Nino Chavez · demo series

ways of working_

Real working sessions with an AI agent, published as teaching demos. Verbatim messages, real production systems, honest failures — receipts, not a highlight reel.

nothing staged · personal names and private links redacted · every demo is one real session

demo 01 · delegation Twelve Messages Everything typed to take a live event from spreadsheet chaos to published social content — and the method that made the other 99% happen. forAnyone delegating real work to an AI agent — functional through deeply technical. getThe verbatim conversation, a five-principle method, the pipeline that runs it, and two honest failures. doSteal the shape: templates over outputs, constraints in the repo, judgment kept human. open the demo → demo 02 · tools The Browser Is a Shell Command Replacing 18,000 tokens of always-loaded browser-automation schema with ten shell commands and a README — and why the agent gets sharper, not weaker. forAgent users paying token tax for tools they barely touch; builders choosing between MCP and CLIs. getThe cost math, four design choices that make a tool agent-friendly, live transcripts, and where MCP still wins. doAudit your always-loaded schemas, then wrap the five operations you actually use as small composable commands. open the demo → demo 03 · enforcement Taught Once, Enforced Forever Corrections given in chat decay when the session ends. The fix is changing the agent's environment — helpers, deny-hooks, and CI ratchets that carry the rule forever. forAnyone tired of re-teaching their agent the same rule every session. getFour real guards with their origin audits, verbatim deny messages, and the five properties that keep guardrails from getting ripped out. doCount your repeated corrections, then promote them up the ladder: wrapper, hook, CI gate — stopping at the lowest level that holds. open the demo → demo 04 · memory Your Sessions Are a Corpus 2,747 agent-session transcripts, mined: reusable prompts, your corrections as standing priors, and an honest ledger of what the agent built that survived. forAnyone who has corrected an AI twice and watched the correction evaporate with the session. getThe mining loop end to end — waste audits, voice priors, graded sessions — plus the tool's own confession that it was rebuilt 12 times before being made durable. doGrep your transcripts for one counted waste number before building anything; save corrections where the next session reads them. open the demo → demo 05 · autonomy The Product That Files Its Own Tickets End users file feedback, an LLM judge triages it into GitHub Issues, an agent implements the safe ones — with the autonomy boundary in deterministic code and a human holding the only merge key. forAnyone deciding how much of an incoming-work queue to hand to an agent. getThe four-stage loop, the allowlist gate read from live source, six real tickets sorted by lane, and a run ledger whose best result was declining to fabricate a fix. doLet the model classify, never authorize: write the autonomy boundary as a small tested allowlist, and keep merging human. open the demo → demo 06 · knowledge The Registry of Landmines Some load-bearing facts are invisible to search — the code compiles and the behavior is still wrong. One registry file holds them, a derive catalog enforces them in CI, and a meta-test keeps the registry from lying about itself. forAnyone whose agent (or teammate) keeps re-learning the same expensive lesson. getThe bug that shipped twice, the token economics of pre-paid conclusions, the why/decided/currently-true split, and the registry-about-the-registry. doStart the file the second time something breaks for the same reason; derive the status, never hand-edit it. open the demo → demo 07 · verification The Agent Said It Checked "Verified" is a sentence, not a fact. A security migration passed its audit while production was broken — and the discipline that came out of it caught three more false claims building this very series. forAnyone who has accepted an AI's (or a doc's, or their own) claim that something was checked. getThe circular-audit failure mode, a prod-broke-twice case study peeled layer by layer, and the re-derivation discipline with its real budget. doAsk "checked how?" — then run that check yourself: grep the file, run the command, end at the runtime. open the demo → demo 08 · process Gates Between Agentic Stages Agents are strong inside a stage and unreliable at the boundaries. A delivery methodology built on that: deterministic gates between agentic stages — 88 versioned revisions, 14 running initiatives, and the day production published fiction. forAnyone chaining AI work across stages — draft to review, analysis to deck, prototype to production. getThe deterministic-core/agentic-shell shape, the migration-sweep incident and the inverted check it left behind, and a methodology versioned like a product. doMake artifacts declare what they are; gate every hand-off mechanically; version your process with a changelog. open the demo →