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ChatGPT sounds thoughtful. Claude sounds empathetic. And yet nobody is home. A mechanistic, philosophical and societal look at the difference between language models and consciousness.

Within a few weeks, two open-source tools have set out to solve Claude Code's memory problem. But they don't solve the same problem — Graphify builds a code graph, MemPalace stores the conversation.

Bonus article of the series — how the byhaushalt demo parser holds up against two independent sources: the official EPL PDFs from the Bavarian finance ministry and the interactive budget diagram at stmfh.bayern.de. Σ revenues and Σ expenses match the PDF Σ to the cent; the residual difference against STMFH is data-vintage-related.

Article 10 of the series — how a Vite SPA in the repo becomes a live site on a custom subdomain. Branch protection for solo projects, a Bash script that fills the pages branch via git worktree, custom domain via DNS CNAME plus .domains file, HTTPS via Let's Encrypt. And why CI deliberately gets its own follow-up article.

Article 9 of the series — three hooks for byhaushalt: PostToolUse formats after every edit, PreToolUse blocks commits with debug leftovers, Stop runs fast tests but only for changed layers. Why an overly aggressive Stop hook does more harm than good, and why Playwright belongs in CI, not in a hook.

Article 8 of the series — Markdown spec as E2E test contract: Claude reads the user flow, explores live in the browser via Playwright MCP, finds robust selectors, and writes the Playwright test. Three specs, three tests, three baseline screenshots.

Article 7 of the series — two MCP servers, one project configuration: Context7 fetches current library documentation directly into the editor before Claude has to guess. Plus a shadcn/ui migration and a chart-builder skill that calls Context7 deliberately.

Article 6 of the series — three worktree branches, three visualizations over the same data model. Treemap, sunburst, and Sankey compared side by side rather than guessed at sequentially. Plus: why the decision in the end was not against two losers, but in favor of a switcher.

Article 1 · Swift on the Server with Hummingbird. We create the project, write Package.swift, set up the AsyncParsableCommand entry point, and build a minimal router with /healthz and /v1/models until curl gets an answer.

Article 5 of the series — v0.4 delivers three JSON files, not a data model. A plan file with three tasks and parallel subagents builds schema, normalization, and property-based tests. Plus: what format inconsistency teaches about parallelization.

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.

Article 4 of the series — three slash commands make the parser repeatable: /parse-epl for any Einzelplan, /check-totals with built-in pytest, /diff-vs-gesamt for comparison against the full budget. Plus: what xfail reveals about parser gaps.

Article 3 of the series — the first parser code for byhaushalt takes shape via TDD: a custom skill with trigger description, uv setup, six tests before implementation, and how the sum consistency test catches hallucinations in PDF parsing.

Article 2 of the series — before byhaushalt sees its first parser code, Claude Code maps the PDF structure of the Bavarian budget plans. Plan Mode, Explore subagent, and Architecture Decision Records as tools for exploring before implementing.

Article 1 of the series — we install Claude Code, set up the byhaushalt repo, write the first memory file, and pin down what the agent has to follow in every session. Plus: permissions, source data, the first day.

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 new LLM out of Miami promises 12 million tokens of context, linear scaling and a 52× speedup over FlashAttention. We take a close look at what's technically behind it — and where reasonable skepticism kicks in.

Eight articles of theory, one bonus chapter of practice. We combine all the code fragments from the LLM series into a working mini language model, train it on TinyShakespeare, and tack on a tiny SFT step. With a wink to Star Trek TNG.

How a base model that completes text becomes a helpful assistant. Supervised Fine-Tuning, RLHF, DPO, and Constitutional AI — the last piece of the LLM pipeline, with the candid question of what alignment actually solves.

Claude Desktop registers a Native Messaging bridge in seven browser directories without asking — even in browsers that aren't installed. What it means technically, why it violates the ePrivacy Directive, and why Anthropic of all companies is squandering trust here.

Position, depth, stability — what gets added on top of attention to make a complete transformer. Positional encodings, feed-forward layers, residual connections, layer normalization, the entire block in Python, and the leap to GPT, BERT, Llama, and Claude.

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.

How the bottleneck of RNNs was replaced by a mechanism that links every token to every other. Query, Key, Value, Multi-Head, and the paper that flipped the NLP world, explained with library metaphors and just enough math for the curious.

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.

Why language needs memory, and how the first language models learned that context. Recurrent networks, LSTMs, and the long-sentence problem, explained without a formula storm.

An independent look at GPT-5.5, released April 23, 2026. What the numbers really say, where Claude Opus 4.7 still leads, and why the pricing trajectory should worry developers.

How neural networks learn from errors. Loss, gradients, chain rule, gradient descent — backpropagation implemented by hand on a 2-layer MLP that learns XOR and token prediction.

What happens between embedding and logit. Neurons, layers, forward pass, and activation functions — fully implemented in numpy, no framework magic.

How language models encode meaning in numbers. Embedding tables, cosine similarity, vector arithmetic, and why King minus Man plus Woman equals Queen.

What happens between input and output? Tokens, probability distributions, and sampling strategies — explained step by step, with real code.

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 open-source tool that outclasses commercial AI memory solutions — using a 2,500-year-old method, running locally, free, and open source.

Anthropic's Claude Mythos broke out of a sandbox and found thousands of zero-days. An assessment between real risk, methodological gaps, and strategic narrative control.