Max Nardit
Data & AI Systems Engineer working on visibility, measurement, and agentic systems.
AI now sits between people and what they’re looking for, and between work and the software that runs it. It answers, routes, remembers, forgets, and now acts on its own. Usually before anyone can check whether it got things right. I study that layer with original data and build the tools to work inside it. My background is the supply side of digital marketing: the crawl, the analytics, the automation and reporting, the plumbing under what looked like marketing. The marketing was never really the problem. Visibility, measurement, and control were. AI didn’t make that problem smaller. It moved it somewhere you can’t see.
Beetroot featured in 窓の杜 (Japan) · original-data research · shipped open-source tools
the systems that decidewhat gets found, trusted,and acted on
01 / Thesis
Operating thesis
AI is changing two things at once: how people find information, and how work moves through software.
That shift isn’t only a search problem. It touches tracking, attribution, context, memory, handoff, and trust: the systems that decide what a person sees before they make a choice.
I work on that layer. Some of it is research: measuring what changes and publishing what holds up. Some of it is engineering: building tools and workflows that keep context, expose failures, and make AI-assisted work inspectable.
02 / Focus
Current areas
- 01
Visibility & discovery
How people, businesses, and tools stay findable when AI systems answer, summarize, route, and act.
- 02
Measurement & tracking
How to know what’s working when clicks, cookies, referrals, and dashboards stop telling the whole story.
- 03
Agentic systems
Memory, handoff, orchestration, tool boundaries, and recovery for agents that touch real workflows.
- 04
Operational evidence
Original-data research, field notes, and shipped tools. Findings over forecasts.
03 / Artifacts
Selected artifacts
Tools I’ve built around the same layer: memory, clipboard, agent handoff, monitoring. Local-first where it makes sense, from problems I hit directly.
- 01BeetrootA local-first clipboard environment for preserving workflow context on Windows.
- 02Clipboard MCPA clipboard bridge between humans and AI agents.
- 03Share2AgentA browser-to-agent handoff surface.
- 04Agent RecallScoped persistent memory for long-running coding agents.
- 05Claude Usage DeckA small operational monitor for Claude.ai limits.
04 / Writing
Recent writing
All articles →Codex CLI managed Git worktrees: three ways to start one, and the model's tool starts from the remote default branch
A hands-on run of Codex CLI 0.162.1 on a throwaway repository: where the checkouts land, which commit each entry point begins at, why your .env and uncommitted edits stay behind, how to merge the work back, and what cleanup leaves on disk.
Claude Code skills as a supply chain: 2.2 million adoptions, no registry, and a scanner that reads the source while Python runs the cache
Reading a skill before you run it is the standard advice, and it has two holes. A copied skill has no update channel, so the copy you read can drift from its source without telling you, and for a skill that ships Python, the file you read is not always the file the interpreter loads.
Claude Code vs Codex: seven ways developers split work between the two instead of picking one
The handoffs are vendor-documented now: a review command, a session transfer, an importer in each direction. Who should get which job is documented nowhere. Seven splits, each traced to its origin and marked documented or reported, plus the sandbox defaults that differ and the integrations that were removed this year.
Context engineering starts with an inventory: you cannot budget a context window you cannot list
Every practice in the guides is a verb of choosing: trim, defer, retrieve, compact. Choosing needs a list. The one Claude Code ships itemizes your configuration by source and size, then reports the whole conversation as a single number, and nowhere says how long anything stays.
WebMCP on a real site: registering tools with document.modelContext, and why my navigator.modelContext script registers nothing
The API moved from navigator to document in May, lost three methods before that and turned its registration call into a promise after. A script written to satisfy a detector in April can expose zero tools to a current browser. The working registration, a test that needs no agent, and where a plain MCP endpoint is the better door.
Anthropic's 2026 usage policy for agent builders: the hardware stop button made it into the announcement, the subscription proxy clause did not
The hardware rules can be checked with a pulled cable. Unauthorized proxying through consumer subscriptions, responsibility for what an agent does with its tools, and a lower enforcement bar cannot be checked from outside, and they came in without comment.
05 / Contact
Get in touch
Email or Telegram both reach me. Telegram is faster.