
Ethereum12×Infrastructureblockchain infrastructure for persistent onchain games
x4029×InfrastructureCreating agent-ready API toolkits with standardized access a…
AWS9×InfrastructureCloud infrastructure
MiniMax M2.73×AIcore agent tasks like fill operations, tool use, and instruc…
Google AI Studio3×AIAI model development and access
DeepSeek2×AIAI language model for on-device use
ENS2×Infrastructuredomain name configuration in atomic transactions
OpenAI Codex2×AICode generation

⚠️ Model Warnings

TalkieDavid Duvenaud & Alec Radford

trained only on pre-1931 text, not suitable for modern knowledge tasks

o4-miniOpenAI

48% hallucination rate in generated code — nearly half of output snippets may contain vulnerabilities

Kimi K2.5Moonshot AI (Kimi)

Cursor did not disclose it as Composer 2's base model, raising transparency concerns

Gemma 4 E2BGoogle

requires WebGPU-compatible GPU in Chrome

model must download on first use

Qwen3 35B MoEAlibaba / community

distilled from Claude Opus — derivative model

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