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software-engineering
75 postsHarness Engineering: Curating Context to Scale AI Coding Agents
Harness engineering keeps AI models fixed and optimizes context and tools instead, encoding nonfunctional requirements for reliable agent output.
Rust Is a Harness: Why AI Coding Agents Favor Strict Languages
As AI coding agents write more software, Rust's strict compiler and type system turn verification into a competitive advantage over ergonomics.
Proof-Adjusted Autonomy: Why a '90% Autonomous' Agent Is Really 61.6%
Why AI agents claiming 90% autonomy actually deliver 61.6% verifiable work — introducing Proof-Adjusted Autonomy and the concept of Proof Debt.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comDesigning a Coding Agent Loop: Goals, Verification, Stopping
How to design a coding agent loop: goal-check separation, a verification ladder, isolated attempts, and explicit stopping states.
Context bankruptcy: why coding agents need strategic forgetting
Massive context windows don't make coding agents smarter; they can cause 'context bankruptcy'. Learn how AST-based pruning and dynamic ignore files restore agent reliability.
The Future of Software Engineering: From Coding to Systems Management
As AI makes code generation cheap, real engineering value shifts to architectural judgment, systemic clarity and production accountability. Here's what changes.
DevTeam AI: A Multi-Agent Engineering Team on QwenCloud
Built for the QwenCloud Global AI Hackathon, DevTeam AI turns a product idea into a full delivery plan using 11 specialized AI agents and human approvals.
Memory Engineering Is a Promotion Pipeline, Not Notes
An AI agent framework runs memory through a promotion pipeline with evidence and approval instead of direct writes; rejection counts as a healthy outcome.
Statgate: Statistically Calibrated Gates for LLM Evaluations
Statgate offers statistically calibrated gates that reduce false positives in LLM evaluations.
Clean Code, Poor Performance: Insights and Implications
Explore the performance impact of clean code principles in this insightful video. Discover best practices for efficiency.