Amaze Networks Morning Briefing — Monday, March 30, 2026

Week of March 30 | Network Architecture · Automation · AI/ML · Science · Security Architecture

🔝 Top 3 Highlights

1. Ethernet Has Won the AI Fabric War

TL;DR: Broadcom's March 2026 earnings confirmed 70% of new AI cluster deployments now choose RoCEv2/Ethernet over InfiniBand — and the hardware is finally catching up to that market reality with the first UEC-compliant 800G NIC and multi-switch UET validation.

Key Points:

Broadcom earnings: ~70% Ethernet/RoCEv2 vs. 30% InfiniBand for new AI deployments; Broadcom AI revenue is now 44% of total company revenue
Thor Ultra NIC: First 800G NIC fully compliant with Ultra Ethernet Consortium Specification 1.0 — per-packet ECMP multipathing, selective retransmission, and programmable congestion control (features previously exclusive to InfiniBand) now native to open Ethernet. Commercial sampling underway, OEM shipments H2 2026
Nokia SR Linux: First vendor to publish validated end-to-end multi-switch Ultra Ethernet Transport (UET) results at 800G, covering the full 7220/7250 IXR switch family. SR Linux's gNMI-first architecture means this UEC-validated fabric is also fully programmable via OpenConfig from day one
RoCEv2 runs on commodity switching silicon — including SONiC-based platforms. This isn't just a NIC story; it validates the entire open networking stack for AI

Deep Dive: The InfiniBand vs. Ethernet debate has been running since at least 2019, when RoCEv2 proponents argued that with good enough congestion control, open Ethernet could match IB's latency and reliability characteristics. NVIDIA always had a counter: their NVLink/NVSwitch/InfiniBand bundle delivers end-to-end SLA in a way that commodity Ethernet couldn't guarantee. The 70% Broadcom earnings figure says the market has voted.

What changed? Three things came together. First, DCQCN (Data Center Quantized Congestion Notification) matured to the point where it handles most congestion scenarios at practical cluster sizes. Second, the Ultra Ethernet Consortium delivered Specification 1.0 in 2025, standardizing the missing pieces — out-of-order delivery, selective retransmit, per-packet multipathing — that IB had always held as architectural advantages. Third, economic reality: Ethernet switches run on commodity ASICs and open NOS platforms. InfiniBand infrastructure costs 2-3x more per port and locks you into NVIDIA's vertical stack.

Thor Ultra is the proof point. Broadcom (the company that also makes the Tomahawk ASICs in most Ethernet switches) now ships the NIC that closes the last technical gap. Nokia running end-to-end UET tests across a full switch family — not a single device bench test — removes the "it works on paper but not in a real fabric" objection. The remaining 30% InfiniBand market is concentrated in dense GPU pods where NVLink/NVSwitch bundles are simply part of the NVIDIA purchase, not a separate architectural decision.

For network architects, the practical implication is significant: SONiC-based fabrics with RoCEv2 tuning are now the mainstream path for AI clusters, not the challenger. Dell Enterprise SONiC supports RoCEv2 with DCQCN. This validates the investment.

So What? The InfiniBand vs. Ethernet question is answered for new AI cluster builds — if you're speccing fabric today and choosing open networking, you're with the majority, not fighting the tide.

Sources: Broadcom March 2026 Earnings / FirstPassLab · https://firstpasslab.com/blog/2026-03-09-roce-vs-infiniband-ai-data-center-networking/ | Nokia Newsroom · https://www.nokia.com/newsroom/nokia-strengthens-leadership-in-ai-ready-data-center-networks-with-successful-end-to-end-ultra-ethernet-test-across-data-center-switch-family/ | Broadcom Thor Ultra · https://investors.broadcom.com/news-releases/news-release-details/broadcom-introduces-industrys-first-800g-ai-ethernet-nic

2. Event-Driven Infrastructure: The Post-GitOps Pattern Taking Hold

TL;DR: The fastest-moving infrastructure teams in 2026 are layering event-driven execution on top of GitOps rather than relying on pull-based reconciliation alone — a shift that changes how automation pipelines are triggered, not just how state is stored.

