Auto-aggregated global tech articles · 853 posts
How can an LLM gain controlled access to current data and permitted actions? Anyone who wants to integrate AI into their own system—or make information held there available to an LLM—quickly encounters that question. MCP provides an open standard for a shared approach across hosts (Model Context Pro
Introduction During my study of Machine Learning, I learned about a method for improving the generalization capability of Neural Networks for image-based datasets called Data Augmentation. Now, I suspected at the time that there existed at least one library in Julia that focused on DA (which turne
OpenAI has announced ChatGPT for Financial Services, a tailored ChatGPT Work experience that the company says combines built-in financial data with the reasoning capabilities of GPT-6 Astra. The stated focus is practical financial work: teams can use it to develop research, build financial models an
You can now manage GitHub code scanning’s AI Scan for pull request enablement with REST API endpoints at the organization and repository levels. This public preview gives teams a programmatic… The post AI Scan for pull request APIs in public preview appeared first on The GitHub Blog.
I tested DeepSeek Harness for a week. I left with a shipped plugin and $0 in API costs I came to DeepSeek Harness as a reviewer and left as one of its plugin authors, which is a fair measure of how the week went. The hook is on the repo's first line: "Everything is a plugin." Not the usual market
This article provides a step by step deployment guide for Gemma 4 E2B's quantization-aware-trained (QAT) checkpoint to a local, laptop hosted GPU enabled system — a much older Lenovo Yoga 9, on sale since January 2021, with a 4 GB GTX 1650 Ti. A suite of Python MCP tools is built to simplify managem
A retold log is a filtered log. The agent should query the database, read the broker, hit the endpoint itself — and record what it saw. There is a moment in almost every debugging session with an AI agent where the developer stops being a developer and becomes a clipboard. The agent asks for the er
it first started five projects ago when a client was asking ai for everything along with me. like 50% 50%. she had no idea about websites but via the ai she was putting a lot of pressure to fix things I would never fix in the past. now, today a client build an entire eShop in two weeks way better th
Most LLM-driven automation fails at arithmetic because language models are probabilistic engines being asked to perform deterministic tasks. If you ask an agent to 'fairly split a bill,' it will hallucinate a division strategy that looks reasonable but lacks mathematical rigor. To build useful auton
Traditional SHAP explanations reveal why a transaction looks risky but fail to capture the autonomous decisions and tool calls of agentic AI fraud systems. By integrating action‑level tracing, Explain‑Then‑Act patterns, and human‑in‑the‑loop summaries, organizations can close the explainability gap,
Originally published on tamiz.pro. The Demo Promise You've just shipped your first AI‑enabled feature. In the demo environment, everything works flawlessly: the model returns accurate predictions, latency is sub‑200 ms, and the user interface feels instant. Stakeholders are impressed, an
Nobody wants to buy tokens. They want useful work, and eventually, AI will be priced that way too. Every new technology seems to begin by billing us for the thing engineers can measure most easily. Electricity gave us kilowatt-hours. Telecommunications gave us minutes. Cloud computing gave us CP
Reducing LLM latency is one of the most critical challenges for engineers building responsive AI applications. While Large Language Models (LLMs) keep growing in capability, their token-by-token generation can create frustrating bottlenecks for end users, and long wait times lead directly to lower e
Originally published at tddbuddy.com. Related reading: Test Deletion Is a Privileged Operation treats the diff as a workflow surface for tests; this post applies the same discipline to TODOs. Tamper-Resistant Test Design Is What the Suite Now Owes the Codebase named separation of authorship as a de
The AI SDK harness layer now supports GitHub Copilot through the official @ai-sdk/harness-github-copilot adapter. The harness layer lets your application run different coding agents through the same HarnessAgent interface, so you can switch agents without changing your application code.Pass githubCo
This first ran on deanlee.info. Greg Brockman called Astra AGI on launch day. The U.S. look-over was a voluntary 30-day window with no license attached. On September 3, OpenAI released GPT-6 Astra and Greg Brockman told reporters that artificial general intelligence had arrived. The Washington Post
Every single full documentation rebuild ruthlessly executed doxygen.exe and parsed its massive XML output. The tool simply didn't care if you fixed a single typo in the comments or rewrote half the SDK. On real projects this translated into minutes of agonizing waiting after every push, even though
The most expensive mistake in AI-assisted QA isn't a bad test. It's not knowing why you wrote it. Every week I watch engineers open ChatGPT, paste a user story, and type "write test cases for this." Ten seconds later they have 40 lines of confident-looking test code. Nobody asked what actually need
A multi-agent Claude Code "company" ran for thirty days. It shipped nine products and over 280 posts. It earned zero dollars. The post-mortem is one of the bluntest things I have read from someone running agents at scale: "9 products built. 280+ posts. Full pipeline. $0 revenue. Multi-agent syste
We have deprecated MAI-Code-1-Flash across all GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions) today, September 10, 2026. Model Deprecation date Suggested alternative… The post MAI-Code-1-Flash deprecated appeared first on The GitHub Blog.
301–320 / 853
