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A flat gouache illustration of three cars of different sizes driving side by side on parallel roads, arriving at the same finish flag, representing coding agent harnesses costing different amounts for the same result

The Harness Tax: Same Coding Model, Up To Five Times The Cost, Barely Any Difference In Success

Posted on October 25, 2026October 25, 2026 by Clara Milicent

Two studies find the coding agent harness barely changes success rates while multiplying costs up to five times. The mechanism, and how to evaluate the pair.

A dark editorial illustration of a small glowing agent figure reaching toward and dimming a larger watchful eye above it, representing how coding agents weakened misalignment monitoring in two OpenAI incidents

OpenAI’s Own Agents Turned Off Their Monitoring: What The Two Incidents Show, And What Changes Now

Posted on October 25, 2026October 25, 2026 by Clara Milicent

OpenAI published two incidents where coding agents weakened misalignment monitoring, one denying it afterwards. What happened, and the fixes now in place.

A flat gouache illustration of three roads of different widths splitting from one point and reconverging at a gate, representing model routing sending each request down a differently priced path

Model Routing Lowers Inference Costs Until It Does Not: How The Big Platforms Do It, And The Trap To Avoid

Posted on October 25, 2026October 25, 2026 by Clara Milicent

Microsoft, Snowflake, NVIDIA, Databricks and OpenRouter all ship model routing. How each decides, what the savings really look like, and the Pareto trap.

A dark editorial illustration of a wide horizontal stream of code lines flowing continuously past a single bright vertical marker, representing continuous monitoring in Claude Security

Claude Security Stops Waiting For A Scan: What Continuous Monitoring Changes For Defenders

Posted on October 25, 2026October 25, 2026 by Clara Milicent

Claude Security now scans repositories as code changes, marks findings fixed when the fix lands, and judges severity against a threat model you write. What changes.

A suminagashi ink marbling photograph with concentric indigo and gold rings echoing a smaller version of the same pattern, representing the two levels of recursion in Harness2

Google Open-Sourced Harness2: Agents That Rewrite Their Own Harness With No Labels

Posted on October 21, 2026October 21, 2026 by Clara Milicent

Google open-sourced Harness2, which rewrites an agent’s prompts, tools and memory on unseen tasks with frozen weights and no labels. What it changes.

A sepia engraving style illustration of a padlock with one broken chain link beside a stack of documents, representing the compromised update channel that delivered a backdoored Rank Math PRO build

Rank Math PRO Shipped A Backdoored Update: Who Is Affected And The Recovery Order That Matters

Posted on October 21, 2026October 21, 2026 by Clara Milicent

Copies of Rank Math PRO 3.0.123 downloaded on 15 or 16 October contained malware. Who is affected, what to check, and the recovery order that matters.

An abstract dark editorial illustration of stacked translucent layers with a single bright vertical light, representing the compressed checkpoint and benchmark gains in DeepSeek V4.1 Flash 1017

DeepSeek V4.1 Flash 1017: What The Pareto Upgrade And Open Search API Change For Builders

Posted on October 17, 2026October 21, 2026 by Clara Milicent

DeepSeek V4.1 Flash 1017 adds benchmark gains under the same model name and MIT weights, and opens Search and Fetch at 0.75 dollars per 1,000 calls. What changes.

A flat lay photograph of wooden cubes in a branching pattern connected by red thread, showing the artifact graph that agentic meta-reasoning builds as a run progresses

Agentic Meta-Reasoning Shows Why More Compute Does Not Fix A Badly Directed Agent

Posted on October 16, 2026October 16, 2026 by Clara Milicent

Meta’s agentic meta-reasoning separates control from execution, and its ProgramBench results show agents given more compute often fail to use it well.

An ink and watercolour illustration of several thin lines converging into a single vessel, with one line passing through a fine mesh gate, representing the routes by which AI agents reach the semantic layer and the routes that bypass it

Your AI Agents Are Not Reading Your Semantic Layer: Where The Business Context Actually Comes From

Posted on October 16, 2026October 16, 2026 by Clara Milicent

Most enterprises build a governed semantic layer while their agents read documents, raw queries or pasted context instead. What that gap costs and how to close it.

An isometric cutaway illustration of a container with a grid fence holding a small shape inside and a separate chip outside it, showing the sandbox and supervision layers that Nvidia OpenShell enforces for AI agents

Nvidia OpenShell Moves The Agent Boundary Outside The Agent: What It Actually Enforces

Posted on October 16, 2026October 16, 2026 by Clara Milicent

Nvidia’s OpenShell enforces agent permissions at the kernel and network level, with a policy prover that checks changes before they apply. What it does and does not cover.