Build Production GenAI for Web3/Distributed: Depth in RAG/Agents/Fine-Tuning. Sequential Ships: Finish One Project, Then Next. Free Compute. Staff-Level Polyglot (Python/TS/Go/Java/Rust). Forked from Top Repos: LangChain/Ray/vLLM/Anchor.
As a senior SWE with TS/Java/Go/Rust/Python under your belt, this roadmap skips the ML basics (e.g., no linear algebra deep-dives)—95% prod focus: Async queues (Go Fiber patterns from awesome-fastapi), typed agent orchestration (TS LangGraph from langchain-ai/langgraph), ZK-secure bots (Rust Anchor from coral-xyz/anchor), distributed inference swarms (Java Ray from ray-project/ray). Trends: Grok-2 multimodal via xAI API (free tier hooks), ZK-ML oracles (Ritual zkML from ritual-net/zkml). Solve real pains: "Edge RAG at 10K QPS for Solana DeFi" with verifiable, fine-tunable code (LoRA via Unsloth from unslothai/unsloth—2x faster on Colab T4). Fork industry-grade: vLLM (quantized serving), Ray (actor scaling), Anchor (gas-optimized contracts). Fine-tune everything: Crypto datasets (e.g., Alpaca-style tx logs) for 90%+ domain accuracy. Output: Separate repos per project (one per phase)—each ships to Render/GCP free—staff cred for $250K+ at Anthropic/xAI/Solana Labs. Central roadmap repo links all for portfolio overview. Per-project: Turborepo root for polyglot management (turbo.json tasks: turbo run build across langs; inspired by Vercel/turborepo examples for multi-lang, e.g., Nx-like caching for Go/Rust/Python).
Philosophy: DSN+TF — Depth (2-3 core areas/project, e.g., async + RAG via LangChain fork), Ship (full metrics/users per 2-week phase—e.g., Locust benchmarks to 2K concurrent), Network (weekly PRs to vLLM/Ray/Anchor + DMs to target engs), Trends (1/project, e.g., WASM edge from Cloudflare Workers patterns), Future-Proof (ZK proofs via Zokrates, quantum-resistant via Rust crypto libs).
Duration: 16 Weeks Sequential (10-12 hrs/day: 70% code/build from forks, 15% refine/fine-tune, 15% ship/net). Track: GitHub Projects Kanban (phases/compute) + Notion dashboard (PR status, credit burns, impressions). Each project = separate repo (e.g., yourusername/edge-rag-microservice for Phase 1)—init one/week odd, refine/ship even. Central repo (ai-systems-roadmap-v4.2) hosts README/guides/links (e.g., docs/project-links.md table w/ URLs). Turborepo per repo: Manages polyglot builds/tests (e.g., turbo run lint --filter=python-backend; cache hits for Rust Cargo/Python Poetry).
Outcomes:
- Portfolio: 10 separate project repos (demos live on Render, e.g., "Multimodal Solana Bot: 99.9% uptime, 5K devnet users")—linked from central repo.
- Skills: Polyglot interop (gRPC between TS/Rust), fine-tuning expert (PEFT LoRA on Grok-2 via axolotl-ai-cloud/axolotl forks—quantized serving w/ vLLM).
- Career: 15 OSS PRs (small/high-value: e.g., "Colab hook" to unslothai/unsloth), 15 referrals (tailored DMs: "Free ZK-RAG collab? @anthropic"). Unlock: Viral project repos (1K stars total via quickstarts) + case studies ("Sequential scale: 10K QPS oracle on $0 GCP") in central repo.
Pro Tip: Leverage seniority—fork once/project (e.g., ray-project/ray for swarms), adapt patterns (e.g., Ray actors for agent chaining). Weekly: Tweet #AIEngineering2025 w/ benchmarks (tag @xAI/@solana for 500+ impressions), blog 1 prod insight (Dev.to: "Go async for Solana edge"), DM 3 engs/target co. Free compute: Scripts automate Colab queues—fine-tune 7B models on T4 w/o stalls. For separate repos: Use GitHub templates (central repo → "Use this template" for new projects) to standardize Turborepo structure. Run npx turbo run dev for hot-reload across TS/Go backends.
