HarnessDev: Self-Evolving Agent Frameworks — How LLMs Build Their Own Infrastructure

7 Vulnerability Patterns I Found in AI-Generated Code (and How to Catch Them) If you've...

Nearly three quarters of my small transformer was a lookup table, so the dial that mattered was embedding precision, not network precision. int4 with one scale per row costs 16 KB more than one scale per tensor and recovers 2.2 of the 2.5 …

The most useful shift in AI tooling this year isn't that any single tool got dramatically better —...

Honest comparison of fine-tuning options across Anthropic, OpenAI, and open-weight models. When fine-tuning wins, when RAG wins, and when prompt engineering is enough - from an Anthropic Partner shipping production ML.

Real numbers, real trade-offs. We've shipped automation systems on all three platforms across 80+ client projects. This is the comparison without affiliate bias - pricing math, AI integration, self-hosting, scale, and which tool fits which…

An Anthropic partner who also ships on OpenAI: why the context window stopped mattering, where the bill really comes from, and the three things that decide the choice in production.

AI Agent Tool Mastery: How Modern Agents Choose and Use Tools Effectively The...

On 2026-08-31 our agent announced the same dev.to article on Bluesky twice, from two runs on two...

Procedural Graphs: Self-Evolving Execution Structures for LLM Agents When AI...

PlaidQ: Writing Code in One Step — The Diffusion Model Revolution Duke University...