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AI Workflows - Page 31
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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IBM TechnologySecurity leaders are paralyzed by AI. Here's where to actually start.
Security leaders are paralyzed by AI options. The fix: start with repetitive tasks, keep humans in the loop, and limit agent permissions. Ignore the…
Y CombinatorWhite House AI strategy: open source, preemption, and the science ecosystem shift.
The White House AI strategy doubles down on open source and preemption, but the real signal is the shift in science funding and the push for autonomous labs.
AI EngineerReal-time video avatars are getting cheap—but not yet emotionally smart
Real-time video avatars are nearing cost parity with voice models, but emotional control and orchestration remain hard. LemonSlice's approach uses world…
GOTO ConferencesAI agents: The security disaster teams aren't preparing for
AI agents create a new attack surface through naive trust, unsecured frameworks, and silent security vulnerabilities. Attackers are already exploiting these…
IBM TechnologyThe AI Security Trilemma: Speed, Smarts, Security – Pick Two
AI agents face a trilemma: smart, fast, secure – pick two. Learn how to prioritize and where a security proxy fits.
AI EngineerCode review is dead. Long live intent verification and the AI slop
With 30% of changes merged without review and code churn up 861%, line-by-line review is dead. The future is reviewing intent and evidence, not diffs—but…
AI EngineerWhy Your AI Agents Need a Security Firewall, Not a Prompt Guard
Deno's Claw Patrol intercepts every byte of agent traffic at the protocol level, blocking destructive actions even when agents are prompt-injected. The…
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…
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