Key Points:

Pattern: Git holds templates and desired state; event bus (Kafka, AWS EventBridge, Argo Events) provides the trigger layer
ArgoCD/Flux reconciliation loops remain but are now composable with operational event sources — telemetry thresholds, CI outcomes, ticket state changes, NetBox webhooks
Network automation translation: a BGP flap triggers Nornir runbook → Batfish validates proposed fix → Nautobot approval request → auto-deploys on approval — all Git-tracked, event-initiated, human-approved
Network automation teams are estimated 12–18 months behind cloud-native SRE in adopting this pattern — but the tooling is mature enough to prototype today
Companion pattern: Connectivity-as-Code (CaC) — network topology, VLANs, BGP peers, and firewall rules declared in the same IaC manifests as compute, provisioned and torn down with the application

Deep Dive: GitOps solved the "where is the truth?" problem for network configuration. Git is now widely accepted as the source of truth for network state, and tools like Batfish and ArgoCD provide continuous reconciliation. But pure pull-based GitOps has a gap: it reconciles toward desired state on a schedule or after a commit, but it doesn't respond to operational events in real time.

Event-Driven Infrastructure closes that gap. The mental model shift: Git is the configuration database and the audit trail, but events are what drive action. A BGP peer flap, a CPU threshold breach, a change ticket approval, a test suite failure — any of these can trigger a runbook, which queries the Git-tracked desired state, validates the proposed action via Batfish, and executes only if validation passes.

For a hands-on network engineer, the tooling is accessible: Argo Events or a simple webhook receiver on your Nornir server, wired to NetBox webhooks and your monitoring alerting, can get you to event-driven network remediation without rearchitecting your entire stack. The conceptual leap is larger than the implementation leap.

The Connectivity-as-Code extension takes this further — treating network segmentation policies and routing constructs as application dependencies rather than infrastructure prerequisites. This is bleeding edge for enterprise networking, but the architecture decision you make today (are your Ansible roles and Nornir tasks API-callable, or only human-run?) determines whether you can participate in CaC workflows in 3 years.

So What? Start wiring existing Ansible/Nornir runbooks to event sources from NetBox and your monitoring stack — the tools are ready, and this is where GitOps matures.

Sources: Medium (AWS in Plain English) · https://medium.com/@sneharani2509/gitops-is-dead-long-live-event-driven-infrastructure-heres-what-replaced-it-in-2026-b25f10e55911 | CalmOps GitOps 2026 Guide · https://calmops.com/devops/gitops-2026-complete-guide/ | Network to Code Batfish · https://networktocode.com/blog/batfish-fits-network-automation-plan/

3. Agentic AI Gets Its Governing Body

TL;DR: The Linux Foundation's Agentic AI Foundation has consolidated MCP, A2A, goose, and AGENTS.md under vendor-neutral governance with every major cloud provider as a platinum member — removing the "protocol abandonment" risk that was the last major enterprise objection to betting on agentic standards.

Key Points:

Platinum members: AWS, Anthropic, Block, Bloomberg, Cloudflare, Google, Microsoft, OpenAI — all major AI labs plus all major cloud providers
Gold members (18) include Cisco, Docker, IBM, Salesforce, SAP, Snowflake, Datadog
MCP: 10,000+ published servers, Fortune 500 deployment scale; AGENTS.md: 60,000+ open-source projects
Three-layer stack solidifying: MCP (tools/data) → A2A (agent-to-agent coordination) → WebMCP (web access)
MCP Dev Summit: April 2–3 in New York City — 95+ sessions, production deployment focus — this week
OpenClaw (see Fun One) runs MCP Registry integration natively — the protocol is becoming infrastructure

Deep Dive: The governance question has been the quiet blocker for enterprise MCP adoption. When a standard is controlled by a single vendor, procurement and architecture teams worry about lock-in, deprecation risk, and unfavorable commercial terms. Moving MCP and the broader agentic protocol stack under the Linux Foundation removes that objection in a way that no individual vendor adoption could.

The three-layer model is worth understanding as a design principle: MCP provides the tool and data connectivity layer (your NMS APIs, IPAM, ticketing system); A2A provides the agent-to-agent coordination layer (one specialized agent delegating to another); WebMCP provides web access for agents that need to reach external resources. Together, these three layers describe how a production agentic system communicates — and they're now standardized.

For practitioners building AI-assisted network operations tooling, this is a green light on MCP as the integration layer. Building a NetBox MCP server (already shipped by Network to Code), wiring it to a Nornir executor agent via A2A, and providing an operator-facing chat interface via any MCP-capable LLM client is now a well-defined architecture with industry-standard protocols at each layer.

So What? The MCP Dev Summit on April 2–3 will produce the clearest signal yet of what production agentic infrastructure actually looks like — worth watching the sessions and community output.

