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253 writings found
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The Permission Hungry Dilemma: When AI Agents Want Access to Everything
ThoughtWorks Radar 34 highlights a fundamental tension: the most useful AI agents need broad access, but our security guardrails haven't caught up yet.
GitHub Copilot's Limits Crisis: When AI Agents Outgrow Their Infrastructure
GitHub just paused new Copilot signups and tightened usage limits. The reason? Agentic workflows are consuming resources faster than their pricing model can handle.
Epic's AI NPCs in Fortnite: When Your Quest Giver Can Go Off-Script
Epic Games lets developers create AI-powered Fortnite characters with conversation capabilities. But there are some very specific rules about what they can't be.
Meta's AI Agents Are Now Fixing Their Own Performance Problems
How Meta built a unified AI platform that automates finding and fixing performance issues, recovering hundreds of megawatts without scaling headcount.
The Memory Crisis Nobody's Talking About: Why Your Next Device Will Cost More
Memory makers will only meet 60% of demand by 2027. AI's hunger for HBM is starving consumer electronics of DRAM, and we're all going to pay for it.
Claude's System Prompt Evolution: What Opus 4.7 Tells Us About AI Behavior Design
Anthropic's latest system prompt reveals a shift toward proactive AI behavior. I dig into what these changes mean for developers building with Claude.
Building an Emoji List Generator Live: What GitHub's Rubber Duck Thursday Taught Me About AI-Powered Development
A live coding session reveals how GitHub Copilot CLI and multi-model AI workflows are changing how we build small tools. Here's what actually happened.
PyCon US 2026: Why This Matters for Python and AI Engineering
PyCon returns to California with new AI and security tracks. What this shift means for the Python community and the future of technical conferences.
When Benchmarks Break: A Laptop Model Drew Better Pelicans Than Claude Opus
A quantized 21GB model running locally outperformed Anthropic's flagship on SVG generation. What this tells us about AI benchmarks and model comparison.
GitHub's eBPF Solution to the Circular Dependency Problem You Didn't Know You Had
How GitHub uses eBPF to detect circular dependencies in deployment scripts, preventing catastrophic incidents when systems depend on themselves to recover.
When Benchmark Performance Stops Meaning What We Think It Means
A quantized local model outdraws Claude Opus 4.7 at pelicans on bicycles. What does that tell us about AI benchmarks? Probably nothing good.
Building a Personal Command Center in a Day: What AI-Assisted Development Actually Looks Like
A GitHub engineer built a productivity tool in one day using AI agents. Here's what that workflow reveals about the future of software development.
The Virtue of Laziness: Why AI Threatens What Makes Us Good Engineers
LLMs lack the programmer's essential virtue of laziness. Without constraints, they generate complexity instead of elegant abstractions.
Meta's Muse Spark: A Tooled-Up Return to Frontier Models
Meta launches Muse Spark with 16 built-in tools, visual grounding, and Code Interpreter. But where's the open source promise?
Meta's Muse Spark: They're Back in the Frontier Game (And the Tools Are Wild)
Meta drops Muse Spark with 16 powerful tools including visual grounding, Python sandbox, and Meta content search. Are they back in the race?