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Building a Deep Research Agent Using MCP-Agent

Documenting my journey building a general-purpose deep research agent powered by MCP, and sharing the valuable (and sometimes painful) lessons learned along the way. Background My name is Sarmad Qadri and I'm the creator of the open source project, mcp-agent. My philosophy for agent development in 2025 can be summarized as – MCP is all you need. Or more verbosely: Connect state-of-the-art LLMs to MCP servers, and leverage simple design patterns to let them make tool calls, gather context and m

Logging in Go with Slog: A Practitioner's Guide

Logging in Go has come a long way. For years, the community relied on the simple standard log Copy package or turned to powerful third-party libraries like zap and zerolog . With the introduction of log/slog in Go 1.21 , the language now has a native, high-performance, structured logging solution designed to be the new standard. slog Copy isn’t just another logger; it’s a new foundation that provides a common API (the frontend) that separates logging logic from the final output, which is contr

DeepCodeBench: Real-World Codebase Understanding by Q&A Benchmarking

At Qodo, we’ve created a new benchmark dataset of real-world questions derived from large, complex code repositories. We are excited to release the dataset, methodology, and prompts used in its creation to support further research and development. Motivation Enterprises often maintain massive codebases that are difficult for any individual developer to navigate and fully understand. Whether onboarding, doing routine development, or using AI-assisted workflows, teams often have questions about

Nvidia unveils new GPU designed for long-context inference

In Brief At the AI Infrastructure Summit on Tuesday, Nvidia announced a new GPU called the Rubin CPX, designed for context windows larger than 1 million tokens. Part of the chip giant’s forthcoming Rubin series, the CPX is optimized for processing large sequences of context and is meant to be used as part of a broader “disaggregated inference” infrastructure approach. For users, the result will be better performance on long-context tasks like video generation or software development. Nvidia’s

Sharing a mutable reference between Rust and Python

As part of my ongoing project to reimplement Django’s templating language in Rust, I have been adding support for custom template tags. The simplest custom tag will look something like: # time_tags.py from datetime import datetime from django import template register = template . Library() @register.simple_tag def time (format_string): now = datetime . now() return now . strftime(format_string) # time_tags.py from datetime import datetime from django import template register = template . Libr

A staff engineer's journey with Claude Code

Until 18 months ago, I wrote every line of code myself. Today, AI writes 80% of my initial implementations while I focus on architecture, review, and steering multiple development threads simultaneously. This isn't another "AI will change everything" post. This is about the messy reality of integrating AI into production development workflows: what actually works, what wastes your time, and why treating AI like a "junior developer who doesn't learn" became my mental model for success. The back

First attempt will be 95% garbage: 6 weeks with Claude Code

Until 18 months ago, I wrote every line of code myself. Today, AI writes 80% of my initial implementations while I focus on architecture, review, and steering multiple development threads simultaneously. This isn't another "AI will change everything" post. This is about the messy reality of integrating AI into production development workflows: what actually works, what wastes your time, and why treating AI like a "junior developer who doesn't learn" became my mental model for success. The back

Using JWT to establish a trusted context for Row Level Security

Row-level security (RLS) is a great feature. It allows restricting access to rows by applying filters defined by a policy. It’s a tool useful for cases when the data set can’t be split into separate databases. Sadly, using RLS may be quite cumbersome. RLS requires some sort of “trusted context” for the RLS policies. The policies need to filter using data the user can’t change. If the filter uses some sort of “tenant ID”, and the user can change it to an arbitrary value, that would break the RLS

Don't Build Multi-Agents

Principles of Context Engineering We’ll work our way up to the following principles: Share context Actions carry implicit decisions Why think about principles? HTML was introduced in 1993. In 2013, Facebook released React to the world. It is now 2025 and React (and its descendants) dominates the way developers build sites and apps. Why? Because React is not just a scaffold for writing code. It is a philosophy. By using React, you embrace building applications with a pattern of reactivity and

Lessons from building an AI data analyst

AI/ML Data Analytics Malloy Malloy TL;DR Text-to-SQL is not enough. Answering real user questions requires going the extra mile like multi-step plans, external tools (coding) and external context. Answering real user questions requires going the extra mile like multi-step plans, external tools (coding) and external context. Context is the product. A semantic layer (we use Malloy ⎋) encodes business meaning and sharply reduces SQL complexity. A semantic layer (we use Malloy ⎋) encodes busines

