docs: triage screenshot dump into 5 actionable issues
Ingested and analyzed 5 screenshots from issue #1275: - IMG_6187: AirLLM Apple Silicon requirements → #1284 - IMG_6125: vLLM backend for agentic throughput → #1281 - IMG_6124: DeerFlow research orchestration → #1283 - IMG_6123: Dev discipline / quality gates → #1285 - IMG_6410: SearXNG + Crawl4AI self-hosted search → #1282 Refs #1275 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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docs/SCREENSHOT_TRIAGE_2026-03-24.md
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# Screenshot Dump Triage — Visual Inspiration & Research Leads
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**Date:** March 24, 2026
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**Source:** Issue #1275 — "Screenshot dump for triage #1"
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**Analyst:** Claude (Sonnet 4.6)
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---
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## Screenshots Ingested
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| File | Subject | Action |
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|------|---------|--------|
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| IMG_6187.jpeg | AirLLM / Apple Silicon local LLM requirements | → Issue #1284 |
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| IMG_6125.jpeg | vLLM backend for agentic workloads | → Issue #1281 |
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| IMG_6124.jpeg | DeerFlow autonomous research pipeline | → Issue #1283 |
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| IMG_6123.jpeg | "Vibe Coder vs Normal Developer" meme | → Issue #1285 |
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| IMG_6410.jpeg | SearXNG + Crawl4AI self-hosted search MCP | → Issue #1282 |
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---
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## Tickets Created
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### #1281 — feat: add vLLM as alternative inference backend
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**Source:** IMG_6125 (vLLM for agentic workloads)
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vLLM's continuous batching makes it 3–10x more throughput-efficient than Ollama for multi-agent
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request patterns. Implement `VllmBackend` in `infrastructure/llm_router/` as a selectable
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backend (`TIMMY_LLM_BACKEND=vllm`) with graceful fallback to Ollama.
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**Priority:** Medium — impactful for research pipeline performance once #972 is in use
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---
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### #1282 — feat: integrate SearXNG + Crawl4AI as self-hosted search backend
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**Source:** IMG_6410 (luxiaolei/searxng-crawl4ai-mcp)
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Self-hosted search via SearXNG + Crawl4AI removes the hard dependency on paid search APIs
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(Brave, Tavily). Add both as Docker Compose services, implement `web_search()` and
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`scrape_url()` tools in `timmy/tools/`, and register them with the research agent.
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**Priority:** High — unblocks fully local/private operation of research agents
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---
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### #1283 — research: evaluate DeerFlow as autonomous research orchestration layer
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**Source:** IMG_6124 (deer-flow Docker setup)
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DeerFlow is ByteDance's open-source autonomous research pipeline framework. Before investing
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further in Timmy's custom orchestrator (#972), evaluate whether DeerFlow's architecture offers
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integration value or design patterns worth borrowing.
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**Priority:** Medium — research first, implementation follows if go/no-go is positive
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---
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### #1284 — chore: document and validate AirLLM Apple Silicon requirements
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**Source:** IMG_6187 (Mac-compatible LLM setup)
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AirLLM graceful degradation is already implemented but undocumented. Add System Requirements
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to README (M1/M2/M3/M4, 16 GB RAM min, 15 GB disk) and document `TIMMY_LLM_BACKEND` in
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`.env.example`.
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**Priority:** Low — documentation only, no code risk
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---
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### #1285 — chore: enforce "Normal Developer" discipline — tighten quality gates
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**Source:** IMG_6123 (Vibe Coder vs Normal Developer meme)
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Tighten the existing mypy/bandit/coverage gates: fix all mypy errors, raise coverage from 73%
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to 80%, add a documented pre-push hook, and run `vulture` for dead code. The infrastructure
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exists — it just needs enforcing.
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**Priority:** Medium — technical debt prevention, pairs well with any green-field feature work
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---
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## Patterns Observed Across Screenshots
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1. **Local-first is the north star.** All five images reinforce the same theme: private,
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self-hosted, runs on your hardware. vLLM, SearXNG, AirLLM, DeerFlow — none require cloud.
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Timmy is already aligned with this direction; these are tactical additions.
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2. **Agentic performance bottlenecks are real.** Two of five images (vLLM, DeerFlow) focus
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specifically on throughput and reliability for multi-agent loops. As the research pipeline
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matures, inference speed and search reliability will become the main constraints.
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3. **Discipline compounds.** The meme is a reminder that the quality gates we have (tox,
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mypy, bandit, coverage) only pay off if they are enforced without exceptions.
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