Karpathy — No Code Since December, Now Directing Agents #
- Karpathy Hasn’t Written Code Since December — He Just Directs AI Agents Now (htek.dev) — Karpathy’s workflow inversion: no manual code since December 2025, now directing fleets of up to 20 parallel agents. The 80/20 ratio of human-to-AI code authorship has inverted. The Autoresearch project — 700 experiments in 2 days from one markdown prompt — is cited as the clearest demonstration of what directing agents at scale looks like.
- Andrej Karpathy Has Renamed Vibe Coding — What Engineering Leaders Need to Do (SD Times) — Karpathy’s reframing: moving “vibe coding” as a pejorative to “agentic engineering” as a discipline requiring deliberate investment in process and tooling. Engineering leaders who dismiss vibe coding as undisciplined are now being asked to take agentic engineering seriously as a structured practice — they’re the same thing with different governance expectations.
Pragmatic Engineer — Definitive Practitioner Survey #
- AI Tooling for Software Engineers in 2026 (Pragmatic Engineer) — Survey of 900+ engineers: Claude Code now leads as the most-used AI coding tool, overtaking Copilot and Cursor. 95% use AI tools weekly; 55% regularly use agents. The most comprehensive practitioner survey of the year — benchmark data for tracking adoption velocity.
- The Impact of AI on Software Engineers in 2026: Key Trends (Pragmatic Engineer) — 75% of engineers use AI for half or more of their work. Agent users are twice as excited about AI as non-users. Anthropic models dominate coding by a wide margin over competitors. Senior engineers (staff+) lead agent adoption at 63.5%.
- How Claude Code Is Built (Pragmatic Engineer) — Deep technical dive into Claude Code’s architecture and design decisions from Orosz’s conversations with the Anthropic team. Unusually substantive inside view; covers why it’s terminal-based, how plan mode works, and the decision-making behind the agentic UX.
- Spec-Driven Development: From Code to Contract in the Age of AI Coding Assistants (arXiv) — Academic formalisation of SDD as a response to AI-generated code drift. Documents vulnerability rates of 9.8%–42.1% across benchmarks and argues for executable specifications as the control mechanism. The paper that gives practitioners the vocabulary to explain why “just vibe it” produces technically risky codebases.
- Diving Into Spec-Driven Development with GitHub Spec Kit (Microsoft Developer Blog) — Hands-on walkthrough of GitHub’s Spec Kit CLI: spec-first workflow, reported order-of-magnitude reduction in “regenerate from scratch” cycles. Microsoft is investing in the spec-driven approach as the governance layer for AI coding in enterprise contexts.
Willison — The Agentic Engineering Pattern Library #
- Agentic Engineering Patterns: Linear Walkthroughs (Simon Willison) — The “linear walkthrough” pattern: using a coding agent to generate a structured explanation of vibe-coded code you don’t fully understand. A practical technique for managing comprehension debt after the fact — pairs naturally with Osmani’s comprehension debt framing.
- Agentic Engineering Patterns: Writing Code Is Cheap Now (Simon Willison) — Writing is nearly free; the bottleneck shifts to review, intent specification, and maintaining understanding. Inverting the economics of software development changes what skills matter — not less important to be an engineer, differently important.
- Highlights from My Conversation About Agentic Engineering on Lenny’s Podcast (Simon Willison, 2026-04-02) — Willison’s evolving views on responsible agentic engineering, when vibe coding is acceptable, and his own workflow practices. Useful as a practitioner’s own periodic synthesis.
Multi-Agent Production — What Survived #
- Multi-Agent in Production 2026: 3 Patterns That Survived (NiteAgent) — Post-mortem: agent-flow (assembly line), orchestration (hub-and-spoke), and bounded collaboration (controlled peer mesh) survived in production. Peer-collaboration systems failed universally. The practical design guidance for anyone building multi-agent systems now — not theoretical patterns but empirically validated ones.
Context Engineering — The New Skill #
- Context Engineering Best Practices for AI-Powered Dev Teams (2026) (Packmind) — The context lifecycle: create → distribute → maintain → update → measure. Covers CLAUDE.md-style files as team-level context artefacts, context drift as conventions evolve, and measuring context effectiveness. Practical operationalisation of what “context engineering” means at team scale.
Cross-links #
- Claude-Specific Expertise The Pragmatic Engineer survey establishes Claude Code as the leading AI coding tool — a direct data point for the claude-expertise topic’s coverage of adoption patterns.
- Applications of Vibe Coding The arXiv SDD paper (9.8%–42.1% vulnerability rates) provides the formal evidence base for the enterprise risk concerns surfacing in the applications journal.
- AI Impact on Society Karpathy directing 20 parallel agents is the most vivid current image of what the “anticipatory layoffs” in ai-societal-impact are anticipating — the skill compression is now documented and named.
- Quality signal: The Pragmatic Engineer survey data (900+ respondents, Claude Code #1) is the most credible adoption measurement available. It supersedes previous qualitative claims about tool leadership.
- Emerging pattern: The “agentic engineering patterns” genre is maturing — Willison’s guides are the most systematic attempt to build a practitioner pattern library. Watch for this to become a formal curriculum in 2026 (see the DeepLearning.AI SDD course).
- Keyword suggestion:
"agent-flow" OR "orchestration pattern" multi-agent production — the production pattern vocabulary is stabilising; these specific terms now have empirical backing.