Search: “coding-agents”

arXiv:2604.12301v1 Announce Type: cross Abstract: We present a systematic measurement study of seven tactics for reducing cloud LLM token usage when a small local model can act as a triage layer in fr

LlamaIndex have a most excellent open source project called LiteParse, which provides a Node.js CLI tool for extracting text from PDFs. I got a version of LiteParse working entirely in the browser, us

arXiv:2605.01567v1 Announce Type: cross Abstract: Large language model (LLM) coding agents increasingly operate over repositories, terminals, tests, and execution traces across long software-engineeri

Built an open-source AI coding agent that was 7%–75% cheaper than a cold 'claude -p' run on 6/6 well-localized tasks across repositories up to ~82k LOC. The biggest difference: Cold agent: 6.83, 207 t

arXiv:2608.29675v1 Announce Type: cross Abstract: Repository exploration is a distinct and costly stage of coding-agent pipelines: before generating a patch, an agent must identify which repository fi

Retrieval benchmarks sometimes feel benchmaxxed by models, so we wanted to find a way to tie it as close as possible to my objective: finding the article that answers a product question right. We work

arXiv:2610.01108v2 Announce Type: replace Abstract: Retrieval-based speculative decoding (SD) drafts tokens by copying continuations from existing text, which suits coding agents that repeatedly repro

I shipped a new feature for my blog today: the Newsletters page, which offers an index of all of the newsletters I've sent out, both my free weekly Substack and my monthly sponsors-only updates. I bui

arXiv:2610.13356v1 Announce Type: new Abstract: Coding agents are increasingly deployed for end-to-end software engineering tasks, where a readily available oracle evaluator that defines the success c

arXiv:2610.13166v1 Announce Type: new Abstract: Terminal agents are moving beyond local operations toward completing real-world professional tasks. Short trajectories can demonstrate commands and tool

arXiv:2610.13152v1 Announce Type: new Abstract: Open coding agents are commonly trained through supervised fine-tuning on interaction trajectories whose final patches pass the benchmark test suite. Ho

arXiv:2610.12549v1 Announce Type: cross Abstract: Embodied coding agents construct robot policies from natural-language instructions by generating executable programs and refining them from execution

arXiv:2610.13022v1 Announce Type: cross Abstract: As LLMs become increasingly capable of implementing software, a critical bottleneck emerges: whether they truly understand what users want. Users ofte

If the agent isn't using my diagnostics library, I could introspect and update AGENTS.md, but there's still a delta, and it'll drift. Instead, I write a pre-commit hook that checks the git diff for di

When we talk about agents, that doesn't necessarily mean we're talking about Python. In today's modern ecosystem, an agent might run as a high-concurrency Go microservice on Cloud Run, or live inside

Today I'm launching a new project called SynthTraces 🔥 It is a minimal codebase to generate synthetic coding agent session traces using Pi (from @badlogicgames) I wanted a large number of coding-agent

arXiv:2608.24188v1 Announce Type: new Abstract: Coding agents re-send large file reads and tool outputs to a frontier LLM every turn, and this context dominates their token bill. General-purpose promp

I’ve been building Catalyst around a capability I want engineering agents to have: An AI agent can read a program and make a good guess about what matters. Catalyst lets it measure what actually matte

arXiv:2610.13356v1 Announce Type: new Abstract: Coding agents are increasingly deployed for end-to-end software engineering tasks, where a readily available oracle evaluator that defines the success c

arXiv:2610.13166v1 Announce Type: new Abstract: Terminal agents are moving beyond local operations toward completing real-world professional tasks. Short trajectories can demonstrate commands and tool

arXiv:2610.13152v1 Announce Type: new Abstract: Open coding agents are commonly trained through supervised fine-tuning on interaction trajectories whose final patches pass the benchmark test suite. Ho

arXiv:2605.16909v1 Announce Type: new Abstract: Tool-using agents are increasingly expected to operate across realistic professional workflows, where they must interpret multimodal inputs, coordinate

arXiv:2606.30111v1 Announce Type: cross Abstract: Embodied agents are typically built as hand-designed compositions of perception, memory, planning, and action modules. This modularity exposes a large

arXiv:2607.21672v1 Announce Type: cross Abstract: Long source-code contexts consume many text tokens, motivating the proposal to render code as images for vision-language models. Recent work asks whet

arXiv:2609.00453v1 Announce Type: new Abstract: Giving an agent a file about a named expert can supply hard-to-find material, produce a recognizable persona, or change what the agent decides. These ar

arXiv:2609.22308v1 Announce Type: new Abstract: Coding-agent benchmarks usually evaluate implementation after the target behavior has been specified in text, code, or demonstrations. Existing research

arXiv:2609.26499v1 Announce Type: new Abstract: Today, progress in open-weight language models enables systems capable of writing, executing and debugging code while still running on a single workstat

arXiv:2610.07862v1 Announce Type: cross Abstract: A central challenge for scientific agents is to turn analytical experience into reusable expertise grounded in physical evidence. Here we introduce Ga

I've been building ANCHOR, a web automation agent that runs entirely on Ollama. You describe a task in plain language ('Register Maria Silva, IT department, contractor, and save'), point it at a site,

arXiv:2608.31057v1 Announce Type: new Abstract: Agent working memory is heterogeneous. Objects such as instructions, artifacts, tool outputs, and agent-generated state play different semantic roles an

arXiv:2609.05527v1 Announce Type: new Abstract: Wherever a coding agent works under engineer supervision, or a clinical model assists a radiologist, the deployment question is whether to keep the huma

arXiv:2609.26499v1 Announce Type: new Abstract: Today, progress in open-weight language models enables systems capable of writing, executing and debugging code while still running on a single workstat

arXiv:2609.26891v1 Announce Type: new Abstract: Modern language-model agents are built around the extit{agent loop}, where the LLM is placed in an environment exposing a set of tools, and the LLM has

arXiv:2609.33762v1 Announce Type: cross Abstract: LLM agents resend their whole conversation on every turn, and most of it was already processed on the previous turn. Serving systems avoid recomputing

arXiv:2609.38983v1 Announce Type: cross Abstract: Modern AI coding-agent harnesses (Claude Code, Codex CLI, Cursor) rest their security boundary on a largely unexamined assumption: that the action A a

arXiv:2610.07816v1 Announce Type: new Abstract: Small language models (SLMs) are attractive as local agent controllers because they reduce remote inference, latency, and deployment footprint, yet stru

When we talk about agents, that doesn't necessarily mean we're talking about Python. In today's modern ecosystem, an agent might run as a high-concurrency Go microservice on Cloud Run, or live inside