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Anup (auto-discovered)

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08:07
2026-10-01
anup.io
artificial-intelligence

What is Jev? A Simple Primer on AI That Makes Decisions

Former OpenAI researcher Diogo Almeida has released Jev, an AI model built to return small, structured judgments with attached probabilities rather than open-ended generated text, according to TypeSaf…

12:37
2026-09-15
anup.io
ai-agents

Defining an AI Agent

Anthropic, OpenAI, and LangChain each offer distinct definitions of an AI agent, with Anthropic describing agents as "systems where LLMs dynamically direct their own processes and tool usage, maintain…

09:56
2026-09-08
anup.io
machine-learning

TIL: What’s actually different about GGUF and ONNX?

A technical comparison explains that GGUF stores model weights and metadata for llama.cpp, which implements the architecture itself, while ONNX stores a computation graph that any compatible runtime c…

16:24
2026-08-28
anup.io
ai-tools

How I code with Claude Code

Anthropic's Claude Code has been used by a developer for over a year, and they have developed a workflow that emphasizes planning and red-teaming before implementation. The workflow involves using the…

07:59
2026-08-10
anup.io
artificial-intelligence

One agent or many?

A new analysis from AI engineering research outlines the architectural trade-off between Single-Agent Systems (SAS) and Multi-Agent Systems (MAS), recommending that engineers choose based on task cont…

05:02
2026-08-05
anup.io
artificial-intelligence

From Prompt Engineering to Loop Engineering

Addy Osmani introduced the term 'loop engineering' in June 2026, describing a new layer of AI system design where the system itself decides when to stop, retry, or escalate a task, moving the final co…

18:26
2026-06-24
anup.io
ai-agents

Who Still Understands the Code?

A senior software engineer warns that AI coding agents, while boosting productivity, erode developers' understanding of their own codebases by breaking the feedback loop between writing and comprehens…

16:59
2026-06-21
anup.io
ai-agents

Designing Teams for an Agentic World

Software organizations are being urged to redesign their teams for an agentic world where coding agents shift scarcity from building to orchestration. Leaders are adopting AI tools quickly but failing…

07:49
2026-06-03
anup.io
artificial-intelligence

The Frontier of Agent Memory: From Recall to Experience

Anup explores the next frontier of agent memory, moving beyond simple recall to systems that can reflect, consolidate, and learn from past interactions. The post argues that durable agent memory requi…

08:47
2026-06-02
anup.io
large-language-models

Speculative Decoding

Speculative decoding accelerates large language model inference by using a small draft model to propose multiple tokens, which a large target model then verifies in a single forward pass, reducing the…

05:36
2026-06-01
anup.io
large-language-models

Query, Key, Values

The transformer attention mechanism uses three learned projections—Query, Key, and Value—to enable each token to selectively gather information from other tokens. The Query determines what the token i…

09:38
2026-05-31
anup.io
artificial-intelligence

How Modern Agent Memory Architectures Work

Modern agent memory architectures move beyond simple context windows by extracting facts, preserving episodes, building semantic structure, and retrieving through multiple signals. The design choices—…

05:42
2026-05-29
anup.io
ai-agents

Why Context Is Not Enough

A new analysis argues that current AI agent systems fail to achieve true memory because they rely on temporary context windows and retrieval rather than durable memory architectures. The piece identif…