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Earlier sources: AI coding agents
AI coding agents use models and development tools to inspect, modify, and test software. Follow coding workflows, repository tooling, evaluations, and evidence about where these systems succeed or fail.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗85 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
AgentSWE: Can Coding Agents Build the Agent You Actually Want? ↗
As the production of software passes into the hands of software itself, coding agents are increasingly commissioned to build agents fitted to their users' own workflows. This delegation carries a quiet assumption, that the delivered agent will faithfully serve the requirement it was built for, rather than merely appear to. No existing benchmark tests that assumption. We introduce AgentSWE, a benchmark for agent software engineering spanning three stages of the agent development lifecycle: Creation of a complete agent from a natural-language requirement, Editing of production agent codebases, a…
- Hacker News · Posted on Hacker News · First archived
Robium – Physical AI harness for coding agents ↗
Hacker News discussion.
- OpenAlex · Published · First archived
An Exploratory Pilot Study of Cognitive Factors Influencing the Adoption of AI Coding Agents in Agile Development Teams ↗
This study considers the cognitive factors influencing the adoption of artificial intelligence (AI) coding agents among software engineers in Agile development environments. In this context, Transparency refers to the degree to which an AI system’s decision processes are clear or understandable to its users, while Trust denotes the confidence developers place in the reliability and correctness of AI-generated code. Specifically, it analyzes the roles of Transparency and Trust as predictors of developers’ Behavioral Intention to deploy AI-generated code. Using a quantitative, cross-sectional su…
- Hacker News · Posted on Hacker News · First archived
Show HN: Crashlytics for AI Coding Agents ↗
Hacker News discussion.
- GitHub · Repository created · First archived
VectorSpaceLab/AgentSWE ↗
Can coding agents build the agent you actually want? A benchmark of 25 agent software engineering tasks across creation, editing and optimization.
- arXiv · Published · First archived
Cadence: Strategic Guidance for Coding Agents ↗
Runtime monitors are increasingly used to improve the reliability of LLM-based coding agents by inspecting execution trajectories and delivering corrective guidance upon detecting misbehavior. However, their effectiveness remains limited by static guidance triggering schemes. Existing monitors rely either on fixed inspection intervals, missing timely guidance during severe misbehaviors while incurring unnecessary overhead during healthy execution, or on rigid heuristic rules, failing to detect complex reasoning errors. To address these limitations, we propose Cadence, a dynamic monitoring fram…
- Hacker News · Posted on Hacker News · First archived
Fakegreen: Catch AI coding agents faking a green build (no LLM) ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Strategies for Pricing an AI Coding Agent Subscription to Ensure Profitability ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Singularity – memory that makes coding agents cheaper on repeat work ↗
Coding agents start every session from zero. Ask Claude Code for a change like one it made last week and it reads the same files again, falls into the same test traps again, and you pay for all of it again. Singularity learns from your finished sessions (change committed, tests passing): where each kind of change goes in this repo, how it gets checked, and the mistakes made along the way. When the next task starts, a hook hands the agent the work…
- Hacker News · Posted on Hacker News · First archived
Show HN: Coding Agent with Cost Saving Built-In ↗
Hey we just launch Wiyomi, coding agent with built-in cost-saving strategy. We want to help developer and engineering team reduce AI waste and build more. I would appreciate if you can try it and give me feedback! thank you.
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about AI coding agents
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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