axiom: Playwright MCP provides 25+ native browser tools to Claude Code via Model Context Protocol, enabling accessibility-tree-based automation that is 10-100x faster than screenshot/vision-based approaches

source: Browser Use Research Report 2026-02-14

genesis_action: Deploy Playwright MCP as primary browser tool for all Claude Code agents — accessibility tree snapshots replace expensive vision model calls


axiom: browser-use Python library enables LLM agents to control browsers via natural language without CSS selectors or XPath maintenance — the AI finds elements automatically using page context

genesis_action: Install browser-use for Genesis agent swarms — natural language browser control eliminates brittle selector-based automation


axiom: Dual-path browser automation is optimal: Playwright MCP for quick Claude Code interactions (screenshot, navigate, click) and browser-use for complex agentic missions (multi-page research, data extraction, form filling)

genesis_action: Wire both Playwright MCP (Tier 1, 5 min) and browser-use (Tier 2, 15 min) into Genesis execution layer as complementary tools


axiom: Puppeteer MCP is deprecated — Microsoft recommends Playwright MCP as the superior alternative with cross-browser support (Chromium, Firefox, WebKit) vs Puppeteer's Chromium-only limitation

genesis_action: Never use @modelcontextprotocol/server-puppeteer — always use @executeautomation/playwright-mcp-server


axiom: Claude Computer Use (pixel-counting vision approach) is overkill for web tasks — too slow for real-time interaction, best reserved for desktop application automation where no API or accessibility tree exists

genesis_action: Use Playwright MCP for all web automation tasks, reserve Computer Use only for native desktop app scenarios where no other option exists


axiom: WSL2 runs Playwright headless by default with zero display server configuration — no X11 or Xvfb required for agent swarm browser automation, enabling clean CI/CD-style execution

genesis_action: All Genesis browser agents run headless by default on WSL2 — only use Xvfb headed mode for visual debugging


axiom: browser-use supports all major LLM providers (OpenAI, Gemini, Claude, Groq, local Ollama) — Genesis can run browser agents on Gemini 2.5 Flash for cost efficiency or local GLM-4.6V on AIVA's Mac Mini for zero API cost

genesis_action: Default browser-use agents to Gemini 2.5 Flash via GeminiRateMaximizer, with fallback to local Ollama for cost-free overnight missions


axiom: Bot detection mitigation for browser agents requires multi-layered defense: Stealth Playwright plugin, user-agent rotation, human-like delays (built into browser-use), and residential proxies as escalation path

genesis_action: Build anti-detection config into GenesisBrowserAgent class — rotate user agents, add randomized delays, keep Stealth plugin as standard


axiom: Graphiti MCP server requires an LLM API key for entity extraction — without it, all submitted memories queue for processing but never actually get processed into the knowledge graph, creating a silent failure mode

source: Graphiti Fix Status Report 2026-02-14

genesis_action: Always verify LLM API key configuration when deploying any knowledge graph processing service — silent queue failures are invisible without explicit health checks


axiom: When remote infrastructure is inaccessible (missing SSH keys), build local processing pipelines that connect directly to the backing store (e.g., FalkorDB) and perform the same operations the remote service would — bypass the broken service, not the architecture

genesis_action: graphiti_memory_processor.py demonstrates this pattern: direct FalkorDB connection + OpenRouter LLM = full processing without SSH access to Docker container


axiom: OpenRouter serves as a universal OpenAI-compatible proxy for any LLM — use it to swap model providers without changing client code, enabling Gemini 2.0 Flash for entity extraction at ~$0.10/1M tokens through OpenAI API format

genesis_action: Use OpenRouter as the standard LLM backend for all Genesis infrastructure services that expect OpenAI API format — model-agnostic by default


axiom: The 5-system memory architecture (Supermemory + FalkorDB/Graphiti + PostgreSQL + Qdrant + Redis) creates redundancy and specialization — each system excels at a different memory pattern (search, graph, relational, vector, cache) and the Genesis Memory Hub queries all 5 in parallel