-
Central Repo Setup:
git clone https://github.com/yourusername/ai-systems-roadmap-v4.2.git # Hosts guides/links cd ai-systems-roadmap-v4.2 ./scripts/setup-central.sh # Clones forks, sets up Notion/GitHub Projects links -
New Project Repo (e.g., Phase 1):
- From central: GitHub UI → "Use this template" → Name
yourusername/edge-rag-microservice. - Or CLI:
gh repo create yourusername/edge-rag-microservice --template=yourusername/ai-systems-roadmap-v4.2 --clone cd edge-rag-microservice npm install # Installs Turborepo (pnpm/turbo from package.json) ./scripts/setup.sh # Lang inits: Poetry (Python), Go mod, Cargo (Rust), Maven (Java) + fork clones (e.g., vllm-project/vllm into packages/python-backend/src/forks/) npx turbo run build # Builds all packages (caches Rust/Python)
- From central: GitHub UI → "Use this template" → Name
-
Build Phase 1 (Edge RAG):
npx turbo run dev --filter=python-backend # Starts FastAPI + Go Fiber # Or: cd packages/python-backend && poetry run python rag/chain.py --query "Solana tx anomaly?" -
Deploy (Free):
cd infra docker-compose up --build --free # Local Qdrant/Redis; hooks to GCP e2-micro/Render # Or: npx turbo run deploy # Turborepo task: gcloud run deploy across services -
Test & Benchmark:
npx turbo run test # Runs pytest/cargo test/go test across packages (80% cov) cd scripts && python benchmark-locust.py --users 200 --spawn-rate 10 # Free local Locust -
Fine-Tune Example:
Openpackages/python-backend/examples/quickstart-rag.ipynbin Google Colab: Loads Unsloth (from unslothai/unsloth fork), fine-tunes Llama-3 on 1K crypto samples (e.g., Solana tx JSONs)—exports to vLLM serving. Push tuned model to HF Spaces (free endpoint). Runnpx turbo run lintpost-import.
Demos:
- Edge RAG Live — Async Python/Go endpoint (from Phase 1 repo).
- Solana Bot Explorer — Rust Anchor deploy (from Phase 8 repo).
(Updatedocs/project-links.mdin central repo w/ all URLs post-ship.)
Sequential phases: Odd weeks = Build (core + trend dive, fork top repos for patterns; init new repo w/ Turborepo). Even weeks = Refine/Ship (fine-tune/benchmarks via free hacks, PRs, net/DMs; push to repo). All 10 projects covered (Phases 1-8 core 8; W16 capstone integrates 9-10: Multi-Tenant SaaS + Full Platform as refinements in Phase 8 repo). 1 trend/project (e.g., Grok-2 multimodal in Phase 3). Stacks: Polyglot progression (Python AI core → TS UIs → Go perf → Java orch → Rust Web3). Each repo: Standalone Turborepo (turbo.json pipelines: build/test/deploy; e.g., turbo run build --filter=go-backend caches Go binaries).
