# agentic-coding

Epoch AI's SWE-bench Verified v2.x aligns model scores with developer reports. Key lesson: benchmark outcomes are heavily influenced by scaffold/tooling quality, environment reliability, and evaluation settings, not just base model capability.

Google announced Gemini 3.1 Pro preview with stronger core reasoning and a verified 77.1% on ARC-AGI-2. The real engineering question is whether the model can handle complex multi-step production workflows, not just win benchmarks.

Peter Steinberger shares a high-scale PR triage workflow: run 50 Codex agents in parallel, emit structured JSON for every PR, then consolidate in one large-context session. Clean reports can beat premature vector database architecture.

Liquid AI's LFM2.5-1.2B-Thinking (1.17B param, 32K context) runs on-device (<1GB mem). Claims to match/beat Qwen3-1.7B on reasoning, with faster decoding & fewer tokens. Strong for tool-calling/data extraction, but weaker on knowledge-heavy tasks.

Anthropic & Infosys partner to integrate Claude/Claude Code with Infosys Topaz. This moves beyond chatbot demos to governance-ready enterprise agents for telecom, finance, manufacturing, and software dev, handling complex tasks like compliance, risk, and legacy modernization.

Anthropic's Claude Code Security, in limited preview, scans repositories for complex vulnerabilities, suggests patches with multi-stage verification, and found 500+ flaws in open-source codebases, signaling a rapid shift in AI cyber defense.

Karpathy used Claude Code to build a custom dashboard in 1 hr, reverse-engineering a treadmill API. He believes AI-native sensors & LLMs will enable highly custom, ephemeral apps, rendering the App Store model obsolete. The ultimate goal: 1-min app creation.

SWE-bench: Claude Opus 4.5 (76.8%) unexpectedly beat 4.6 (75.6%) for #1. MiniMax M2.5 tied for #2 at 1/20th Opus's price, with 4 Chinese models in top 10. GPT-5.3-Codex missed due to no API. Bonus: Claude for Chrome to add chart labels.

Ethan Mollick's game-changing AI framework: Model, App, Harness. The same AI (e.g., Claude Opus 4.6) performs vastly differently across layers. Mollick used Claude Code to turn GPT-1's 117M weights into 80 books in ~1 hour, selling out immediately.

Claude Code's UI change to 'Read 3 files' summaries ignited developer fury on HN: they felt the AI hid its actions. Boris Cherny responded, admitted mistakes, and shipped fixes. This revealed the core tension in AI tool design: simplicity vs. transparency.

Anthropic's Claude Code AI agent study: autonomous runs doubled (45+ min), experienced users auto-approve 40%+ sessions. Claude clarifies more than interrupted. 73% of API actions still human-in-loop. Key: models handle more autonomy than users grant ('deployment overhang').

Hugging Face CTO Thomas Wolf analyzes how AI fundamentally restructures software: return of monoliths, death of Lindy Effect for legacy code, rise of strongly typed langs, new LLM langs, & open source changes. Karpathy predicts: "rewriting large fractions of all software many times over."

Drexel/Missouri S&T analyzed 33,596 agent-authored GitHub PRs from 5 coding agents. Overall merge rate: 71%. Codex: 83%, Claude Code: 59%, Copilot: 43%. Rejection cause: no review. LeadDev warns PR flood is crushing monorepos/CI.

Steve Yegge's 'AI Vampire' theory: AI boosts productivity 10x, but who gets the 9x gain? If the company takes all, burnout. If you take all, company dies. Agentic coding is 3-4 hrs/day max. Yegge's $/hr formula: control the denominator, not the numerator.

AI writing better code? That "Deep Blue" feeling, coined by Simon Willison & Adam Leventhal (Oxide & Friends), means IBM's chess computer & the color of sadness. It's not just a tech problem, but a psychological crisis for engineers.

GitHub's Agent HQ now offers multi-agent support (Claude, Codex, Copilot) for Copilot Pro+ & Enterprise users. Run multiple AIs simultaneously in GitHub/VS Code to tackle problems from different angles. Outputs become Draft PRs. A paradigm shift for code review.

Technical debt lives in code, cognitive debt in your brain. As AI writes 80% of code, system understanding drops to 20%. UVic's Margaret-Anne Storey, Simon Willison, & Martin Fowler confirm this isn't a hypothetical future—it's happening now.

Thoughtworks' AI in software retreat: Juniors more valuable, mid-level devs at risk, source code transient, AI agents on org charts. Humans too slow for AI's speed.

Spotify's co-CEO revealed top developers haven't written code since December, using Honk (powered by Claude Code) to fix bugs & ship features via phone. This AI-driven approach led to 50+ new features in 2025, proving AI is their secret weapon, not more engineers.

OpenAI's Responses API now uses 'Skills' via the shell tool: reusable instruction bundles loaded by models as needed. Simon Willison found inline base64 skills in JSON requests neatest. Skills fill the 'missing middle layer' between system prompts and tools, preventing bloat.