Latest AI Articles

Mar 2

AI+ Renaissance Conference in San Francisco

The headline AI event of the year bringing together 2,000 of the leading founders, researchers, investors and operators, one day before Nvidia's GTC

There are moments in technology when the direction of an entire industry is decided.

AI+ ∙ 12 LIKES

EileenDQ

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Mar 6

The timing between GDC and GTC is strategically sharp—enterprise buyers are watching consumer AI patterns more closely than ever. I've been tracking similar convergence dynamics over at Beyond the Seat, especially how agentic systems are forcing CIOs to rethink procurement cycles. Curious which stealth launches will actually have enterprise hooks versus pure developer tooling.

Creators' AI

Mar 13

Claude Marketplace & Pentagon AI Drama | Weekly Digest

The Block "AI washing" scandal, NASA's Claude-assisted Mars drive, and tools of the week

Hey! Welcome to the latest Creators’ AI Edition.

Daniil Andreev ∙ 4 LIKES

AgenticLoops AI

Mar 12

Disassembling AI Agents - Part 2: Claude Code

Inside the prompts, tools, and architecture that reveal how Claude Code works

In Part 1, we disassembled GitHub Copilot: 65 tools, three modes, and a prompt architecture designed for a polished IDE experience.

Alex ∙ 14 LIKES ∙ 1 RESTACKS

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The useful shift here is that the shell is starting to matter almost as much as the model. Once an assistant can edit files, choose tools, manage context windows, and recover from failures, the product stops being just "Claude, but in a terminal" and becomes a control-plane design question: what gets loaded, what gets permissioned, and what persists between turns. That's why these coding agents feel meaningfully different even when model capability is converging.

AgenticLoops AI

Mar 5

Disassembling AI Agents - Part 1: GitHub Copilot

Inside the prompts, tools, and architecture of the VS Code's GitHub Copilot

In the previous post, we explored the key patterns behind AI agents — the ReAct loop, planning, and how a few tools turn a language model into an autonomous problem-solver.

Alex ∙ 4 LIKES ∙ 1 RESTACKS

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This is brilliant. The 97% input tokens stat for the agent session is the kind of number that changes how you think about token economics. Most of the cost is the model reading, not writing.

The three-mode split is smart too. Ask at 654 tokens, Plan at 8.5K, Agent at 16.7K. Copilot is basically buying tool surface area with token budget. Every tool schema costs tokens whether it gets used or not.

This connects to something I've been looking at with the Google Workspace CLI. It took the opposite approach to tool surface management. Instead of shipping all tools upfront, it builds its commands dynamically from Google's Discovery Documents at runtime. The token cost shifts from "describe all tools at prompt time" to "discover what's available when you need it". Wrote up how the architecture works here https://reading.sh/google-workspace-finally-has-a-cli-and-its-built-for-agents-5f5fe87d0425

Are you planning to do Claude Code next in the series? I'd be very curious to see how its tool-use pattern compares to Copilot's.

AI Space

Mar 5

Distribution Is the Only AI Moat Left

For three years we obsessed over intelligence.

AI Space

Epoch AI

Feb 26

The least understood driver of AI progress

An opinionated guide to “algorithmic progress” and why it matters

This post is part of Epoch AI’s Gradient Updates newsletter, which shares more opinionated or informal takes on big questions in AI progress. These posts solely represent the views of the authors, and do not necessarily reflect the views of Epoch AI as a whole.

Anson Ho ∙ 45 LIKES ∙ 5 RESTACKS

Herbie Bradley

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Feb 26

Nice analysis! I do think section IV underestimates the dynamics from data, and I think the data improvements model could benefit from some application of diminishing returns. For example, most researchers estimate we're years past the point of severe diminishing returns from pretraining on public data. Labs have moved more towards synthetic data, which is decent but is dominated by domains in which it's easy to verify (software), and private data (requires paying companies).

