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CompaniesSep 22, 2026

Andreessen Horowitz building an AI academy turns talent into infrastructure

The Verge's report on Andreessen Horowitz's AI academy is less about one training program and more about where the bottleneck has moved. Capital is abundant in AI, but teams still need people who understand models, products, evals, distribution, and company-building at the same time.

AI in PracticeSep 15, 2026

AI adoption inside audit firms is becoming a trust test

Audit is one of the worst places to treat AI as a casual productivity trick. Financial Times reporting on rapid AI adoption by major audit firms shows why professional services are excited, but also why the stakes are high.

FundingSep 15, 2026

The AI slowdown debate is becoming an investor stress test

The AI slowdown debate has a financial side that is easy to miss. Financial Times analysis argues that slowing frontier development could change the flow of capital into chips, data centers, cloud deals, and lab valuations.

Developer ToolsSep 11, 2026

OpenAI is productizing the infrastructure behind agents

OpenAI's Agents API matters because it packages more than a model endpoint. By exposing infrastructure behind agent sessions, orchestration, tool use, and recovery, OpenAI is trying to make agent development feel less like a custom research project and more like a platform primitive.

InfrastructureSep 8, 2026

AI labs are learning that credit ratings may matter as much as model ratings

The AI buildout is moving from venture story to balance-sheet story. Financial Times reporting on investment-grade financing shows that frontier labs and infrastructure providers are now chasing cheaper capital because compute commitments are too large to fund like ordinary software growth.

InfrastructureSep 4, 2026

Crusoe’s reported funding shows AI infrastructure money is still accelerating

AI infrastructure is still pulling capital at a scale that looks disconnected from the rest of the economy. Crusoe’s reported raise is another signal that investors believe the bottleneck for AI is physical: power, land, chips, cooling, and the ability to turn all of that into usable capacity.

InfrastructureSep 4, 2026

Anthropic’s Lambda deal shows Claude is becoming a compute-planning problem

Claude’s future is being negotiated in data-center contracts as much as in model research. Anthropic’s reported Lambda deal shows how quickly a successful assistant becomes a capacity-planning challenge: every new enterprise seat, coding workflow, and API customer needs compute behind it.

ResearchAug 31, 2026

Post-training is starting to look like maintenance work, not magic

A useful AI research signal this week is the move to describe LLM post-training as industrial maintenance. That framing is important because many model improvements depend less on mystery and more on cleaning, shaping, measuring, and repairing the data systems around the model.

ResearchAug 27, 2026

Anthropic's lab agent moves AI from screens into experiments

AI agents have mostly been judged by what they can do on a screen: browse, code, write, click, and call APIs. Anthropic's reported lab-agent work moves the question into rooms with instruments, materials, protocols, and experiments that can fail in expensive ways.

InfrastructureAug 26, 2026

NVIDIA earnings keep AI infrastructure at the center of the market

NVIDIA's latest numbers make the AI boom look less like a software story and more like an infrastructure race measured in chips, power, and capital commitments. The company is still turning model demand into data-center demand, and every forecast now becomes a readout on how much compute the industry believes it can absorb.

AI in PracticeAug 24, 2026

Thomson Reuters chooses owned AI over rented frontier models

Thomson Reuters is a useful enterprise signal because its business depends on trusted information. If a company like that leans toward owning more of its AI capability, it suggests some workloads may be too sensitive, specialized, or valuable to leave entirely to rented APIs.