Sources: Linux Foundation AAIF · https://www.linuxfoundation.org/press/linux-foundation-announces-the-formation-of-the-agentic-ai-foundation | MCP Dev Summit · https://events.linuxfoundation.org/2026/02/24/agentic-ai-foundation-unveils-mcp-dev-summit-north-america-2026-schedule/

🌐 Networking

IETF BGP YANG Model Draft-19 Advances Standardized Programmatic BGP

TL;DR: The IDR working group's BGP YANG model draft continues active progression toward RFC status, providing the foundational data model for programmatic BGP configuration via gNMI, NETCONF, and RESTCONF — the spec that Dell Enterprise SONiC implements for gNMI-based BGP automation.

Draft-19 covers full BGP policy augmentation: neighbors, communities, route-maps — all configurable via YANG without CLI
Companion draft: BGP-PIC (Prefix Independent Convergence) advancing alongside — prefix-independent reconvergence in multi-path fabrics without management provisioning
Dell flag: Dell Enterprise SONiC implements this YANG model via Management Framework for gNMI BGP config; BGP-PIC flows into FRR (SONiC's BGP stack)

So What? Standardized BGP YANG is what makes "configure BGP via Ansible over gNMI" reliable across vendors — and it's getting closer to RFC. Start testing your gNMI BGP configuration paths against draft-19 today.

Source: IETF Datatracker · https://datatracker.ietf.org/doc/draft-ietf-idr-bgp-model/ | BGP-PIC · https://datatracker.ietf.org/doc/draft-ietf-rtgwg-bgp-pic/

Cisco Silicon One G300: 102.4 Tbps ASIC Challenges Broadcom for AI Switch Silicon

TL;DR: Cisco's Silicon One G300 — 102.4 Tbps, on-chip 200G SerDes, 512-port radix, 28% GPU utilization improvement claim — is the first credible proprietary challenger to Broadcom's Tomahawk dominance in AI fabric silicon. Systems ship H2 2026.

Intelligent Collective Networking: shared packet buffer + path-based load balancing for reduced GPU job completion time
No external retimers required; 33% increased network utilization claim
Proprietary silicon (not open ecosystem), but 1.6T port support future-proofs the platform
Competing with Tomahawk 6 series in the AI hyperscaler sweet spot

So What? Cisco's G300 is worth tracking as competitive pressure on Broadcom pricing — even if you're building on open silicon, market competition drives down cost and pushes feature development.

Source: Cisco Newsroom · https://newsroom.cisco.com/c/r/newsroom/en/us/a/y2026/m02/cisco-announces-new-silicon-one-g300.html | The Register · https://www.theregister.com/2026/02/10/cisco_challenges_broadcom_nvidia_switch_chips/

⚙️ Automation

Nautobot 2.4.29 Released; v3.1 Alpha in Development

TL;DR: Nautobot v2.4.29 dropped March 17 with a new port_type field on Interface models and security patch for pyjwt. The v3.0 baseline brought Approval Workflows and new Load Balancer/VPN models; v3.1 alpha is now in pre-release.

v2.4.29: port_type field on Interface and InterfaceTemplate (SFP28, QSFP-DD, etc. trackable at model level), per-user locale preferences, async subprocess job capture, pyjwt → 2.12.1
v3.0 baseline: Approval Workflow system for change control — this is what enables proper automated playbook gates; Bootstrap 5 UI, new navigation
v3.1 alpha: active pre-release on GitHub; pip install nautobot --pre
The Approval Workflow in v3.0 pairs directly with Event-Driven Infrastructure patterns — wire Ansible/Nornir runs to a Nautobot approval gate before deployment

So What? If you're on Nautobot 2.x, the port_type field alone is worth the upgrade; v3.0's Approval Workflows are the change-control primitive your automation pipeline is probably missing.

Source: GitHub Releases · https://github.com/nautobot/nautobot/releases | Network to Code · https://networktocode.com/blog/whats-new-in-nautobot-3-0-2025-12-18/

Wingpy: Unified Cisco API Client Gets Packet Pushers Spotlight

TL;DR: Wingpy (open-source, MIT) provides a single Python client across the entire Cisco API estate — FMC, APIC, Catalyst Center, SD-WAN vManage, ISE, Meraki, Nexus Dashboard — with auto-handled auth, pagination merging, and parallel page retrieval.

pip install wingpy covers all platforms; FMC(), CatalystCenter(), ISE() etc. as client classes
Auto-handles: authentication on first request, paginated result merging, parallel retrieval, domain UUID substitution
Featured on Packet Pushers NAN115 (March 2026)
The "unified vendor SDK" pattern is directly applicable to any multi-platform automation — worth borrowing the parallel page retrieval design for custom API clients

So What? Even if Cisco isn't your primary stack, the unified SDK pattern + parallel pagination design is worth studying for your own API client implementations.

