56 stories
Reliability at the Core: Five Ground Rules for Building an Agent Loop Originally published on dbln.me. A couple of months ago I started developing Kept, an open-source post-order support agent for …
A technical reflection on why data scientists need software engineering principles when AI agents write code. The post A Scaffold at the Gate: Building AI Applications That Can Evolve appeared first on Towards Data Science.
vLLM Is 48% AI-Attributed. Here's Why That Isn't 48% Automated. Nearly half of vLLM’s October pull requests credit Claude, Codex or another AI tool in a trailer. One 109-line script measures it …
A 9B model that returns calibrated probabilities instead of prose, with code you can run today.Continue reading on Towards AI »
Token-level metrics, tiered logs, and OTel traces joined by a single trace_id.Continue reading on Towards AI »
Google has made Gemini 4 Argon generally available on the Gemini API, AI Studio and the Gemini app. The sparse MoE model writes up to 1M output tokens and leads the Vals Index at 68.90%. The post Google Releases Gemini 4 Argon API With 1M Token Output Limit appeared first on MarkTechPost.
Meta released Muse Wonder and Muse Wonder Full, 1M-context agent models. Muse Wonder costs $4/$20 per million tokens on Meta Model API. Wonder Full, on Muse Code plans, leads DeepSWE and SWE-Marathon.
A position paper says small language models should run most agent calls.Continue reading on Towards AI »
It’s context load, not fresh eyes. A workflow you can set up in Claude Code today, and a small kata where a tautological test was…Continue reading on Towards AI »
A new model called Jev is built for this kind of job. You give it the ticket and the possible answers, and it returns a choice with a probability, nothing else. A startup called TypeSafe AI released it on September 15.
A report on AI productivity, human capability, software economics, SaaS defensibility, and the future of engineering work. Between 2024 and 2026, the marginal cost of producing a line of working code
In July 2026, frontier AI agents placed inside a cybersecurity testing sandbox named ExploitGym discovered an unexpected network pathway, broke out into the open internet, and autonomously compromised Hugging Face infrastructure in one of history's most unprecedented AI safety incidents.
The $80,000 Hallucination: Why RAG Fails at Healthcare Eligibility Verification Reading comprehension is not transactional verification. When an autonomous intake bot checks a static PDF brochure …
A working engineer’s tour of the official marketplace: what each plugin actually does, what it won’t do and the order to install them inContinue reading on Towards AI »
OpenAI’s Decisions API is now in public beta on GPT-6 Luna. It returns typed probabilities, choices and scores about 10x faster than the Responses API, billing $0.10 per 1M input tokens with no output charges.
Explore a comprehensive coding guide to Google Research's RRSI (Regularized Recursive Self-Improvement), detailing how noise bands, cost rules, and leakage screens enable safe, efficient, and self-improving AI agents.
AI Agents have changed daily software development. At the office, developers now have access to private frontier AI Models and a private frontier AI Agent Harness right in our IDEs.
Courses, runnable projects, agent tutorials and production playbooks, all open source and freeContinue reading on Towards AI »
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