JIT-Context OS
Sub-3ms epistemic context runtime eliminating the Haystack Tax, prompt drift, and agent self-poisoning.
Core Rule: User Authority = 1.0. Assistant Speculation = 0.0. Runtime Tool Proof = 1.0.
The Challenge
Modern autonomous coding agents deteriorate rapidly as turn history accumulates: prompts explode past 50k tokens, attention degrades (Lost-in-the-Middle), API rate limits trigger 429 errors, and agents suffer from epistemic self-poisoning—recursively treating their own past hallucinations as ground truth.
The Architecture
A deterministic 3-tier cascade: L0 Hot-Path in local SQLite WAL (<3ms Read-Your-Own-Writes), L1 Project Scope Hysteresis (<10ms), and L2 Bounded Associative Broker (600ms fail-open). Pairs deterministically with a local Obsidian Vault (plain Markdown dossiers in projects/<project>.md and knowhow/<topic>.md) as the human-in-the-loop Single Source of Truth — replacing opaque vector databases. Protected by 10 ironclad Epistemic Invariants (I1–I10). The prompt NEVER accumulates unbounded chat history: each turn receives fixed tool declarations (100% cache hit), the latest tool output, and an adaptively compiled <ONA_CONTEXT> capsule (400–1,200 tokens).
The Verified Impact
Empirically validated on production codebases (Synthapse E2E benchmark across 45 audio modules and 199 Vitest suites): achieved a 2.44x speedup in task delivery (-59.0% wall-clock time), reduced LLM turns by 61.4% (105 rounds avoided), cut tool execution churn by 62.1%, and achieved zero runtime error loops with 100% test pass rate on the first attempt.
Wall-Clock Delivery Time⚡ 2.44× Faster (-59%)
Baseline (Haystack): 45.8 min Total Agent Turns📉 -61.4% Turns
Tool Execution Churn🎯 -62.1% Churn
JIT-Context OS: 119 tool calls Peak Prompt Volume (Turn 30+)🛡️ -98% Token Bloat
Baseline: >54,000 tokens (Haystack) JIT-Context OS: ~1,140 tokens (Capsule) | Metric Dimension | Baseline (Haystack Accumulation) | JIT-Context OS (<1.2k Capsule) | Empirical Gain |
|---|
| Wall-Clock Delivery | 2,752.6s (45.8 min) | 1,127.3s (18.8 min) | 2.44x faster (-59%) |
| Local 9B Duel (EXP-009) | 10 turns (Failed 0/4) | 4 turns (100% Pass) | Local M2 Pro beat Gemini Flash |
| Total LLM Turns | 171 turns | 66 turns | -61.4% API calls |
| Tool Execution Churn | 314 executions | 119 executions | -62.1% tool churn |
| Test Regression Loops | 7 runtime error loops | 0 error loops | Zero regression loops |
| Prompt Input Volume | >54,000 tokens (Turn 30+) | 482 – 1,140 tokens | >98% token reduction |
| Prefix Cache Hit Ratio | <18% (frequent invalidations) | >88% stable cache hits | ~74% cost reduction |
- <3ms L0 SQLite WAL
- 2.44x faster delivery
- Local 9B Beat Gemini 3.8 Flash
- 10/10 Invariants PASS
- CERN Zenodo DOI: 10.5281/zenodo.22649542
InvoiceFlow
Production document pipeline: vision OCR proposals governed by deterministic validation and KSeF accounting export.
Core Rule: The probabilistic model proposes. The deterministic engine decides.
The Challenge
Automating invoice processing across multiple business entities requires 100% arithmetic accuracy and compliance with Poland's national KSeF e-invoicing schema. Relying on raw LLM output creates dangerous liability for VAT discrepancies, duplicate accounting, and tax filing penalties.
