Sveriges mest populära poddar
ArchitectIt: AI Architect
ArchitectIt: AI Architect

The Architect's Builders Review: pi-mega-compact EP2.

1 tim 10 min•6 augusti 2026

Om avsnittet

Four days. That's the delta. July 31 to August 5. Version 0.11.13 to 0.20.22. Forty releases. Two hundred and seventy commits. Three hundred and sixty-three thousand lines of TypeScript across nineteen hundred files. And an entirely new architectural layer — the Vector Cortex — twenty-seven sprints, VC0 through VC8, shipped and complete as of the morning of recording.


This is episode one of "Then vs Now," a new ArchitectIT format where we review a project, wait, and measure the delta. The thesis: in the age of AI-assisted development, the interesting unit of time isn't the quarter or the sprint — it's the week. What can change in a week? What actually ships? What holds up?


Pi-mega-compact is a local context compression extension for the pi coding agent. Fully local, zero telemetry, no external API calls — a hard invariant called PREVENT-PI-004 enforced by a static scanner. It manages your context window so long coding sessions don't blow up: compressing, deduplicating, and recalling conversation history with a three-stage Trident pipeline, three-layer semantic dedup, and a RAPTOR memory hierarchy. On July 31, it was the most sophisticated open-source context management tool we'd seen. In the first episode, we did a full architecture breakdown and a gap analysis. Four gaps were identified. All four are now closed.


The RAG suite — spec-only on July 31 — is shipped. Query reformulation with TF-IDF and Reciprocal Rank Fusion. Tiered routing across L0 in-memory cache, L1 FTS5 trigram, and L2 PGlite HNSW. CRAG quality metrics. HyDE auto-activation. Provider prompt cache visibility — the gap we called embarrassing — is now a full cache economics system with a crystal compiler that models cache hit and miss patterns as actionable economic signals, plus diagnostics and breakers that trip when cache poisoning is detected. The dashboard — flagged as overengineered — was completely rebuilt with Tailwind, shadcn, Playwright smoke tests, and a settings panel. Dedup thresholds now have audit logging, false-positive rate tracking, and a soft-as-hard headroom gate.


The Vector Cortex is the headline. A new architectural layer above the compression engine: a causal cache and proof system with twenty-seven sprints across nine phases. Baseline observability. Canonical event ledger with occurrence tracking. Multi-head encoder contract with deferred ML gate. Deterministic cortical topology with graph queries. Dual-tier semantic and exact shards with mandatory reconstruction fidelity. A prompt DAG with budgeted portfolio planning. Closure optimization with transitive reduction. Exact source restoration. A self-healing derived controller with fifteen healing scenarios. Frozen range cache crystals. Provider cache economics. Cache diagnostics with breakers. A consent-bound outcome ledger. A shadow adaptive policy engine with a bounded action set. And a Rust parity artifact — a second implementation that proves the TypeScript output is byte-identical and reproducible. Six named migrations with downgrade export. A triad A/B/C resilience model with a six-state breaker state machine, write-ahead logging, and chaos tests. A statistical evaluation framework with powered non-inferiority testing, stratified bootstrap, and rollout gates at one, five, twenty-five, fifty, and one hundred percent with seventy-two-hour minimums.


Then the reveal. The commit co-author tags say Claude — but the actual inference was open-weights models routed through Plexus, an API gateway. DeepSeek, Qwen, GLM, Kimi, MiniMax. The tags are an artifact of the client, not the model identity. Every line of implementation — all four hundred and forty-three commits — was done with open models. GPT-5.6 Sol was used exactly once: to design the Vector Cortex master plan. The plan was proprietary. The build was open. A frontier model was the architect. Open models were the builders. A human was the director.

ArchitectIt: AI Architect med ArchitectIT finns tillgänglig på flera plattformar. Informationen på denna sida kommer från offentliga podd-flöden.