Source: Packet Pushers NAN115 · https://packetpushers.net/podcasts/network-automation-nerds/nan115-simplifying-network-automation-with-wingpy/ | PyPI · https://pypi.org/project/wingpy/

AI Copilots Enter the CI/CD Pipeline as Config Review Gates

TL;DR: Network to Code March 2026 analysis documents AI copilots moving from advisory chat to active CI/CD pipeline roles — flagging policy violations pre-commit, suggesting remediation on failed tests, and acting as a "second reviewer" in automation pipelines.

NetBrain AI Co-Pilot and Selector Network LLM are the two production deployments cited most
These are fine-tuned or RAG-augmented on network-specific corpora — not general-purpose LLMs
Self-built version: a pre-commit hook sending Ansible playbook diffs to Claude API for anti-pattern review costs minimal effort to prototype and adds meaningful safety
The architectural distinction: AI as pipeline gate (blocking) vs. AI as advisor (informational)

So What? Wire a Claude API call into your Ansible pipeline as a pre-deploy config reviewer — it's a one-afternoon project that improves safety meaningfully.

Source: Network to Code · https://networktocode.com/blog/2025-03-27-ai-netdevops-reshapes-network-automation/ | Packet Pushers · https://packetpushers.net/blog/the-future-of-network-and-infrastructure-management-is-ai-powered-heres-how-to-get-ready/

🤖 AI/ML

NVIDIA Groq 3 LPX Rack: First Dedicated Inference Silicon Ships H2 2026

TL;DR: The Groq 3 LPX rack (256 LPUs, 150 TB/s memory bandwidth, copper chip-to-chip spine) is NVIDIA's first purpose-built inference hardware — targeting trillion-parameter decode workloads with a claimed 35x improvement in tokens per megawatt versus Blackwell alone.

256 LPUs per LPX rack; 32 compute trays × 8 LPUs; direct chip-to-chip copper interconnect
512 MB on-chip SRAM per die (Samsung 4nm); 150 TB/s memory bandwidth — SRAM-based, not HBM
Combined Vera Rubin NVL72 + LPX architecture: up to 35x tokens/MW and 10x revenue opportunity for trillion-parameter models
OpenAI confirmed early adopter (Codex use case); availability H2 2026
Formalizes a two-rack architecture: NVL72 for prefill/training + LPX for decode

Infrastructure angle: Power budgeting, rack layout, and cross-rack interconnect design must now account for LPX as a first-class inference tier. The copper chip-to-chip spine and multi-rack LPX pooling have direct networking implications.

So What? AI cluster sizing estimates from 6 months ago are likely too conservative — the LPX token/watt improvement changes capacity planning calculations for token-intensive agentic workloads.

Source: The Decoder · https://the-decoder.com/gtc-2026-with-groq-3-lpx-nvidia-adds-dedicated-inference-hardware-to-its-platform-for-the-first-time/ | ServeTheHome · https://www.servethehome.com/decoding-the-future-of-inference-at-nvidia-groq-lpus-join-vera-rubin-platform-for-low-latency-inference/

DeepSeek V4 Inference Architecture: 40% Memory Reduction, 1.8x Throughput

TL;DR: DeepSeek V4 introduces two architecture-level inference optimizations — tiered KV cache storage (40% memory reduction) and Sparse FP8 decoding (1.8x throughput) — that are now propagating into vLLM and HuggingFace TGI as the new efficiency baseline for open-weight deployments.

Tiered KV cache: hot layers in HBM, cold layers offloaded to cheaper memory tiers
Sparse FP8 decoding: selective attention head activation; 1.8x decode throughput with minimal accuracy degradation
These techniques are architecture-level, not GPU-vendor-specific — applicable to AMD, Intel Gaudi, custom silicon
Direct implication: larger context windows and longer agent chains on same hardware envelope

So What? Inference cluster sizing models need updating — these efficiency gains change what a given hardware investment can sustain for agentic AI workloads.