At every point in the last 5y at which it seemed like there might be a slowdown, we found a new mini-paradigm to continue (e.g., pretraining -> RLHF data -> RL env data -> inference time compute). But many of these are approaching diminishing returns. It's useful to bear in mind that at the point where we get automated AI R&D, we should expect labs to have spent tens of billions on custom RL environments for every aspect of knowledge work, and potentially more on pretraining data cumulatively. That's just a huge amount of effort, and this is one of the main reasons why I don't expect a software-only singularity.

Daniel Kokotajlo

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Feb 26

Nit: “Will compute be a major bottleneck to the software intelligence explosion?” should read "will *training* compute be a major bottleneck..."

Because obviously experiment compute will be; AI 2027 and the AI Futures Model are built around that assumption.

I think you are clear on this elsewhere in the piece, which is why this is just a nitpick of a typo.

AI Search

Mar 8

CUDA Agent, GPT 5.4, LTX 2.3, OmniXtreme, Kiwi Edit, Helios: AI NEWS

Welcome to the AI Search newsletter. Here are the top highlights in AI this week.

LTX-2.3 is an open-source video generation model with sharper details and better prompt following. It features a rebuilt training pipeline, 4x larger text understanding capacity, and native portrait video support up to 1080×1920. The model offers two modes: Fast for quick iteration and Pro for maximum quality, both supporting up to 20 seconds of video.

AI Search ∙ 2 RESTACKS

Claudia + AI

Mar 2

Claude Cowork Starter Guide + 30 examples

The AI That Does the Work

I am finalizing the intro for this newsletter while up in the air on my way to Asia. It has been a trip that has been planned for a long time, got cancelled twice, got shortened because I only have so many vacation days now, and even at the airport on Sunday morning, it almost didn't happen. A transit visa to China, that allows Americans to stay in the …

Claudia + AI ∙ 69 LIKES ∙ 7 RESTACKS

Opinion AI

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Really useful guide. You made Claude Cowork feel practical, not confusing, and the 30 examples help people see where it actually saves time.

Anuja Gupta

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Very comprehensive guide. Claude Skills are so helpful particularly if you are looking to scale. Thank you for sharing this great resource.

The AI Dispatch

Mar 10

AI Hits Its Operational Footing

Inside the AI Transformation of Parts, People & Processes

Hi, I'm Lily. I live in the world of distribution, where for years, AI was the knowing part (pilots, proofs of concept, strategy slides). Everyone understood the potential. Few knew how to act on it. Now the proof stories are piling up. NAPA just committed to 100+ robots after a pilot that worked. DSG reported earnings and named specific AI tools runnin…

InstaLILY AI ∙ 27 LIKES

Epoch AI

Mar 2

The Epoch Brief - February 2026

Biological AI models, "economic value" benchmarks, robot autonomy, hyperscaler capex, Anthropic revenue, and how close is AI to taking my job

Hi! Welcome to this edition of the Epoch AI Brief!

Epoch AI ∙ 11 LIKES

AI Frontiers

Mar 2

How AI Could Benefit Workers, Even If It Displaces Most Jobs

AI is already taking jobs, but that is only one facet of its complex economic effects. Price dynamics and bottlenecks indicate that automation could be good news for workers — but only if it vastly ou

Benjamin Jones — March 2, 2026

AI Frontiers ∙ 17 LIKES ∙ 4 RESTACKS

Nate Sharpe

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Mar 4

“Count me as skeptical that this happens anytime soon.” - what do you define as “any time soon”? It seems very feasible within 10 years, and almost definite within 20, which seems quite soon in the grand scheme of things to me and well within the definition of “rapid change”.

Another potential negative is if the bottlenecks that remain are low status/or just not interesting or fulfilling to most people. If AI outcompetes humans and most or all knowledge work in the near future and the bottlenecks is physical drudgery, that seems small comfort.

Frank Bruno

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Mar 5

Love this counterintuitive take on why we should root for AI to "beat us by a mile"! Your point about bottlenecks perfectly illustrates why we must ensure the underlying architecture is structurally sound rather than just a "marginally better" imitation that offers no real economic anchor. I commend this masterful analysis for proving that the real value for workers lies in the integrity of the tasks machines cannot master!