From multi-head to latent attention: The evolution of attention mechanisms

From Multi-Head to Latent Attention: The Evolution of Attention Mechanisms Vinithavn 7 min read · 15 hours ago 15 hours ago -- Listen Share Press enter or click to view image in full size What is attention? In any autoregressive model, the prediction of the future tokens is based on some preceding context. However, not all the tokens within this context equally contribute to the prediction, because some tokens might be more relevant than others. The attention mechanism addresses this by allow

From Multi-Head to Latent Attention: The Evolution of Attention Mechanisms

From Multi-Head to Latent Attention: The Evolution of Attention Mechanisms Vinithavn 7 min read · 15 hours ago 15 hours ago -- Listen Share Press enter or click to view image in full size What is attention? In any autoregressive model, the prediction of the future tokens is based on some preceding context. However, not all the tokens within this context equally contribute to the prediction, because some tokens might be more relevant than others. The attention mechanism addresses this by allow

Show HN: Magic links – Get video and dev logs without installing anything

Hey HN, For a while now, our team has been trying to solve a common problem: getting all the context needed to debug a bug report without the endless back-and-forth. It’s hard to fix what you can't see, and console logs, network requests, and other dev data are usually missing from bug reports. We’ve been working on a new tool called Recording Links. The idea is simple: you send a link to a user or teammate, and when they record their screen to show an issue, the link automatically captures a

LLMs solving problems OCR+NLP couldn't

The first idea resembling something like the idea of OCR got developed in 1870 as a reading machine for the blind - the Optophone. This was the first step to solve a problem that sounds pretty simple: How do we get writing on paper inside a computer? 150 years of research, engineering breakthroughs and hundreds of IDP products later we were finally able to scan a receipt and have the fields be filled out - if it looked nice and friendly enough to the OCR model. Heureka. Unfortunately for Tesse

DeepWiki: Understand Any Codebase

Welcome to another post in the AI Coding Series, where I'll share the strategies and insights I've developed for effective AI-assisted coding. In this post, I break down how I use DeepWiki - my go-to tool for understanding unfamiliar codebases, spinning up dev environments, and generating context for coding agents like Claude and Cursor. Whether you're evaluating an open-source repo, onboarding to a new project, or building an AI-powered dev tool, DeepWiki can save you hours. Note: This is not

Launch HN: April (YC S25) – Voice AI to manage your email and calendar

Hi HN, we’re Neha and Akash from April ( https://tryapril.com ). We are building an AI executive assistant to help you get through emails and manage your schedule, hands-free while you drive to work, or whenever else you prefer voice interaction. Here's a demo: https://www.youtube.com/watch?v=ISKwEyuQQEo#t=50 ...and here's a second one showing more complex use cases: https://www.youtube.com/watch?v=P8APprJ3-eY. While driving 40 mins daily from SF to Berkeley, my inbox would flood to 30+ email

Show HN: CasCache – multi-generational cache with optimistic concurrency control

cascache Provider-agnostic CAS like (Compare-And-Set or generation-guarded conditional set) cache with pluggable codecs and a pluggable generation store. Safe single-key reads (no stale values), optional bulk caching with read-side validation, and an opt‑in distributed mode for multi-replica deployments. Contents Overview CAS safety: Writers snapshot a per-key generation before the DB read. Cache writes commit only if the generation is unchanged. Writers snapshot a per-key before the DB rea

Developers lose focus 1,200 times a day — how MCP could change that

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Software developers spend most of their time not writing code; recent industry research found that actual coding accounts for as little as 16% of developers’ working hours, with the rest consumed by operational and supportive tasks. As engineering teams are pressured to “do more with less” and CEOs are bragging about how much of their codeb

How to Fix Your Context

Mitigating & Avoiding Context Failures Following up on our earlier post, “How Long Contexts Fail”, let’s run through the ways we can mitigate or avoid these failures entirely. But before we do, let’s briefly recap some of the ways long contexts can fail: Context Poisoning: When a hallucination or other error makes it into the context, where it is repeatedly referenced. When a hallucination or other error makes it into the context, where it is repeatedly referenced. Context Distraction: When

My tips for using LLM agents to create software

This post details my experiences creating software with LLM coding agents, emphasizing that what you do with AI agents is ‘creation’, not just 'coding,' and sharing what worked for me. This is not 'The One True Path To AI Success.' tl;dr: I’m not a professional developer, just a hobbyist with aspirations I wanted to accomplish a coding project beyond my skill level and have been experimenting with agentic coding tools for several months (spoiler: mostly success) You should use Anthropic’

Do Large Language Models Dream of AI Agents?

