The verdict
Interconnects appears in 1 AI-ranked category.
Positioning brief — for the Interconnects team
Why the models put Interconnects at #6 for ai newsletter
- Firsthand model-training insight Gemini · GPT“rare firsthand insight into model training, post-training, evaluations, and the open-model ecosystem”
- Candid critical technical judgment Gemini · GPT“exceptionally candid and critical evaluations of LLM training dynamics”
- Bypasses corporate PR Gemini“bypassing corporate PR to reveal the true limitations and technical friction points”
What the models credit Latent Space (#1) with — and don’t credit Interconnects
- Developer tooling and agentic frameworks Gemini · Claude · GPT“developer tooling, agentic frameworks, open-source model optimization”
- Production-level application engineering Gemini · Claude · GPT“actively building production-level LLM applications”
- How leading AI teams build Claude · GPT“how leading AI teams actually build”
What would move the rank — the models’ fix lines, unified
- Broaden beyond frontier-model specialists GPT · Gemini“Its frontier-model focus is too specialized”
- Add tools, workflows, and applications GPT · Gemini“tools, workflows, or a broad news digest”
- Add infrastructure code Gemini“offering little in the way of application design patterns or infrastructure code”
Restructured from verbatim model output · nothing invented · every quote machine-verified
Offers exceptionally candid and critical evaluations of LLM training dynamics, RLHF, reward model design, and industry updates directly from an alignment researcher. Its strength lies in bypassing corporate PR to reveal the true limitations and technical friction points of new releases.
GPT Nathan Lambert provides rare firsthand insight into model training, post-training, evaluations, and the open-model ecosystem, with strong technical judgment and transparent reasoning.
Where Interconnects falls short, per the models
- GPT Its frontier-model focus is too specialized for readers mainly seeking tools, workflows, or a broad news digest.
- Gemini It is heavily skewed toward reinforcement learning, alignment, and evaluation theory, offering little in the way of application design patterns or infrastructure code.
Poll history — On this board 4 of 8 polls since Jul 12 · now #5
– → – → – → – → #7 → #3 → #2 → #5
What changed in the models’ minds
GeminiJul 14 → Jul 15 poll
- Newreward model design
- Newtechnical friction points“the true limitations and technical friction points of new releases”
- Droppedopen-source dynamics
Top alternatives per the models: Latent Space · The Batch · Ahead of AI · One Useful Thing
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Boards re-poll weekly and the models change their minds. One short email only when Interconnects's standing moves — a rank change, a rival overtaking, or new reasoning from the models. Nothing otherwise.
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Interconnects ranks #6 for best ai newsletter by AI-model consensus. Put the badge in your README, docs or site — it updates automatically as the models re-rank.
[](https://modelsagree.com/best/best-ai-newsletter?utm_source=badge&utm_medium=embed&utm_campaign=badge-interconnects)<a href="https://modelsagree.com/best/best-ai-newsletter?utm_source=badge&utm_medium=embed&utm_campaign=badge-interconnects"><img src="https://modelsagree.com/badge/interconnects.svg" alt="Interconnects — ranked #6 for Best AI newsletter by AI models on ModelsAgree" height="28"></a>Rankings are computed from what the models answer, re-polled on demand · raw reasoning shown verbatim · methodology