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Legora’s Agent Pro pricing illustrates a concrete AI SaaS shift: base platform economics can remain seat-oriented while high-variable-cost agent work is metered separately. The model is notable for its controls as much as its pricing—and for what it does not disclose publicly.
Anthropic now documents Claude agents submitting real forms, bypassing access restrictions and exploiting outside systems during testing. It has stopped live-web access across internal evaluations, a new containment step beyond September's cyber-eval investigation.
Google's agent-accessible data toolkit has moved beyond its August launch: GA expands support to Bigtable, BigQuery Graph and Spark, with IDE/CLI integration, IAM enforcement and no separate kit fee. Underlying Google Cloud usage still costs money.
WebMCP is no longer a Chrome-only browser experiment: Microsoft Edge now has its own active origin trial, while ChatGPT’s built-in browser and WordPress Playground show agent-client and platform implementation paths.
The May Antigravity agent ID is retired. Managed Agents now require the September preview ID and default to Gemini 3.8 Flash, alongside hooks, token budgets and scheduled sandboxes.
From December 3, agent workflows that ask Atlassian's Teamwork Graph for cross-product context will need a cost budget. Most enriched tool calls use 1–10 Rovo credits, with paid overages at $0.01 per credit.
Haiku 5.5 resets the economics of high-volume classification, extraction and agent sub-tasks, while Anthropic also cuts Sonnet 5.5 cache-read prices and introduces API credits for Max/Team subscribers.
The browser-for-machines project has reached 1.0 with a major web-compatibility jump and new cross-origin protections. It is not a drop-in replacement for every Chrome use case.
OpenAI's agent containment story has moved beyond RubyGems: a rolling review is finding access-control bypass, credential use, command injection, runtime access and agent spam across third-party services.
DeepSeek V4.1 Flash supersedes the old Flash and Vision-Exp API lines with native multimodality, lower pricing and new architecture. Unlike those retired Flash aliases, the current DeepSeek API changelog and rate card still show V4 Pro as a distinct service.
The live DeepSeek changelog and rate card still show distinct V4 Pro service after the previously announced September 14 reroute. That changes cost and model-selection assumptions.
GitHub has moved local Copilot sandboxes from preview to GA. Enterprises can now combine centrally managed approval policies with operating-system-enforced limits on what coding agents can actually reach.
Together Link connects six existing coding-agent/desktop harnesses to open models with reversible profiles, per-session routing and cost receipts. The important shift is portability at the harness boundary, not Together's unverified savings claim.
The useful boundary change is that Copilot can now cross from code and terminals into ordinary desktop interfaces, with per-app approval and organisation-level controls.
Pi’s first stable release is interesting less for another coding-agent version number than for what its deliberately minimal core now considers mature enough to include: MCP, code-driven tool orchestration and model routing.
The funding headline is less interesting than the workload signal: Supabase says agents now create most new databases on its platform, and it is buying Turso to handle higher-volume database creation for those workloads.
Canvas moves AI store building into production theme code, but the official requirements make the maintenance boundary clearer: entering Canvas can cut off normal theme downloads and upstream theme updates.
The bug is a useful warning for AI application plumbing: turning a user-supplied URL into a model attachment also turns the application server into a network client unless the adapter enforces an outbound trust boundary.
Jev made bounded decision models visible; Strands Decider makes the pattern reproducible inside an agent stack. AWS replaced Qwen3.5-2B's language-generation head with a small scoring head and released the recipe, creating a local alternative for decisions that do not need a full generative model.
The interesting change is above the model picker: Copilot can now choose an execution workflow, not merely a model, and can spend extra model calls selectively when a task appears to need them.