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AI Workflows - Page 11
How engineering teams turn AI tools into repeatable work. Curated tldw.news briefings about ai workflows, with practical engineering takeaways from long-form AI and developer-tool videos.
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AI EngineerContext compaction is a trap when caching is cheap
Caching flips the economics of context management. Full history outperforms compaction on cost and accuracy. Teams that compact by default may be wasting money.
Cole MedinWhy your AI coding team is slower than you think—and how to
AI coding without a system leads to a productivity mirage. This workshop shows how to build a shared AI layer (rules, skills, MCP) that makes agents reliable…
IBM TechnologyRAD from 1991 Is the Missing Workflow for AI Coding Agents
RAD's four-phase methodology is back in the age of AI coding. But the real lesson is spec-driven development: prototype fast, but govern production with a…
InfoQAgents aren't magic—they're a security and cognitive liability
AI agents promise productivity but introduce security gaps, cognitive overload, and testing challenges. Bannon explains why governance matters more than…
All About AIYour ML model's 93% win rate is probably just luck. Here's why.
A 14-trade winning streak on Kalshi looks like a machine learning edge. The creator's own analysis shows it's luck. Expected loss after 1,000 windows: $12.
IBM TechnologyFive patterns for agent-tool connections: security grows, complexity follows
A security-minded ranking of five agent-to-tool connection patterns, from direct API calls to vault-backed short-lived credentials. The security gains are…
AI EngineerThe Hidden Cost Trap in AI Agents: When Renting Context Fails
AI search and CaaS promise plug-and-play context, but repeated queries create a cost trap. For stable knowledge work, building custom scrapers may be cheaper.
AI EngineerWhy RL-Trained Agents Fail in the Real World — and How to
RL agents break when real UIs fight back. Amazon AGI shows why flight simulators and harness guardrails are the difference between demo and product.
AI EngineerBrowser agents aren't failing because models are weak. It's an engineering problem.
Browser agents aren't failing because models are bad—they're failing because the engineering around them is immature. Three things matter: multimodal design…
NeuralNineDeepSeek's radical transparency reveals what agent tooling has been missing
DeepSeek's developer preview prioritizes modularity and full traceability, offering a transparent alternative to opaque agent tooling. The design philosophy…
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