Source: StorageReview · https://www.storagereview.com/news/nvidia-gtc-2026-rubin-gpus-groq-lpus-vera-cpus-and-what-nvidia-is-building-for-trillion-parameter-inference

🔒 Security Architecture

Three-Tier Microsegmentation Framework Achieves 99.7% Attack Path Reduction

TL;DR: A peer-reviewed framework (March 2026) proposes a three-tier microsegmentation architecture — DNOS orchestration plane, ZFLOW system-level policy, and eBPF endpoint agents — with evaluations showing 99%+ ENICE reduction and 99.7% attack path reduction.

Tier 1: Network-level Zero Trust Orchestration (DNOS algorithm)
Tier 2: ZFLOW programmable system-level process control
Tier 3: Lightweight eBPF-based endpoint enforcement
eBPF enforcement tier maps directly to DPU-accelerated patterns (BlueField, Pensando) already in enterprise AI fabric deployments
First formally evaluated three-tier model — vendor-agnostic reference architecture

So What? This gives you a peer-reviewed baseline for evaluating microsegmentation vendor claims — map their architecture against these three tiers and see what's missing.

Source: ScienceDirect · https://www.sciencedirect.com/science/article/pii/S1110016826001638

Agentic AI in the SOC: Build the Governance Layer Before Granting Execution Rights

TL;DR: As AI agents move from advisory to autonomous execution in SOC workflows, the architectural imperative is governance-first: policy guardrails, human-approval gates for high-blast-radius actions, audit trails, and rollback mechanisms must be designed in before execution rights are granted.

AI agents in production = privileged network actors requiring the same ZTA controls as any privileged identity
Governance layer maps directly to approval gates in GitOps workflows before policy pushes execute
The "governance layer first" pattern applies equally to network automation: automated remediation runbooks need the same guardrails as SOC playbooks

So What? Before you extend your automation with AI-driven remediation, design the approval gate architecture first — not as an afterthought.

Source: Security Boulevard · https://securityboulevard.com/2026/03/agentic-ai-in-the-soc-the-governance-layer-you-need-before-you-let-automation-execute/

CSA: AI Security Must Be Programmable and CI/CD-Native by Default

TL;DR: The Cloud Security Alliance's "State of Cloud and AI Security in 2026" report establishes that AI security is a software engineering discipline — sandboxed tool execution, scoped credentials, adversarial testing in release workflows, and cryptographically signed model artifacts are 2026 design requirements, not optional best practices.

Model updates, prompt changes, and agent reconfigurations must each trigger predefined security test suites automatically
Direct parallel to software supply chain security — signed playbooks, verified images
This is the moment AI security architecture formally inherits from DevSecOps

Source: Cloud Security Alliance · https://cloudsecurityalliance.org/blog/2026/03/13/the-state-of-cloud-and-ai-security-in-2026

🔬 Science

IBM Quantum "Loon" Chip Integrates All Fault-Tolerant Components for the First Time

TL;DR: IBM's 112-qubit Loon processor — now in active validation testing — is the first chip to co-integrate every hardware element required for fault-tolerant quantum computing, including real-time classical error decoding under 480 nanoseconds using qLDPC codes (a full year ahead of schedule).

Key additions: multiple high-quality routing layers, "c-couplers" for non-adjacent qubit connectivity, mid-circuit qubit reset
480ns real-time decoding threshold: classical hardware can now correct errors faster than they propagate
IBM targets: verified quantum advantage by end of 2026; full fault tolerance by 2029
Loon is the architectural blueprint — not just a faster version of previous IBM chips, but a different integration philosophy

So What? Fault-tolerant quantum is now an engineering problem, not a physics problem. IBM's 2029 timeline is more credible today than it was six months ago.

Source: PostQuantum.com / IBM Newsroom · https://postquantum.com/industry-news/ibm-loon-nighthawk/ | Status: Industry announcement, preliminary validation

IceCube Detects a Bend in the Cosmic Neutrino Spectrum at 30 TeV

TL;DR: Fourteen years of South Pole data reveal a statistically significant spectral break at ~33 TeV in the astrophysical neutrino spectrum — 4-sigma confidence in Physical Review Letters — suggesting at least two distinct cosmic source populations, not one.

