Akamai vs Amazon Web Services (AWS)

a16z Leads Series A in Private Network Startup doxxnet

Andreessen Horowitz (a16z) announced it is leading a Series A investment in doxxnet, a startup building a private, parallel internet infrastructure for individuals and AI agents. doxxnet offers a software-defined global network with non-Internet domains, encrypted peer-to-peer communication, and DNS-level threat protection, all without requiring personal information like email or phone. The company is founded by Barrett Lyon, known for Prolexic (acquired by Akamai), BitGravity, and Defense.net. The funding will support the development of its 'Agentic Defined Networking' concept, which allows users and their agents to configure and control the network. The announcement highlights growing privacy needs driven by AI agents that operate with access to user data.

• a16z is leading a Series A investment in doxxnet.
• doxxnet provides a private, parallel internet infrastructure for users and AI agents.
• doxxnet was founded by Barrett Lyon, who previously founded Prolexic, BitGravity, and Defense.net.

Akamai Announces $11.6 Billion Multi-year Agreement with Anthropic to Support Growing Demand

Akamai today announced a significantly expanded relationship with Anthropic for $11.6 billion of contractual commitment over seven years.

AI companies adopt risky 'take-or-pay' contracts for compute

The AI industry is increasingly relying on take-or-pay contracts to secure computing power, a model borrowed from the energy sector. These agreements require AI companies to pay for GPUs, server time, and other inputs regardless of usage, creating significant financial risks. The payments are backed by expected future revenue, but there are concerns about whether AI revenues will materialize in time to meet payment schedules. Off-balance-sheet commitments are growing, with estimates ranging from $1.65 trillion to $3 trillion. Major players like Anthropic and OpenAI have committed billions, while companies like CoreWeave and Alphabet rely heavily on such contracts. Financial analysts and regulators warn that the entire system could collapse if companies fail to secure enough capital. The Bank of International Settlements has highlighted potential systemic risks, particularly through special purpose vehicles. The article notes that major banks and investors are closely monitoring this trend, with experts predicting a 'wave of disputes' as the sector matures.

• Take-or-pay contracts obligate AI companies to pay for compute regardless of usage, similar to energy sector agreements.
• Anthropic committed $750 billion for compute through 2030; OpenAI could spend over $500 billion in the next 10 years.
• Off-balance-sheet commitments in tech sector estimated at $1.65 trillion to $3 trillion.

AWS Launches 'Built Together' Community Program for Data Centers

Amazon Web Services (AWS) has announced new initiatives to counter criticism over its data center expansion in the U.S., including a $1 billion investment over five years for community programs focusing on education, workforce training, energy efficiency, water conservation, and local infrastructure. Additionally, AWS introduced the 'Amazon Data Center Commitment' with pledges on energy, water, transparency, and employment, and has ceased using non-disclosure agreements (NDAs) with government agencies for new projects. CEO Matt Garman addressed data center 'myths', citing that generators run only about 10 hours per year and that water consumption is 0.5% of industrial use, while highlighting over $1 billion in community contributions in the past three years. These actions come amid over 100 proposed moratoriums on data centers across the U.S.

• AWS invested over $1 billion in communities with data centers over five years.
• AWS stopped using nondisclosure agreements with government agencies for new data centers.
• AWS data center generators run roughly 10 hours per year (99.9% idle).

Vespa.ai Achieves AWS AI Competency

Vespa.ai announced it has achieved the Amazon Web Services (AWS) AI Competency in the AI Software category. This designation recognizes Vespa as an AWS Partner that helps customers build, deploy, and operate large-scale AI applications on AWS. The Vespa AI Search Platform combines hybrid retrieval, advanced ranking, machine learning inference, and real-time serving in a single platform, reducing infrastructure complexity while providing low latency and scalability for production AI. Vespa is trusted by organizations including Perplexity, Spotify, and Yahoo, powering billions of queries and recommendations across industries such as information platforms, digital commerce, media and advertising, and life sciences. The recognition validates Vespa's expertise in building production AI search applications on AWS.

• Vespa.ai achieved the AWS AI Competency in the AI Software category.
• The designation recognizes Vespa as an AWS Partner for building and operating large-scale AI applications on AWS.
• Vespa AI Search Platform combines hybrid retrieval, advanced ranking, ML inference, and real-time serving.

Startup FinOps: Cloud Cost Optimization Playbook

This playbook outlines practical FinOps steps startups can use to reduce cloud spend without major re-architecture. Key recommendations include making spend visible via enforced cost-allocation tags, scheduling non-production environments to sleep, adding caching and CDNs, cleaning up orphaned resources, rightsizing underutilized compute and databases, and buying commitment discounts (Savings Plans / Reserved Instances) for steady-state baseline usage. The guide recommends measuring cost against business units (e.g., cost per user), validating production changes with metrics, and making a lightweight monthly FinOps review a habit. The author cites typical waste at 25–35% of cloud bills and claims many Series A companies can realize 25–40% savings within 90 days by following these practices.

• Industry data cited: idle resources, over-provisioning, and missed commitment discounts account for roughly 25–35% of the average cloud bill.
• Hosting can consume 6–12% of revenue for early-stage companies, making cloud waste a runway risk.
• Practical low-risk actions recommended: schedule non-production environments to sleep, add caching, route static assets via a CDN, and clean up orphaned resources.