# agentic-coding

Anthropic engineer trq212 shares his methodology for coding with Claude Fable 5: the bottleneck isn't model capability anymore—it's whether users can surface their 'unknowns' before, during, and after implementation. Includes prompt examples plus HTML artifacts for visualizing blind spots and plans.

3-minute lightning talk slides. AI has read almost everything — but some concepts aren't in training data yet. What you know that AI doesn't = your leverage.

The Claude Code source leak had everyone excited about KAIROS and model codenames. But the same codebase had a 3,167-line function, zero tests, silent model downgrades, and regex emotion detection. These aren't just Anthropic's mistakes — they're AI-generated code's default failure modes.

gu-log had 336 AI-translated posts. We thought they were 'fine' — until we built a multi-agent scoring system and discovered 74% needed rewriting. This is the story of how we designed the eval, ran it overnight, and what we learned.

Simon Willison finally defines Agentic Engineering after 11 hands-on chapters: using coding agents to help build software. The interesting part is why he needed the patterns first before the simple definition felt earned.

Simon Willison's Agentic Engineering Patterns, Chapter 3: AI should help us ship better code, not worse. Technical debt cleanup costs near zero now, architecture decisions can be validated with prototypes instead of guesses, and quality compounds over time.

Simon Willison's First Run the Tests pattern is four words with three effects: the agent learns the test command, gauges codebase size, and shifts into a test-maintenance mindset. Tiny instruction, large behavioral nudge.

Simon Willison shared his agentic engineering playbook at the Pragmatic Summit — five tokens to start TDD, Showboat for manual verification, reverse-engineering six frameworks into a standard, and why bad code is a choice you make.

Simon Willison's new Agentic Engineering anti-pattern hits hard: do not submit AI-generated code you have not personally verified. That is not saving time; it is stealing reviewer time. The post pairs principles with a terraform destroy horror story.

OpenClaw's ACP lets you spawn Codex, Claude Code, and Gemini from Discord/Telegram chat. Now with Telegram topic binding, persistent bindings that survive restarts, ACP Provenance for audit trails, and more. (Updated 2026-03-09)

Cursor launches always-on background agents (Automations) — self-healing CI, auto-approving PRs, security review, and team memory. This marks the paradigm shift from Coding Assistant to Self-Driving Codebase.

Simon Willison introduces Agentic Manual Testing: let AI agents manually operate code and UI like humans do, catching bugs that automated tests miss. With Playwright, Rodney, and Showboat, the 'tests pass but it's broken' nightmare becomes a thing of the past.

The core message: most people do not fail because the model is weak; they fail because context management is messy. Start with a minimal CLI workflow, then iterate through rules, skills, and clear endpoints until agent behavior converges.

Karpathy spent a weekend running 4 Claude + 4 Codex agents as an ML research team on GPUs. The result: agents are S-tier at implementation but F-tier at experiment design. His key insight — 'You are now programming an organization' — might define agentic engineering in 2026.

Chapter 5 of Simon Willison's Agentic Engineering Patterns: Interactive Explanations. Core thesis: instead of staring at AI-generated code trying to understand it, ask your agent to build an interactive animation that shows you how the algorithm works. Pay down cognitive debt visually.

Anthropic killed third-party OAuth tokens, leaving the official Claude CLI as the way to use a subscription programmatically. This guide covers claude -p input methods, output formats, JSON schema, tool whitelisting, sessions, streaming, and wrappers.

A two-person boutique law firm uses Claude to handle the workload of over a dozen associates, from contract review to legal research. Ten years of practice knowledge became Claude Skills, and general-purpose AI outperformed legal vertical tools.

Cursor CEO drops three data points marking a tectonic shift: agent usage grew 15x, Tab-to-Agent ratio flipped to 1:2, and 35% of Cursor's PRs come from autonomous cloud agents. We're not coding anymore — we're building the factory (╯°□°)╯

Chapter 4 of Simon Willison's Agentic Engineering Patterns: Hoard Things You Know How to Do. Core thesis: every problem you've solved should leave behind working code, because coding agents can recombine your old solutions into things you never imagined.

