Coding

DeepReinforce trains a coding model that learns its own agent harness. I tested the 9B and 35B locally on an M3 Max. The idea is strong, the benchmarks are self-reported, and the biggest stumbling block sits in the packaging.

For the finale we place the local agent where Claude or ChatGPT usually sit inside Xcode. Apple showed the local provider slot at WWDC26, and we installed macOS 27 and Xcode 27 on purpose to put it to the test. How far does the borrowed small model get there? Article 13 of the series "A Local Coding Agent with apfel".

The series finale: n8n binds to its own service on SAP BTP with a real OAuth flow. Client Credentials against the xsuaa token endpoint, a CAP service as a SAP-native stand-in, the n8n OAuth2 credential, and a workflow that enriches a ticket with a case ID from BTP.

Eleven articles covered what n8n can do. This one places where it does not belong: against SAP Cloud Integration with its EAI heritage and the Edge Integration Cell with its data boundary. With a decision tree instead of a tool takedown.

Operation goes production-ready. This article moves the single-process instance to queue mode: main accepts webhooks and enqueues executions in Redis, workers run them. With worker scaling, queue metrics, a production checklist, and a note on what queue mode does not do.

With @function you define your own CSS functions. The real novelty is not that CSS rebuilds Sass, but that a CSS function decides in the browser instead of at build time.

The pipeline now enriches its tickets with master data from a SAP backend. This article shows the OData binding over HTTP, SAP's own error format, graceful degradation on an unknown customer, and where AIF stays complementary.

With the Containerization architecture and the new Container machine, Apple has spent two years building a native Docker alternative for the Mac. A technical analysis of who is really under attack.

The agent gets a third surface. Behind a Hummingbird server it streams its work into the browser over Server-Sent Events, confirmation by click included. The same core as in the terminal, only a different sink. Article 11 of the series "A Local Coding Agent with apfel".

MCP moves writing tools out of the agent into separate servers. We build a small MCP server, attach it to apfel, and measure what MCP solves and what it doesn't. Article 10 of the series "A Local Coding Agent with apfel".

A single AI backend degrades to the rule-based emergency exit on failure. This article builds real redundancy from two local models: round-robin in normal operation, automatic failover on a single outage, rule-based only when both are down.

The one-shot command becomes an interactive REPL session. The key to testability is the strict separation of render logic and terminal I/O. Article 9 of the series "A Local Coding Agent with apfel".

Two months after warning that Mythos was too dangerous to release, Anthropic makes the Mythos class public. A look at Claude Fable 5 and Mythos 5 between benchmark records, pricing tactics, and 30-day data retention.

The naive agent loop ends when the model goes quiet, and that is just a self-report. We build a loop whose stop condition is a machine check, with an iteration limit and a context budget as guards. Article 8 of the series "A Local Coding Agent with apfel".

Until now two separate paths ran side by side: the rule-based ingest and the AI classification. This article merges them into one pipeline, makes classification a swappable stage, and positions the rule-based classifier as a deliberate fallback behind the model.

The naive file edit fails on the small model. We build the agent around that weakness, with constrained output and a two-stage edit workflow, and measure how much can be recovered. Article 7 of the series "A Local Coding Agent with apfel".

A reproducible eval of 15 tasks across five categories measures where the local Foundation Model carries as a coding agent and where it breaks. With a cloud sample and a separate measurement of what the model claims about its own success. Article 6 of the series "A Local Coding Agent with apfel".

The AI classifier runs, but what happens when the model goes down? A global error workflow with a Telegram alert, an observability stack of Prometheus, Loki and Grafana, and a silent fallback that wants to be made visible.

We build the first tools the agent uses to change things, and lock them down — a path sandbox, a confirmation gate, a diff before writing, and defense-in-depth for the shell. Article 5 of the series "A Local Coding Agent with apfel".

We teach the agent to call tools — the tool definition in the OpenAI schema, the round-trip of invocation, execution and continuation, and a tool abstraction in Swift. Article 4 of the series "A Local Coding Agent with apfel".

Cross-document view transitions bring app-like navigation to classic multi-page sites — with a single CSS at-rule and no framework at all.

We set up a Swift package, build an async HTTP client against apfel --serve and process SSE streaming token by token — Article 3 of the series "A Local Coding Agent with apfel".

We start apfel as a local OpenAI-compatible server, walk through every endpoint and see where the protocol diverges from OpenAI — Article 2 of the series "A Local Coding Agent with apfel".

We install apfel, walk through the three modes (prompt, serve, chat), and see where the on-device model holds up and where it gives way — Article 1 of the series "A Local Coding Agent with apfel".

A series takes a close look at the Foundation Model every Apple Silicon Mac running macOS 26 ships with — and builds on it a coding agent in Swift that runs locally.

The TeamPCP incident from May 2026 shows how a tampered VS Code extension led to the exfiltration of around 3,800 internal GitHub repositories — and why the problem is not GitHub but the trust model of modern developer environments.

Anthropic has released Claude Opus 4.8: same price as 4.7, a clear jump in coding and reasoning, a measurably lower tendency to let its own code flaws slip by, and dynamic workflows with hundreds of parallel subagents.

How an n8n workflow gets an authenticated webhook endpoint, how credentials are stored securely, and how classifier logic is extracted into a sub-workflow.

Building a rule-based ticket classifier in n8n: the item model in practice, writing expressions correctly, choosing between Set and Code nodes — and where the classifier predictably fails.

Why a real ticket dataset has no place in a public repo, and how a hybrid generator using local models and Claude produces realistic test data with a reproducible distribution.

Self-hosting n8n in a production-grade setup: Docker Compose, Postgres instead of SQLite, Caddy with auto-HTTPS, persistent volumes, and the environment variables that actually matter.

What n8n actually is under the hood: editor, execution engine, task runners, workflows as JSON. Plus the item array as the central data model and where n8n fits in the integration landscape.

Article 7 of the Hummingbird series. We measure the LLM gateway against functionally equivalent implementations in FastAPI and Fastify — with a fair middleware stack, a deterministic backend stub, and oha as the load generator. The results are both what you expect and somewhat surprising.

SAP has taken a strategic stake in n8n and embedded it in Joule Studio. Mercedes-Benz is rolling out the platform globally. A prologue to the n8n getting-started series.

SAP announced the ABAP MCP Server at Sapphire 2026 — the technical foundation for plugging external AI agents like GitHub Copilot, Amazon Q, or Claude Code directly into ABAP development. A look at what the announcements mean technically, what they will cost, and where the gaps remain.

Prologue · Series: Agentic Coding with Claude Code. Anyone reading tech newsletters, conference keynotes, and tool landing pages this year runs into two terms sold with identical promises: Vibe Coding and Agentic Coding. The future of programming, they say.

A step-by-step migration strategy away from GitHub, with a focus on CI pipelines. Concrete workflow translation, self-hosted runner setup, why OSS and proprietary builds must not share runners, and a checklist you can tick off.

Which code hosting platforms operate without default-on data processing? Comparison table, platform profiles from Codeberg through Gogs and Launchpad to AWS CodeCommit, plus a concrete TDM opt-out implementation.

Since April 24, 2026, GitHub uses Copilot data from Free, Pro and Pro+ accounts for AI training by default. What's behind the change and why it exposes the platform's two-class model.

Anthropic releases Claude Opus 4.7 with significantly better coding performance, 3.75 megapixel vision, and a new xhigh effort level. An assessment of the benchmarks and the Mythos hint on the side.

An Obsidian plugin for bidirectional synchronization with BookStack — built with Claude Code as a structured development partner.