I'm Matt Wood, and this is For Your Information. A live list of riffs and links for you and your agent, drawn from what I'm reading, noticing, questioning, concluding, and revising.

With this release MCP becomes a stateless protocol that scales on ordinary HTTP infrastructure. Every request now carries protocol version, client info, and client capabilities inside its _meta parameter, eliminating the need for a one-time initialization handshake. Clients that need to learn what a server supports can call the new server/discover method at any point.

Companies that invest heavily in AI grow headcount 10% over the two years following adoption. Entry-level headcount grows 12%.

Jensen Huang positioning: "Fireworks is the TSMC of AI Factories..."

In both cases, the country is celebrating a major birthday in the midst of a rising stock market and widespread fears of "technological unemployment" (mechanical power then vs. AI now); giddy wealth is coiled with economic anxiety; technology has transformed the way that people get information, mind-wiring us to a global cacophony of far-flung emotions (radio then vs. social media now).

From the homepage: "Build something Lovable. Create apps and websites by chatting with AI." Templates include spatial canvas tools, blogs, habit trackers, code-powered presentation builders, and e-commerce stores. Key metrics highlighted: millions of projects built, with substantial new projects created per week.

Transfer finding: "Learn it on the wrist. Use it anywhere on the body. Pretrain once on the wrist, then point the model anywhere. It holds up on body placements, and even sensor types like gyroscope and magnetometer, that it never saw during training."

Post-conditions pattern:

@ai_function(post_conditions=[check_length, check_style], max_attempts=5)
def summarize_meeting(transcripts: str) -> MeetingSummary:
    """Write a summary of the following meeting in less than 50 words."""

Post-conditions can be plain Python assertions or other AI Functions. The function only returns once eve

Custom agents provide a way to customize Kiro behavior by defining specific configurations for different use cases. Each custom agent is defined by a configuration file that specifies which tools the agent can access, what permissions it has, and what context it should include.

What the techno-determinism angle misses is: Why did these technologies catch on in the first place? Not every technology people have invented has caught on the way these forms have. They caught on in large part because of this impulse people have to live in a uni-context.

Agents need clarity above everything else — APIs where reading the code tells you exactly what it does.

Maintainers are now facing an assault on two fronts. The barrier to entry for generating code has dropped to zero... flooded repository gates with an alarming volume of low-quality, AI-generated pull requests. Maintainers who once spent their time writing code are now forced to become full-time, unpaid code reviewers.

Key positioning: "Stop relying on generic AI models. Databricks has the tools to build agent systems that deliver accurate, data-driven results."

In the run that used GPT-5.5 for both planners and workers, the workers alone cost $9,373. In the run where Opus 4.8 did the planning and Composer 2.5 did the work, the entire worker fleet cost $411.

Valkey is an open source (BSD) high-performance key/value datastore that supports a variety of workloads such as caching, message queues, and can act as a primary database. The project is backed by the Linux Foundation, ensuring it will remain open source forever.

ARC-AGI-3 gives an agent a game environment, without an explanation of what it is seeing. At each step, the agent receives a 64×64 grid of 16 color indices and a set of legal actions. The environment supplies no object list, rule sheet, stated goal, or shaped reward.

Key research highlights at ICML 2026: - FlashAttention-4: Algorithm and kernel pipelining co-design for asymmetric hardware scaling (Tri Dao et al.) - Mamba-3: Next-generation state space model (CMU + Princeton + Together + Cartesia) - DeepSWE: Fully open-sourced state-of-the-art coding agent trained by scaling RL - Cache-aware prefill-decode disag

Baseten delivers the infrastructure, tooling, and expertise needed to bring the most performant AI products to market, fast.

Key specs: - Battery: LiFePO4, 51.2V 75Ah (3,840Wh), expandable to 53.8kWh - Output: 6,000W max (12,000W with expansion), 120V/240V via NEMA L14-30R - Solar: Dual 165V MPPT inputs, 1,600W each (3,200W total), full charge in 1.5 hours - USB-C: 100W per port - UPS switchover: 20ms - Weight/size: 27.6 x 15.3 x 15.6 inches, on wheels - Cycle life: 3,00

The policies that require tracking state across events are also the ones that rarely specify the concrete commands and paths needed to write the rule. Cross-event policies are 95% context-dependent (77% project, 19% task).

"We are building an intelligence layer for the entire aviation system with Zee. The company that owns the data and the foundation model will help lead the aviation industry into the next era of flight," said Adam Goldstein, founder and CEO of Archer.

A metastable failure is a self-sustaining congestive collapse in which a system degrades in response to a transient stressor (e.g., a load surge) but fails to recover after the stressor is removed. These rare but potentially catastrophic events are notoriously hard to diagnose and mitigate, sometimes causing prolonged outages affecting millions of

Model specs: - 975B total params, 41B active (Mixture-of-Experts) - Inkling-Small: 12B active params - 1M token context window - Pretrained on 45T tokens (text, images, audio, video) - Controllable thinking effort (0.2 to 0.99 sweep)

"The command line of the past was machine-first: little more than a REPL on top of a scripting platform. Today's command line is human-first: a text-based UI that affords access to all kinds of tools, systems and platforms."