Topic
AI Infrastructure
Model platforms, cost, latency, and operational trade-offs. Curated tldw.news briefings about ai infrastructure, with practical engineering takeaways from long-form AI and developer-tool videos.
237
breakdowns
Page 1 of 24
Machine Learning Street TalkEnterprise voice agents fail. Here's the fix most teams miss.
Speech recognition is not solved. Mistral's research lead breaks down why enterprise voice agents fail at scale and why customization, not generalization, is…
AI EngineerYour AI agent harness is overengineered. The model got better.
Agents-as-files: Google DeepMind shows how markdown instructions replace Python agent loops. Cursor replaced 12,000 lines of TypeScript with 200 lines. But…
AI EngineerDurable execution is the real agent infrastructure challenge
Giselle van Dongen demonstrates why durable execution infrastructure, not agent SDKs, is the real bottleneck for production agent systems. Concrete failure…
IBM TechnologyGPT-6 solved a Millennium problem—does your team need that?
GPT-6 solved a Millennium math problem with 10,000 agents and massive compute. A security startup used AI to create a WeChat worm. Engineering leaders must…
No Priors: AI, Machine Learning, Tech, & StartupsAI agents need bank accounts and institutional memory, not better models
Coinbase treats every human correction to an AI PR as permanent repository memory. Agent payments and memory loops are becoming operational realities.
AI EngineerACP: The protocol that could finally decouple clients from agent harnesses
ACP standardizes how clients talk to AI agents. Early demos show any client controlling any harness. Adoption is the open question.
AI EngineerAI agents fail without organizational context: the case for context engineering
AI agents are smart but ignorant of your organization's history. Context engineering solves the gap between code that compiles and code that works.
AI EngineerLLM inference is a memory problem, not a compute problem
Inference cost is the hidden operational tax on AI products. This workshop breaks down the KV cache bottleneck, model vs. serving optimisations, and when VLM…
Machine Learning Street TalkAI Governance Is the Real Bottleneck, Not Model Capability
AI isn't just a productivity tool—it's a governance challenge. The 2040 scenario shows why pacing and transparency matter more than raw capability.
InfoQShipping faster is compounding performance debt faster
AI agents are accelerating shipping—and hidden performance debt. OpenAI says the bottleneck isn't just GPUs; it's the entire pre-inference path.
Get TL;DW
Too Long; Didn't Watch.
A concise breakdowns of the AI and devtools videos that actually matter for engineering leaders.
Free. Weekly. No hype.