Below 33 TeV: harder (flatter) spectrum; above: steeper power law consistent with prior observations
14-year dataset with refined ice models and systematic corrections
Aligns with predictions linking neutrinos to diffuse gamma-ray background (shared source origin)
Most structurally significant refinement to the astrophysical neutrino spectrum since initial IceCube discovery

Source: Physical Review Letters 136 (March 26, 2026) · https://journals.aps.org/prl/abstract/10.1103/2gh9-d4q7

LHAASO Resolves the Cosmic-Ray "Knee" With a Double Spectral Crossing

TL;DR: China's mountain observatory precisely separated proton and helium cosmic ray spectra across 0.16–13 PeV (straddling the mysterious "knee" at ~1 PeV), finding that the two species swap dominance twice — at 0.7 PeV and again at 5 PeV — no previous instrument could resolve this.

Protons overtake helium near 0.7 PeV; helium overtakes again near 5 PeV
Rules out single-source, single-mechanism models of galactic cosmic ray acceleration
Sets a new benchmark that theoretical acceleration/escape models must match
The cosmic-ray knee has been observed for 60+ years — this is its first resolved composition structure

Source: Physical Review Letters 136, 121001 (March 26, 2026) · https://lifeboat.com/blog/2026/03/elucidating-the-cosmic-ray-knee | Peer-reviewed (PRL)

⚡ Quick Takes

Connectivity-as-Code (CaC): A March 2026 pattern reframes network topology, VLANs, BGP peers, and firewall rules as programmable application lifecycle components — declared in the same IaC manifests as compute and provisioned/torn down with the app. 3–5 year horizon for brownfield enterprise, but the key decision now: make your Ansible roles API-callable. (Source: CalmOps · https://calmops.com/devops/gitops-2026-complete-guide/)
US Foreign Router Ban Pushback: A Georgia Tech public policy professor called the FCC's ban on foreign SOHO routers "industrial policy disguised as cybersecurity," arguing it strengthens Netgear's lobbying position without improving security. The architectural critique: supply chain security through procurement restrictions is fundamentally weaker than cryptographic integrity verification. (Source: The Register · https://www.theregister.com/2026/03/30/professor_criticizes_fcc_router_ban/)

🎯 The Fun One: OpenClaw Is The Fastest-Growing GitHub Project Ever — And Also a Security Catastrophe

OpenClaw, an MIT-licensed personal AI agent framework built on Node.js, crossed 335,000 GitHub stars in ~60 days — overtaking React's cumulative all-time record. It connects LLMs to 20+ messaging platforms (Slack, WhatsApp, iMessage, Discord, Teams, Telegram, and more) via a plugin architecture with 100+ prebuilt capabilities, MCP Registry integration, and Tailscale-native remote access for multi-device agent coordination.

It's genuinely clever engineering. And also: over 135,000 instances were publicly exposed as of February 2026, with approximately 15,000 vulnerable to remote code execution (CVE-2026-25253) because default configs bind to public-accessible interfaces without authentication.

The lesson here is depressingly familiar. A new tool achieves viral growth. The developer community deploys it enthusiastically. Security configuration is treated as optional setup rather than a default requirement. 15,000 RCE-vulnerable instances result. If OpenClaw is in your environment, audit your network exposure before anything else.

The capability story is real — this is the "personal Claude Code" moment for always-on agentic AI across all your communication channels. The security story is equally real. They coexist.

Source: GitHub · https://github.com/openclaw/openclaw | KDnuggets · https://www.kdnuggets.com/openclaw-explained-the-free-ai-agent-tool-going-viral-already-in-2026

👀 Watch Today

MCP Dev Summit (April 2–3, NYC): 95+ sessions on production MCP/A2A deployments — the agentic AI governance story gets its first large-scale practitioner showcase this week. Follow the session outputs.
IETF BGP YANG draft-19 progression: The path to RFC for programmatic BGP config is clear. Worth tracking for your gNMI automation roadmap.
Nokia UET fabric availability: SR Linux's gNMI-native UEC-validated fabric is commercially available now — worth a look if you're evaluating AI fabric vendors in 2026.
IBM Loon validation results: Interim results as IBM works toward end-of-2026 quantum advantage target.

📊 Pipeline Stats

Run type: Morning Briefing (Monday)
Date: 2026-03-30
Domains covered: Networking (5), Automation (4), AI/ML (4), Science (3), Security (3)
Quality score: 4/5
Dedup rejections: 1 (Groq 3 LPX borderline — included with new rack-level details distinct from 3/29 brief mention)
Sources used: ~20 web searches across 5 parallel domain agents
Estimated messages: ~38