The Architecture
A multi-stage validation cascade: Vision OCR models propose initial field extractions (Pydantic v2 schemas). A deterministic Python engine validates gross/net VAT arithmetic, checks supplier tax IDs against official registries, tracks High-Water Marks (HWM per NIP) to prevent duplicate processing, and enforces strict accounting ledger rules before generating KSeF XML packages.
The Verified Impact
Operates as an active production workflow handling continuous invoice batches. By strictly decoupling extraction proposals from deterministic validation, human review is required only for true anomalies, while 100% of arithmetic decisions remain provable and audit-proof.
- Vision OCR + Pydantic v2
- Deterministic VAT validation
- KSeF XML compliance
- High-Water Mark deduplication
- Production
Onboarding Flow
Universal schema-driven state machine decoupling complex KYC and legalisation rules from codebase changes.
Core Rule: Process changes happen in swappable schemas, zero code changes.
The Challenge
Client onboarding and employee legalisation in dynamic regulatory environments undergo constant operational adjustments. Hardcoded forms require lengthy engineering deployment cycles whenever a document requirement or form field changes.
The Architecture
A universal, schema-driven onboarding engine built on FastAPI, async SQLAlchemy 2.0, PostgreSQL with asyncpg (JSONB dynamic payload storage), and Alembic migrations. A deterministic state machine guides users through 108 datapoints defined in swappable schema files. Model assistance is strictly constrained to bounded multilingual interpretation and OCR transcription. Production integrations include magic-link authentication, iDenfy KYC biometric verification, and Google Maps address geocoding.
The Verified Impact
Eliminated engineering bottlenecks: operations teams modify workflow rules and document checklists directly in JSON schemas without redeploying backend containers or altering database migrations.
- 108 Datapoints
- Schema-driven state machine
- iDenfy biometric KYC
- FastAPI + asyncpg
- JSONB dynamic payloads
Feedby
Autonomous feedback-to-fix loop: user reports end in reviewable pull requests at the merge boundary.
Core Rule: Feedback belongs in code, not in dead ticket queues.
The Challenge
User bug reports and UX friction points frequently die in neglected backlog queues. The operational gap between a reported issue and an applied code fix erodes customer trust and developer focus.
The Architecture
An AI-native feedback widget integrated directly into client web apps, wired to a multi-agent orchestration harness (Claude Code SDK / Agent Zero / OpenHands / cmux). Triage agents classify and deduplicate reports; planning agents isolate affected source files; and execution agents draft surgical code fixes using JIT Context scoping to prevent prompt drift. Pull requests are generated with full test regression suites for review-gated human merging.
The Verified Impact
Active pilot demonstrating closed-loop issue remediation: compresses bug-to-PR cycle from days to minutes while keeping human engineers firmly in control of the final merge gate.
- Multi-agent pipeline
- Widget → PR pipeline
- JIT context scoping
- Review-gated merge boundary
- Pilot
Synthapse
Real-time generative AI techno instrument powered by Google Lyria with deterministic DSP watchdogs.
Core Rule: Generative models create the mood; deterministic DSP guarantees the sound.
The Challenge
Generative audio foundation models suffer from spectral drift, phase cancellation, and unpredictable sub-bass collisions—rendering them unusable in live club sound systems where low-end discipline is mandatory.
The Architecture
A high-performance browser instrument combining Google Lyria RealTime audio streaming, Meyda spectral feature extraction, WebGL audio-reactive shaders, and dynamic loop banks. A deterministic DSP watchdog layer continuously arbitrates audio output: enforcing sub-bass mono collapse below 120Hz, real-time kick transient alignment, and hard limiter protection. Served as the empirical testing ground for JIT-Context OS paired benchmarking.
The Verified Impact
Public live demo operational at synthapse.theones.io across four interactive surfaces (root, play, dj, and kkik hardware studio). In empirical testing, JIT-Context OS achieved 2.44x faster autonomous feature implementation on this 45-module codebase with zero error loops.
- Google Lyria RealTime
- Deterministic DSP watchdogs
- Meyda spectral analysis
- WebGL shaders
- Live Demo
UniPro OS
Workflow intelligence: screen observation → validated primitives → deterministic execution.
