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AI Workflows - Page 9
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 TechnologyThe Model Wars Are Over—Customization Is the New Moat
Inkling’s open-weight fine-tuning platform vs. Muse Spark’s agent focus: The model race is no longer about benchmarks but who gives teams the most control.
Theo - t3․ggKimi K3: Open-Weight Frontier with Hidden Tradeoffs
Kimi K3 is the first open-weight model to reach frontier performance, but its massive scale and security gaps raise hard questions for engineering leaders.
AI EngineerAI Leverage Is in Org Charts, Not Model Choice
Garry Tan: AI leverage is org design—skill files as employees, resolver tables as org charts—not model choice. Revenue per head records broken.
AI EngineerExecution Is Cheap—Your Eval Design Will Make or Break Success
An AI agent won a coding competition by executing human ideas, signaling execution is automated. High-leverage work shifts to evaluation design, architecture.
Latent SpaceWhy the Next AI Scaling Axis Might Be a Wet Lab
Lila Sciences treats automated labs as verifiers, turning physical experiments into a scaling axis by generating tokens for generalist AI.
Theo - t3․ggYour Model Is Fine, Your System Prompt Is Sabotaging You
Codex’s hidden system prompt mandates specific border radii and bans empty states, wasting tokens and producing generic output. Fix the harness, not the model.
AI EngineerBetter Agent Tooling Can’t Hide Near‑Zero Success on Real Tasks
Background computer‑use agents gain a cross‑platform driver that lifts success rates, but new benchmarks expose a gap on real‑world tasks.
AI EngineerCursor’s Model Flywheel: From Fine-Tuning to Full Pre-Training and Recursive Improvement
Cursor’s shift to full pre-training and recursive model improvement turns agent feedback into a self-reinforcing data flywheel—a new moat for AI coding tools.
The Pragmatic EngineerDark AI Factories Break: Context Engineering and Slow Loops Work
Dex Horthy explains why his lights-off coding factory failed and how context engineering plus incremental loops are the pragmatic path to reliable AI code.
AI EngineerSoftware engineering is becoming a product taste job
Anthropic’s agents now land 65% of product PRs, shifting engineering to product thinking and raising the bar for automated code review.
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