| Phase | Weeks | Project | Key Fork | Stack | Outcome |
|---|---|---|---|---|---|
| 1 | 1-2 | Edge RAG Microservice Trend: Edge Inference (MLX/Grok-2) |
vllm-project/vllm (quantized async); ml-explore/mlx (Apple edge) | Python 3.12 • FastAPI • Go (Fiber) • Docker/WASM • vLLM/MLX • Qdrant • Redis | <300ms edge latency; 200 req/min benchmarked (Locust local); 100+ real queries shipped on Render free. Repo: yourusername/edge-rag-microservice (links to central). |
| 2 | 3-4 | Enterprise Knowledge Search Trend: Graph-RAG (Neo4j integration) |
langchain-ai/langchain (hybrid chaining); neo4j/graphrag (structured retrieval) | LangChain • Python/Go • Cohere/Grok Embeddings • Redis/Neo4j • Qdrant | 97% recall pipeline; 2K docs indexed; <150ms queries w/ caching (85% hits). Repo: yourusername/enterprise-knowledge-search (imports Phase 1 RAG). |
| 3 | 5-6 | Multi-Source Research Agent Trend: Multimodal Agents (Vision+Text) |
langchain-ai/langgraph (async planning); crewaiInc/crewai (tool chaining) | LangGraph • AsyncIO • Node.js/TS • Slack/Discord API • Grok Vision API | 15+ tasks/day automated; multimodal summaries (e.g., tx images + text); 95% completion CRON. Repo: yourusername/multi-source-research-agent (uses Phase 2 retrieval). |
| 4 | 7-8 | Fine-Tuned Domain Expert Trend: ZK-Verified Fine-Tuning |
huggingface/peft (LoRA adapters); axolotl-ai-cloud/axolotl (train scripts); ritual-net/zkml (proof hooks) | HF Transformers • PEFT • Unsloth/Colab • Rust (tch-rs + Zokrates) • vLLM • BitsAndBytes | 88%+ domain accuracy (fintech tx); <800ms ZK-proof inference; fine-tuned on 1K samples (Colab T4). Repo: yourusername/fine-tuned-domain-expert (tunes Phase 1/3 models). |
| 5 | 9-10 | Autonomous Research Agent Trend: Swarm Agents (Ray Actors) |
crewaiInc/crewai (reflection loops); ray-project/ray (actor swarms); langchain-ai/langgraph (RAG chaining) | CrewAI • LangGraph • vLLM • Notion API • Next.js/TS • Ray Actors | 75+ reports generated; UI-triggered swarm pipeline (Next.js streaming); 20+ sources cited/report. Repo: yourusername/autonomous-research-agent (chains Phases 2-4). |
| 6 | 11-12 | Distributed RAG Orchestrator Trend: Edge Swarms (WASM Distro) |
ray-project/ray (scaling); lydtechconsulting/introduction-to-kafka-with-spring-boot (events); confluentinc/kafka-go (brokers) | Ray • Java (Spring Boot + Akka) • Kafka • Redis Streams • Docker Compose/WASM | 2K+ concurrent queries; 99.95% edge availability; 10x throughput via fault-injection (Chaos Mesh free). Repo: yourusername/distributed-rag-orchestrator (orchestrates Phases 1-5). |
| 7 | 13-14 | AI Observability Dashboard Trend: AI-Native Observability (LangFuse + OTel) |
langfuse/langfuse (LLM tracing); ajeetraina/aiwatch (React dashboards); Weights & Biases/wandb (metrics) | LangFuse • Prometheus • Grafana • React/TS • Node.js • GitHub Actions/ArgoCD | Alerts on <1s drift/retrieval hallucinations; zero-downtime CI/CD; 10K requests tracked publicly. Repo: yourusername/ai-observability-dashboard (monitors all prior repos). |
| 8 | 15-16 | AI-Powered Solana Bot (Capstone Integration) Trend: ZK-ML Oracles (Chainlink CCIP) |
coral-xyz/anchor (contracts); sendaifun/solana-agent-kit (AI bots); chainlink/chainlink (oracles) | Rust • Anchor • Solana Web3.js/TS • Python (solana-py) • CrewAI • Grok Oracles • CCIP | 2K tx/hr analyzed; ZK-verified DeFi spotting (0 failures in 50 executions); integrates SaaS/UI/obs from prior (500-user bundled, <2s latency, post-quantum secure). Repo: yourusername/ai-powered-solana-bot (capstone: bundles 9-10 as subdirs/links). |
Capstone Note (W16 Refinement): Bundle Phases 1-7 into full platform (Multi-Tenant SaaS + Optimization): gRPC interop (GoogleCloudPlatform/microservices-demo fork), AWS/GCP free multi-tenant (JWT/OAuth via next-auth). Outcome: 10K users flagship; Product Hunt launch. Add as submodules/links in Phase 8 repo.