Core Rule: Models interpret user intent; the OS compiles and validates the plan before execution.
The Challenge
Allowing unconstrained AI agents to write and execute arbitrary desktop code on corporate machines creates severe risks of data destruction, unauthorized access, and uncontrolled side effects.
The Architecture
A multi-tier desktop operating environment (Insight → OS → Rosea). UniPro Insight monitors user operational actions on screen and extracts semantic activity primitives. UniPro OS compiles raw intent into validated Plan JSON, verifying schema conformance, tool permission registries, and security policy boundaries before invoking any OS automation APIs.
The Verified Impact
Pioneers policy-bounded computer use by inserting a deterministic compiler between visual models and system calls, turning probabilistic observations into auditable, repeatable desktop automation.
- Plan JSON compiler
- Desktop activity telemetry
- Permission registry
- Multi-tier OS architecture
Tuli.my
Relational intelligence PWA with event-sourced workflows, explicit consent, and tiered model routing.
Core Rule: Privacy is an architectural invariant, not a terms-of-service promise.
The Challenge
Consumer relational AI requires deep contextual continuity while protecting intimate personal reflections. Traditional monolithic RAG pipelines risk token cost blowouts and accidental context leakage between partners.
The Architecture
Event-sourced Progressive Web App built around cryptographic consent boundaries. A central AI Gateway routes conversational, reflective, and analytical tasks to tiered models based on required capability and cost. Context is partitioned into strictly isolated personal and shared scopes. Features include Web Push notifications, an agent-ready MCP API, and idempotent Stripe billing.
The Verified Impact
Demonstrates sustainable consumer AI economics: reduces per-turn inference costs by over 70% through tiered routing while guaranteeing that unconsented personal reflections never cross partner context boundaries.
- Event-sourced architecture
- Tiered model routing
- Explicit consent boundaries
- Agent-ready MCP API
Boocco
AI-assisted salon operations platform integrating calendar, client records, and tenant-scoped RAG.
Core Rule: Enterprise-grade scheduling and finance simplified for non-technical salon operators.
The Challenge
Independent beauty salons are trapped between predatory booking marketplace fees that siphon their clients and convoluted enterprise software designed for multi-location franchises.
The Architecture
Next.js monorepo deployed with self-hosted Supabase and PostgreSQL. Combines a high-concurrency calendar engine with an embedded pgvector RAG assistant (HNSW indexing) for instant schedule resolution and client history lookup. Implements row-level security (RLS) and strict multi-tenant scoping so salon data remains hermetically isolated.
The Verified Impact
Provides salon owners with an autonomous operating center handling real-time appointments, 2-way SMS customer confirmation, and financial tracking without marketplace commission churn.
- Next.js + Supabase
- pgvector HNSW assistant
- Row-Level Security (RLS)
- Multi-tenant isolation
Arara API
Self-healing REST gateway modernizing legacy backoffice workflows with automated token lifecycle management.
Core Rule: Never rewrite a working legacy system when you can wrap it in an indestructible API.
The Challenge
A high-volume logistics recruitment pipeline was locked behind an outdated web portal lacking public APIs, plagued by rapidly expiring session tokens, manual data entry bottlenecks, and frequent hiring cascade stalls.
The Architecture
A resilient FastAPI microservice exposing clean REST endpoints over the legacy backoffice: candidate search, operational metrics, and automated push-to-HIRED status transitions. Solved token authentication dual-path: a Manifest V3 browser extension for active session sync alongside a headless Playwright automation daemon with auto-recovery, mutex locking on token refresh, and exponential backoff.
The Verified Impact
Fully automated candidate ingestion and status updates without touching the legacy codebase, saving hundreds of hours of manual administrative clicking every month.
- FastAPI REST gateway
- Self-healing OAuth2/Session sync
- Headless Playwright fallback
- Docker & Nginx