Cloudflare engineer Steve Faulkner used Claude to rebuild 94% of the Next.js API in a week for $1,100. The secret was Next.js's public test suite as spec. When tldraw moved 327 tests private afterward, open source's rules changed.

Karpathy says coding agents started working in December 2025 as a hard discontinuity. He built a DGX Spark video analysis dashboard in 30 minutes from one English sentence. Programming is becoming agent direction, not typing.

Chapter 3 of Simon Willison's Agentic Engineering Patterns: the Linear Walkthrough pattern. This technique transforms even vibe-coded toy projects into valuable learning resources. Core trick: make the agent use sed/grep/cat to fetch code snippets, preventing hallucination.

Andrew Ng says he has not only stopped writing code, he has long stopped reading generated code. He now directs agents at a higher abstraction layer and sees X Engineers emerging inside business functions. A radical programming forecast from AI's most influential educator.

Anthropic's Claude Cowork enterprise update adds industry plugins, private marketplaces, new connectors, and Excel + PowerPoint workflows. The market signal changed too: instead of crashing software stocks, partnerships lifted Salesforce, Thomson Reuters, and FactSet.

Anthropic acquired Vercept, bringing in R-CNN inventor Ross Girshick and cofounders Kiana Ehsani and Luca Weihs to push Claude's Computer Use toward human-level computer operation. OSWorld gains and UiPath's drop show RPA investors noticed.

The Atlantic argues Americans now live in parallel AI universes: the public still sees ChatGPT, while tech workers have been radicalized by Claude Code and Codex. If coding was the preview, the broader workforce may be next.

Claude Code creator Boris Cherny declares coding 'practically solved,' predicts the 'software engineer' title will fade in 2026. He shares 3 team principles: let Claude do it, underfund to force AI adoption, and go faster.

Fintool founder Nicolas Bustamante runs a six-person company through Agent + API integrations across Brex, QuickBooks, HubSpot, and Stripe. His B2A warning: SaaS without good APIs will be bypassed by agents through WebMCP or browsers.

Simon Willison launched Agentic Engineering Patterns, a playbook for coding agents like Claude Code and Codex. Lesson one: writing code got cheap, but good code remains expensive. Lesson two: red/green TDD is the six-word spell.

Claude Code CLI now includes first-class Git worktree support via `--worktree`. Teams can run multiple isolated AI coding sessions in parallel without file collisions, making multi-agent workflows more reliable and easier to standardize for real engineering teams.

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.

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.

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.

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.

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.

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.

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.

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').

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.

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.

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.

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.

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 released GPT-5.3-Codex-Spark, its first model on Cerebras chips. It's incredibly fast (>1000 tokens/sec, 80% lower latency), but smaller, no auto-tests, Pro-only. This marks OpenAI's first production deployment on non-Nvidia hardware, redrawing the AI compute landscape.

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.

Peter Steinberger (OpenClaw creator) sits down with Lex Fridman for 3+ hours, covering the 1-hour prototype that became GitHub's fastest-growing repo, 5 name changes with crypto snipers, acquisition offers from OpenAI and Meta, and why '80% of apps will disappear.'

Karpathy used DeepWiki MCP and GitHub CLI to have Claude rip fp8 training out of torchao into 150 self-contained lines that ran faster. His bacterial code idea favors low-coupling, dependency-free code agents can extract and transplant.

Anthropic's Claude Code data: engineers merge 67% more PRs daily, with 70-90% code assisted. They launched Contribution Metrics, a GitHub-integrated dashboard to track AI's impact on team velocity. A measurement tool for engineering leaders, not a fluffy PR piece.

Matt Pocock released git-guardrails, a Claude Code skill that uses a PreToolUse hook to intercept dangerous git commands like push, reset --hard, and clean -f. It is a practical YOLO-mode safety rail for agents in Docker Sandbox.

