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Coding Agents - Page 9
Practical shifts in agentic coding, review, and delivery. Curated tldw.news briefings about coding agents, with practical engineering takeaways from long-form AI and developer-tool videos.
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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.
Latent SpaceAgent harnesses need three layers: executive, harness, sandbox
Self-improving agents require separating policy from state. Exo's three-layer architecture enables safe recursive self-improvement while protecting secrets…
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.
IBM TechnologyIBM and Meta show open AI's industrial and on-device future is real.
IBM partners for B300 GPU clusters, Meta releases an on-device model that outperforms expectations, and OpenAI teases a model it won't release. The real…
AI EngineerYour Agent Improvement Strategy Is Incomplete Without Trace Mining
LangChain's research lead argues that agent improvement is a data mining problem. Trace data—tool calls, outputs, errors—is the signal for continuous…
AI EngineerHow to improve coding agents without golden answers or regression
Continual learning for coding agents doesn't need golden answers. Applied Compute's distillation spectrum shows offline traces plus targeted hints improve…
IBM TechnologyForget Prompt Engineering: Context Engineering Is Where Agents Live or Die
Context engineering—not prompt engineering—is the skill that separates prototype agents from production-ready systems. Learn why more context hurts…
Theo - t3․ggStop Blaming Models: Your Agent Prompts Are the Real Bottleneck
One engineer's deep dive into optimizing AI agent behavior through prompt engineering, not model upgrades. The secret: invest in failure analysis and…
InfoQCoding agents are making comprehension the new bottleneck for engineering teams.
Coding agents remove the gatekeeping around code production, but create a new bottleneck: comprehension. The speaker argues that the future belongs to…
AI EngineerWhy your coding agents fail in teams and how to fix it
Coding agents work for individuals but break in teams. The fix isn't better models or prompts—it's organizational investment in shared agent infrastructure.
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