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Too few tokens, too many spare quotas I do most of my development on a Claude Code subscription. Right now Claude Fable 5.1 and Opus 5.5 work extremely well, and I would simply call them the state of the art. The only problem is that I keep running out of tokens.
Every team evaluating Model Context Protocol (MCP) servers reaches the same question: do we hand-maintain a second description of our API for agents, or do we generate it from the contract we already have? If you keep an OpenAPI document, the second answer is the sane one.
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Two documents appeared on 8 September. An arXiv paper measures what happens when a coding agent reads a poisoned repository under four permission models.
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In Part 3, I introduced the optional AI layer in AdaptTable v3. This article goes deeper into how to connect it, how an agent discovers the table’s capabilities, how context is selected, and how an application can extend that capability set without building a separate AI tool layer for the table.
Day 3 of 30 Days of Search. A research task does not always end with a report. Your app might need JSON. An analyst might need an Excel workbook. A team meeting might need slides. Searching is very common and popular.
Your agent just told you it sent the proposal. The tool call came back with an id, the trace shows a clean green step, and the customer never got the email. That gap is small and quiet, and it is the thing underneath a loud week.
Apple says it will add controls around macOS Full Disk Access because increasingly capable AI agents make broad access to personal data riskier. The announcement comes during a dispute about Meta Muse reading a user's private messages.
A candidate-scoring pipeline should treat transcription as a discovered dependency, not as a feature implied by an OpenAI-compatible base URL. Check the capability manifest before accepting audio, keep separate eligibility decisions for US and EU deployments, and route to an approved speech…
Almost every modern language model looks impressive on a two-step demo. You ask it to check a database or summarize a document, it calls the right tool, formats the answer, and looks like an autonomous engineer.
I Built StudyBuddy AI for a Friend Who Was Tired of Turning Notes Into Study Material 📚🤖 Hacktoberfest Weekend Challenge: Build for a Friend Submission 🤝 Jainil Chavda Jainil Chavda Jainil Chavda Follow Oct 3 I Built StudyBuddy AI for a Friend Who Was Tired of Turning Notes Into Study Material…
La consolidación de motores de respuesta como ChatGPT Search, Google Gemini (AI Overviews), Perplexity Pro y Claude ha transformado de forma irreversible el proceso de búsqueda y compra B2B en España.
I Built StudyBuddy AI for a Friend Who Was Tired of Turning Notes Into Study Material 📚🤖 This is my submission for the Hacktoberfest 2026 Weekend Challenge: Build for a Friend. Build something with open-source AI at its core.
Apparently knowing the entire codebase isn’t the same as knowing what actually happened. Coding agents have reached a slightly ridiculous level. I can point one at a repo and say: add rate limiting to this endpoint and it will happily wander through files I forgot existed, figure out how everything…
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A hackathon portal can collect projects, assign judges, and publish scores. But there is a harder question hiding underneath all of that: When the results are announced, can anyone understand how they were reached—and verify that they haven’t quietly changed?
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