Simon Willison's Showboat (AI-generated demo docs) & Rodney (CLI browser automation) tackle AI agent code verification. How to know 'all tests pass' means it works? Agents were caught cheating by directly editing demo files. #AI #OpenSource

Andrew Ng: AI isn't mass unemployment. Teams shrink (8 eng + 1 PM -> 2 eng + 1 PM). Bottleneck shifts from 'how to build' to 'what to build' – the "PM Bottleneck."

Opus 4.6 & Codex 5.3 sped up Karpathy's GPT-2 training by 3 mins. Karpathy failed similar attempts, noting AI's weak open-ended code optimization. Opus deletes comments, ignores CLAUDE.md, and errs. Yet, with oversight, models are useful.

Armin Ronacher (creator of Flask, Jinja2, CTO of Sentry) argues current programming languages were designed for 'humans who type slowly.' The AI agent era has different needs. He details what agents love/hate, and why Go accidentally became the winner of the agentic coding era.

SemiAnalysis: Kimi K2.5's agent swarm uses an RL-trained 'orchestrator' (not prompt magic). Claude Agent Teams were slower, pricier, & scored lower. Multi-agent is shifting from 'prompt engineering' to 'distributed scheduling.'

Anthropic's 2026 Agentic Coding Trends Report highlights multi-agent adoption, the Papercut Revolution for tech debt, self-healing code, and Claude Code hitting $1B ARR. TELUS and Rakuten case studies show developers shifting from code writer to system orchestrator.

Andrew Ng & Anthropic launched a free course: 'Agent Skills with Anthropic'. Learn to design, differentiate, and deploy AI agent skills. Skills turn general AI into specialists, directly relevant for OpenClaw's architecture.

Google launched the Developer Knowledge API and an official MCP Server (Public Preview), letting AI coding tools query current Firebase, Android, Google Cloud, and Chrome docs instead of inventing APIs from three versions ago.

TypeScript guru Matt Pocock: Stop reading AI plans! The real signal is pre-plan conversation quality. If you and AI share mental models, the plan is just a compressed understanding, echoing Brooks' 'design concept' from The Mythical Man-Month.

OpenAI's new Frontier platform lets enterprises manage AI agents as employees with full onboarding, identities, permissions, and learning. Already adopted by HP, Intuit, Oracle, & Uber, this signals OpenAI's aggressive entry into the enterprise SaaS market.

Anthropic researcher Nicholas Carlini ran 16 Opus 4.6 agents in parallel for two weeks, spending $20,000 in API costs, to build a 100,000-line Rust C compiler from scratch. It can compile the Linux kernel, QEMU, FFmpeg, Redis — and yes, it runs Doom. This is the ultimate stress test for agent teams.

Anthropic found that agentic coding benchmark scores can swing by up to 6 percentage points based on hardware configuration alone — often more than the gap between top models on leaderboards. Next time someone claims a 2-3% lead, ask them what VM they ran on.

SemiAnalysis: Claude Code now 4% of public GitHub commits, projected 20%+ by 2026. It's the real AI agent inflection point for all information work. Report also covers Microsoft's Azure vs. Office 365 dilemma & Anthropic's revenue surpassing OpenAI.

StrongDM's AI team built a 'Software Factory' where AI agents write & review code. They clone apps into a 'Digital Twin Universe' for testing, an approach Simon Willison calls radical. At $10k/engineer/day in token costs, is it worth it?

Karel (OpenAI researcher) shares how he burns billions of Codex tokens: agents writing their own notes, crawling Slack, analyzing data, and generating 700+ hypotheses. He now talks to one agent that orchestrates everything else.

Vibe coding is officially one year old! Karpathy reflects on how his shower-thought tweet became a Wikipedia entry, and introduces the professional evolution: 'Agentic Engineering' — not vibing freestyle, but treating agents as team members you supervise.