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Showing 41–60 of 114 dossiers

Funes gives coding agents a local memory that can follow you across tools and machines

Funes treats agent memory as user-owned data rather than a hosted account feature: retrieval and reranking run locally, provenance stays attached to recalled passages, and cross-machine sharing is optional. The main risk is that publishing session-derived memory can still expose secrets if redaction misses them.

Reddit’s tracked share of ChatGPT Search citations fell 86% in mid-August

A third-party GEO dataset recorded an 86.4% relative collapse in Reddit’s visible ChatGPT Search citation share while Google AI citation changes were much smaller. The result is a useful warning against building an AI-discovery strategy around one source platform, not proof of an OpenAI penalty or Reddit removal.

LinkedIn Ads API adds a 1,000-segment audience cap as Legacy Geo shuts down August 31

Audience-management systems can now fail with `SEGMENT_LIMIT_EXCEEDED`, while old geography identifiers begin returning invalid-field errors after August 31. LinkedIn also opened the Matched Audiences API to applications from qualified developers, increasing the importance of handling these limits correctly.

TRACE gives AI agents a portable, hardware-attested runtime evidence format

TRACE targets a gap between audit promises and what an AI agent actually did at runtime. Its v0.2 developer preview can bind model, policy, data and tool-use claims to confidential-computing attestation, but it is still pre-ratification and explicitly not ready to treat as a production compliance guarantee.

VS Code is moving coding agents into a standalone host with shared AHP sessions

Microsoft is rearchitecting VS Code around a dedicated Agent Host rather than treating each coding agent as an editor-bound extension. AHP gives different harnesses one shared session model, but the rollout is still active and VS Code 1.132 removed the administrator policy that had centrally disabled the Agent Host.

WebMCP gives websites a structured tool layer for browser agents

WebMCP has crossed from a browser experiment into a usable agent integration: ChatGPT’s built-in browser now discovers site tools out of the box, while Chrome exposes the proposed standard through an origin trial. Builders can add structured actions to existing web apps, but the API and security model remain experimental.

Codex 0.149.0 ships asynchronous user messaging so agents can keep working after questions

Codex 0.149.0 includes the async-message tool, delivery metadata and removal of the client-side feature gate that BTN previously tracked only on main. Parallel human-agent work is now in a stable client, but late replies can still race with decisions and model capability metadata remains the final exposure gate.

Agent Plugins 1.0 now has a concrete cross-client compatibility layer for Skills and MCP

Agent Plugins 1.0 now has documented support across VS Code, Cursor, GitHub Copilot, ChatGPT/Codex, Kiro and several open-source agents. That makes the format materially more useful for cross-client distribution, but portable components remain limited to Agent Skills and MCP servers while permissions, hooks, commands and host UX stay client-specific.

A 3,940-product SaaS census finds flat platform pricing is more common than pure per-seat billing

The useful finding is not that one pricing model has 'won.' It is that observable SaaS pricing is much more heterogeneous than the default per-seat narrative suggests—and that the answer changes sharply with methodology. PulseSignal’s living public-price census keeps moving, and its latest disclosed extraction audit improved to 90%, but the data should still be treated as directional packaging evidence rather than a universal market truth.

Google is adding hard spend caps and commitment pricing for AI agent workloads

Google’s new agent FinOps model combines hard monthly spend caps that pause agent API calls, Flexible Savings Plans with one- or three-year commitments, pay-as-you-go Gemini Enterprise usage and planned deferred execution at up to half normal inference cost. The controls are useful, but commitment economics and task eligibility need to be modeled carefully.