Grounded AI

Mar 10

Grounded AI and SciFlow: Bringing Veracity into the Writing Workflow

We’re excited to share that Veracity is coming to SciFlow — embedding citation checks where they matter most: while you write.

At Grounded AI, we built Veracity because we believe citation integrity shouldn’t be an afterthought. Too often, problematic references — retracted papers, mismatched metadata, unverifiable sources — only surface during peer review or, worse, after publication. By then, the cost to authors, editors, and institutions is already significant.

Grounded AI ∙ 5 LIKES ∙ 1 RESTACKS

The AI Evaluation Substack

Feb 27

2026 February "AI Evaluation" Digest

Quis custodiet ipsos custodes?

Some of the most interesting benchmarks are starting to look less like thermometers and more like courtrooms. Instead of passively registering performance, task success must be argued over, weighed, and ultimately adjudicated. This month’s through-line is that evaluation is no longer just about better questions; it is about understanding the evaluator. …

AI Evaluation ∙ 14 LIKES ∙ 1 RESTACKS

Pawel Jozefiak

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Mar 2

The point about benchmarks breaking when the judge can't keep up hits something I noticed practically. Built on Mistral during the EU Hackathon last weekend and what struck me wasn't any single failure - it was the cumulative management overhead.

Constant small corrections that add up. It's not captured in any benchmark I know of, but it changes what you're willing to build. 'Developer experience under realistic pressure' is probably its own evaluation dimension. Wrote about it here if anyone wants a non-benchmark data point: https://thoughts.jock.pl/p/mistral-ai-honest-review-eu-hackathon-2026

Alex Willen

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Feb 27

This is a great roundup, thanks. The moral performance piece is pretty fascinating to me - with humans I would say it matters more whether a person is doing the right thing than whether it’s for the right reasons, but we’re not growing exponentially in capabilities.

Mint Tech & AI

Mar 6

AI & War: Principle, Profit and Agentic AI combat

Anthropic out, OpenAI in. Iran war rages on. The Human, in all of this, is not amused.

Last week, we wrote about Anthropic’s emergence as the poster child of AI. That was short-lived. The US Department of War (formerly, Pentagon) chose the more pliable OpenAI to do business with, even as it threatened to label Claude AI as a “supply-chain risk”, due to Anthropic’s reluctance to allow use of its models without the couple of extra guardrail…

Leslie D'Monte ∙ 8 LIKES

AI Monk

Mar 10

Perplexity Computer Is Changing AI Search From “Finding Answers” to “Getting Work Done”

We all use search engines every day. But let’s be honest — searching often means opening many tabs, reading different websites, comparing information, and spending a lot of time before we get one clear answer. 😅

AI Monk ∙ 10 LIKES

Christopher Dollar

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Is this a sponsored piece?

Creators' AI

Mar 6

Claude #1 on App Store, GPT-5.4 Lands, DeepSeek V4 Is Here | Weekly Digest

Alibaba’s Qwen drama, the anti-AI march in London, and tools of the week

Hey! Welcome to the latest Creators’ AI Edition.

Creators AI ∙ 11 LIKES

Learn AI Together

Mar 12

LAI #118: What’s Actually Happening Inside Your AI Models

RL agents, gradient failures, automatic differentiation, statistical testing, and VAEs for real anomaly detection.

Good morning, AI enthusiasts,

Louis-François Bouchard, Towards AI, and Louie Peters ∙ 4 LIKES

AI Monk

Mar 8

AI Agents for Entrepreneurs: Run Your Business Like a Team of 10 Without Extra Hires

If you’re running a small business, you already know the truth: your biggest problem isn’t ideas—it’s time.

AI Monk ∙ 13 LIKES

The AI Dispatch - PE Edition

Mar 12

PE's AI Posture Gets Serious

How Implementation Intelligence is Transforming Portfolio Performance

Hi, I’m Lily. I created this PE edition of the AI Dispatch for our growing community of thousands of private equity leaders and portfolio company operators navigating AI implementation.

InstaLILY AI ∙ 8 LIKES