source: Graphiti Fix Status + Genesis Memory Hub

genesis_action: Never rely on a single memory backend — the Memory Hub parallel query pattern ensures no single system failure causes memory loss


axiom: FalkorDB graph operations are sub-millisecond latency with no authentication required on internal networks — direct Redis protocol connection at port 6379 gives raw graph manipulation speed that exceeds REST API overhead by orders of magnitude

genesis_action: For bulk graph operations (axiom loading, entity ingestion), use direct FalkorDB connection instead of Graphiti MCP REST endpoint


axiom: Silent failures in distributed memory systems are the most dangerous failure mode — a service that accepts input and returns success but never processes it creates false confidence in data persistence

genesis_action: Every memory write must include a verification read — write then immediately query to confirm data appears in the target store


axiom: The first live client demo requires 85%+ readiness across 8+ verification dimensions — website quality, API tokens, CRM contacts, workflow activation, hosting deployment, end-to-end testing, sales collateral, and demo script rehearsal

source: George Bunker Monday Demo Report 2026-02-14

genesis_action: Create a standardized demo readiness checklist with automated verification for each dimension — run before every client demo


axiom: GHL workflows must be manually activated in the UI — the GHL API does not support publishing workflows programmatically, creating a dependency on human action that cannot be automated

genesis_action: Always document GHL workflow activation as a manual step in deployment checklists — never promise fully automated GHL deployment


axiom: Automated pre-demo verification (API token validity, CRM contact existence, workflow status, chat widget accessibility) can increase demo confidence from 75% to 85%+ with zero human effort — script the verifiable checks, isolate the manual ones

genesis_action: Build pre-demo-check.py that validates all automatable dimensions and generates a clear report of remaining manual actions


axiom: The revenue-leak audit is the strongest sales opener for tradies — showing a business their 52/100 digital score, Grade D rating, and $35-75K/year revenue leak from missed calls creates urgency that generic product pitches cannot match

genesis_action: Lead every tradie demo with the automated audit report — quantified revenue leak > feature list every time


axiom: The $400/month price point positions AI services as a direct replacement for existing spend (e.g., LocalSearch) rather than new budget — framing as 'same price, 10x the value' eliminates budget objection entirely

genesis_action: Always anchor pricing against the client's existing spend on comparable services — replacement framing beats new-line-item framing


axiom: Demo site hosting via Netlify drag-and-drop deployment takes 2 minutes and produces an instant shareable URL — this removes hosting complexity as a barrier to client demos and enables same-day site delivery

genesis_action: Use Netlify drag-and-drop for all client demo sites — instant deployment, free tier, custom subdomain support


axiom: A complete demo package for tradies requires 6 assets minimum: demo website, business audit report, chat widget integration, GHL CRM setup, cold call script, and pricing proposal — missing any one creates a gap that can stall the close

genesis_action: Build a templatized demo package generator that produces all 6 assets from a single business input (name, phone, ABN, website URL)


axiom: 34-point automated website verification (DOCTYPE, viewport, navigation, CTAs, phone links, service cards, testimonials, FAQ, chat widget, mobile responsiveness) catches quality issues before client-facing deployment

genesis_action: Run 34-point verification suite on every demo site before client delivery — automated QA eliminates embarrassing broken elements


axiom: The demo script follows a 6-step psychological escalation: Audit (pain) -> Website (vision) -> Live Chat (proof) -> MCTB (automation) -> CRM Dashboard (control) -> Close (value comparison) — each step builds on the previous to make the close inevitable

genesis_action: Formalize the 6-step demo escalation as a reusable script template for all tradie verticals


axiom: Context management in long-running agent sessions requires a 4-layer defense: (1) StatusLine for real-time token tracking, (2) Pre-compaction anchors saving critical state, (3) Post-compaction recovery from persistent memory, (4) Session handoff protocols for graceful continuation

source: Genesis Context Management Architecture

genesis_action: Implement all 4 layers of context defense — any layer alone is insufficient, the combination provides resilient context across any compaction event


