Morning Digest, June 25, 2026

16 newsletters, 13 overlapping stories

Top Stories

Anthropic launches Claude Tag, a Slack-native AI teammate

(6 newsletters)

Anthropic gave Claude its own Slack account. Tag @Claude in any channel and it reads the conversation for context, takes on tasks, hands off threads, and can run solo projects for days, with admins controlling token spend and data sharing. It is in beta for Enterprise and Team customers, and Anthropic says the system has become core to its own internal operations. The launch landed hard across the newsletters, with several noting it puts the dozens of startups building “AI for Slack” assistants on notice.

OpenAI unveils Jalapeño, its first custom chip built with Broadcom

(5 newsletters)

OpenAI revealed Jalapeño, an inference-focused ASIC co-designed with Broadcom and taken from design to factory-ready in nine months, a cycle OpenAI calls the fastest ASIC development ever. The company says its own models helped design and optimize the chip, and that early testing shows performance per watt “substantially better than current state-of-the-art.” It is a major step toward owning the full stack and reducing reliance on Nvidia, with a goal of powering 10 GW of compute on custom silicon by 2029.

Mistral releases OCR 4 for document intelligence

(4 newsletters)

Mistral’s OCR 4 returns not just clean text but bounding boxes, typed blocks, and per-region confidence scores, feeding citation-ready chunks directly into RAG and agent pipelines. It supports 170 languages, runs self-hosted in a single container, and claims a roughly 4x speed advantage over rival systems. API access starts at $4 per 1,000 pages.

The shift from prompts to “loops” in agentic coding

(3 newsletters)

A recurring theme this week is the move from one-shot prompting toward automated “loops” where coding agents run repeatedly against a clear definition of done. Proponents argue loops let agents handle porting, refactors, and long-horizon work with less back-and-forth, while skeptics warn that overly hands-off runs produce less comprehensible, harder-to-maintain code and can quietly burn through token budgets. The consensus advice is to give agents a testable target and keep a human reviewing diffs. See also Writing Loops, Not Prompts.

Krea opens the weights to two fast image models

(3 newsletters)

Krea released Krea 2 Raw, an unaligned base checkpoint for training custom styles and LoRAs, and Krea 2 Turbo, which renders native 2K visuals in about two seconds on consumer hardware. Both are available on Hugging Face, aimed at developers who want to port custom tuning across the two models without fighting built-in aesthetic defaults.

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