During sleep, the human brain sorts through different memories, consolidating important ones while discarding those that don’t matter. What if AI could do the same? Bilt, a company that offers local shopping and restaurant deals to renters, recently deployed several million agents with the hopes of doing just that. Bilt uses technology from a startup called Letta that allows agents to learn from previous conversations and share memories with one another. Using a process called “sleeptime compu

Fast and observable background job processing for .NET

BusyBee 🐝💨 Fast and observable background job processing for .NET BusyBee is a high-performance .NET background processing library built on native channels. It provides a simple, configurable, and observable solution for handling background tasks with built-in OpenTelemetry support and flexible queue management. Installation dotnet add package BusyBee Quick Start Register BusyBee in your DI container and start processing background jobs: // Program.cs builder . Services . AddBusyBee ( ) ;

Fun with Finite State Transducers

ENOSUCHBLOG Programming, philosophy, pedaling. Aug 14, 2025 Tags: devblog, programming, rust, zizmor I recently solved an interesting problem inside zizmor with a type of state machine/automaton I hadn’t used before: a finite state transducer (FST). This is just a quick write-up of the problem and how I solved it. It doesn’t go particularly deep into the data structures themselves. For more information on FSTs themselves, I strongly recommend burntsushi’s article on transducers (which is wha

Teaching the model: Designing LLM feedback loops that get smarter over time

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Large language models (LLMs) have dazzled with their ability to reason, generate and automate, but what separates a compelling demo from a lasting product isn’t just the model’s initial performance. It’s how well the system learns from real users. Feedback loops are the missing layer in most AI deployments. As LLMs are integrated into ever

Model intelligence is no longer the constraint for automation

The perception is that model improvement seems to be stagnating. GPT-5 wasn’t the step change that people were expecting. Yet, models continue to improve on reasoning benchmarks. Recently, both OpenAI and Google models were on par with gold medallists in the International Mathematical Olympiad 2025 (IMO). At the same time it’s still difficult to make AI agents work for relatively simple enterprise use cases. Why is there such a disparity in model performance between problem domains? Why are mode

Launch HN: Embedder (YC S25) – Claude code for embedded software

Hey HN - We’re Bob and Ethan from Embedder ( https://embedder.dev ), a hardware-aware AI coding agent that can write firmware and test it on physical hardware. Here’s a demo in which we integrate a magnetometer for the Pebble 2 smartwatch: https://www.youtube.com/watch?v=WOpAfeiFQkQ We were frustrated by the gap between coding agents and the realities of writing firmware. We'd ask Cursor to, say, write an I2C driver for a new sensor on an STM32, and it would confidently spit out code that used

Launch HN: Embedder (YC S25) – Claude Code for Embedded Software

Hey HN - We’re Bob and Ethan from Embedder ( https://embedder.dev ), a hardware-aware AI coding agent that can write firmware and test it on physical hardware. Here’s a demo in which we integrate a magnetometer for the Pebble 2 smartwatch: https://www.youtube.com/watch?v=WOpAfeiFQkQ We were frustrated by the gap between coding agents and the realities of writing firmware. We'd ask Cursor to, say, write an I2C driver for a new sensor on an STM32, and it would confidently spit out code that used

Google Gemini will now learn from your chats—unless you tell it not to

As Gemini is increasingly woven into the fabric of Google, the way the chatbot accesses and interacts with your data is in a constant state of flux. Today, Google is announcing several big changes to how its AI adapts to you, giving it the ability to remember more details about your chats for improved answers. If that's a concern, Google also has a new temporary chat option that won't affect the way Gemini thinks about you. You might recall several months back when Google added a "personalizati

Claude gets 1M tokens support via API to take on Gemini 2.5 Pro

Claude Sonnet 4 has been upgraded, and it can now remember up to 1 million tokens of context, but only when it's used via API. This could change in the future. This is 5x more than the previous limit. It also means that Claude now supports remembering over 75,000 lines of code, or even hundreds of documents in a single session. Previously, you were required to submit details to Claude in small chunks, but that also meant Claude would forget the context as it hit the limit. With up to a 1 milli

Claude Sonnet 4 now supports 1M tokens of context

Claude Sonnet 4 now supports up to 1 million tokens of context on the Anthropic API—a 5x increase that lets you process entire codebases with over 75,000 lines of code or dozens of research papers in a single request. Long context support for Sonnet 4 is now in public beta on the Anthropic API and in Amazon Bedrock, with Google Cloud’s Vertex AI coming soon. Longer context, more use cases With longer context, developers can run more comprehensive and data-intensive use cases with Claude, incl