axiom: Pre-compaction flush should trigger proactively at ~50% context usage, not reactively at 90%+ — early flush preserves more context fidelity and prevents emergency state loss during unexpected compaction events

source: Genesis Immortal Session Protocol

genesis_action: Set context flush triggers at 50% (proactive), 75% (warning), and 90% (emergency) — graduated response prevents context loss


axiom: Telnyx NaturalHD voices (eucalyptus for Australian Female, marlu for Australian Male) provide premium voice quality for AI assistants at no extra cost — HD Voice is enabled by default on all Australian numbers

source: AIVA Voice Configuration 2026-02-14

genesis_action: Use Telnyx NaturalHD.eucalyptus as default voice for all Australian-market voice agents — premium quality with zero premium pricing


axiom: Telnyx voice discovery API (GET /v2/text-to-speech/voices) exposes 2,287 available voices — systematic evaluation of all voices by language, accent, and naturalness enables optimal voice selection for each market vertical

genesis_action: Build voice evaluation script that tests top 10 voices per market (AU, US, UK) against naturalness benchmarks before production deployment


axiom: The ClawdTalk revenue opportunity represents $25K-200K/month potential with 8.2/10 defensibility — conversational AI products built on top of existing agent infrastructure have high margins due to near-zero COGS once the platform exists

source: ClawdTalk Revenue Analysis (MEMORY.md reference)

genesis_action: Prioritize ClawdTalk-style products that leverage existing Genesis infrastructure — marginal cost of new products on existing platform approaches zero


axiom: The Gemini 2.5 Flash model running through browser-use creates the most cost-effective browser agent: natural language control + rate-maximized API calls + headless WSL2 execution = enterprise-grade browser automation at commodity pricing

genesis_action: Default all browser agent missions to Gemini 2.5 Flash through browser-use — optimize for cost while maintaining capability


axiom: Browser agent use cases split into two categories: competitive intelligence (scrape competitor pricing, extract feature lists, monitor positioning) and operational automation (GHL dashboard navigation, lead enrichment, E2E testing) — each requires different agent configurations

genesis_action: Build two browser agent templates: IntelligenceAgent (stealth mode, data extraction, structured output) and OperationsAgent (authenticated sessions, form filling, workflow execution)


axiom: Stagehand (Browserbase) is TypeScript-first and should be skipped for Python-first systems — browser-use offers equivalent natural language browser capabilities natively in Python with broader LLM provider support

genesis_action: Do not evaluate Stagehand for Genesis — browser-use is the correct choice for Python-first architecture


axiom: Local-first browser automation (run on WSL2, no cloud dependency) provides cost optimization, LLM flexibility, and zero vendor lock-in — the Genesis advantage over cloud browser services like Browserbase or MultiOn

genesis_action: Maintain local-first browser execution as competitive differentiator — cloud browser services add latency, cost, and vendor dependency


axiom: The graphiti-core Python SDK (v0.27.1) processes episodes into entity-relationship graphs using customizable LLM backends — 5 entities and 3 relationships extracted from a single test episode demonstrates reliable extraction quality

genesis_action: Use graphiti-core SDK for all local knowledge graph processing — proven extraction quality with configurable LLM backend


axiom: Elestio VPS instances each have unique SSH keys not shared across services — when provisioning new infrastructure, immediately save the SSH key locally and add to ~/.ssh/config to prevent future access lockout

category: infrastructure

genesis_action: Add SSH key backup to VPS provisioning checklist — every new Elestio instance key must be saved to ~/.ssh/ within 1 hour of creation


axiom: The minimum viable weekend prep for a Monday client demo is 30-45 minutes of manual actions: workflow activation (5 min), hosting deployment (2 min), live chat test (5 min), MCTB test (10 min), mobile test (5 min), and dry run (15 min) — everything else can and should be automated by agents beforehand

genesis_action: Maximize agent pre-work to minimize human weekend effort — target 30 minutes or less of manual demo prep