Thinking out loud on hard problems
- Self-Hosting Chatterbox on Apple Silicon: The Build Log, and the Bigger Bet Underneath It
A real build log for self-hosting Resemble AI's Chatterbox voice-cloning model on Apple Silicon — the judgment calls the docs skip — and why this pattern reaches well past TTS demos.
- The Agent That Forgets Everything: Cross-Session Memory Without Breaking the Audit Trail
The first five parts solved within-session problems. Part 6 addresses what happens when the context window closes — and why cross-session memory for a compliance agent is the hardest unsolved problem in this stack.
- 530,702 Tokens in the Index. 560 Reached the Model. All 12 Answers Correct.
Part 4 mapped the two retrieval architectures. Part 5 builds the experiment and runs the numbers — a k-sweep from top_k=20 to top_k=1 where accuracy never broke.
- Why Did the Wrong Tokens Arrive? Reranking vs. PageIndex
Parts 2 and 3 compressed the tokens that arrived. Part 4 asks the better question — why did the wrong tokens arrive at all? Two retrieval architectures answer it in opposite ways.
- 60–95% vs. 9.2%: What I Actually Measured With Headroom
The upstream claim is 60–95% token reduction. My measured result was 9.2% for the config I'd ship to a regulated client — and 25.6% for the one I wouldn't. Here's why that gap is the right story.
- 97% Fewer Tokens, Zero Model Changes: RTK at the Harness Boundary
The harness made the agent reliable — and expensive. RTK cuts the cost without touching the model, the prompt, or the pipeline logic. And it covers a lot more than git.
- Your Agent Doesn't Need a Better Model. It Needs a Harness.
Most agent failures aren't capability problems — they're enforcement problems. A controlled six-rung experiment shows what actually moves the needle.
- Three Layers Between Your Code and Your Database
Drivers, ORMs, and wire protocol adapters do three different jobs. Conflating them is the line between a developer who uses databases and an engineer who designs systems around them.
- Voicebox.sh — The Local-First Voice Stack That Just Made MCP Voice Agents Practical
An engineer's tour of voicebox.sh — what it actually is, how the local API and MCP server work, and what developers are already building on top of it.
- The AI Stack Nobody Drew You a Map For: Agents, RAG, MCP, Skills, and the LLM Beneath Them All
Everyone says they're building AI. Almost nobody agrees on what that means. Here's the five-layer stack that actually explains what enterprise AI is made of — and how to stop picking the wrong piece for the wrong problem.
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