Leverage seniority: Script automations (Go cron for GCP status, Python for Colab queues). Est. $0–$20 total. Track in Notion: "Burn: 5 hrs Colab W4." Per-repo: Add ./scripts/free-hacks.md (e.g., Phase 4: Colab Unsloth guide). Turborepo task: turbo run free-benchmark (runs Locust across packages).
| Need | Free Hack | Fallback (Low-Cost) | Tie-In (Phase/Week) | Industry Pattern |
|---|---|---|---|---|
| Fine-Tuning (LoRA/PEFT) | Google Colab Free (T4 GPU, 12GB; Unsloth.ai from unslothai/unsloth—2x faster single GPU, queue ~1-2 hrs); Kaggle Notebooks (P100/T4, 30 hrs/wk); HF Spaces (free CPU/GPU endpoints for serving). | RunPod spot A100 (~$0.20/hr; Go bidder script <10 hrs). | Phases 4/5 (W7 refine); axolotl fork w/ Unsloth hooks. | Fork huggingface/peft: Add Colab export (small PR). |
| ZK Proof Gen | Local Rust (Zokrates/libsnark from ventali/awesome-zk—CPU toy proofs); Solana devnet (free tx via Light Protocol); SnarkyJS (TS browser-local verifies). | GCP free e2-micro VM (burst GPU; $300 credits/90 days). | Phases 4/8 (W8 refine); simulate 200 tx. | Fork sendaifun/solana-agent-kit: Local ZK example PR. |
| Benchmarks (10K QPS/Locust) | Locust/JMeter (free Python/OpenJDK; local multi-core or GCP f1-micro); k6 OSS (cloud-free to 5K QPS laptop); Solana devnet RPC (free tx sims). | AWS free t3.micro (750 hrs/mo; $100 credits). | Phases 1/6 (W2/12 ship); ramp 1K→10K. | Fork ray-project/ray: Locust integration PR. |
| General Infra (Deploys/Ray) | GCP Always Free (e2-micro, 30GB; $300/90 days); AWS Free ($100/6 mos; Activate $1K+ solo); Azure Founders Hub ($150K credits—apply as AI dev). | Weekly apps: GCP Startup ($100K/2 yrs), AWS Activate ($1K–$100K). | All (weekly); 95% local Docker/WASM. | Fork GoogleCloudPlatform/microservices-demo: Free gRPC hooks. |
Pro Hacks: ./scripts/monitor-colab.py (queues joins); Unsloth for 4x VRAM savings (7B on T4). If stall: CPU fallback (Rust tch-rs)—still ships. Doc "Free ROI: Tuned on $0, 99.9% uptime" in each repo's README. Turborepo: Cache free hacks (e.g., turbo run finetune --cache=false for Colab exports).
Use central repo as GitHub template: Each project repo is a Turborepo root (package.json w/ turbo, turbo.json pipelines: build/test/lint/deploy across polyglot packages; inspired by Vercel/turborepo polyglot examples—e.g., cache Go/Rust builds like Nx). Standalone: Lang packages in packages/; apps/ for entrypoints (e.g., Next.js UI). High stars/forks: Badges/shields, quickstarts (notebooks=engagement), contrib ease (filter by package), Mermaid diagrams (visuals). Deploy: turbo run deploy (orchestrates docker-compose/GCP). Polyglot: gRPC/REST comms (infra); cross-repo deps via npm/Cargo publish (e.g., publish Phase 1 as @yourscope/edge-rag).
[project-repo-name]/ # e.g., edge-rag-microservice (Turborepo root; Badges: stars, coverage, license)
├── README.md # Project-specific (adapt from central: "Phase 1: Edge RAG")
├── CONTRIBUTING.md # "Fork packages/lang, PR small (e.g., async hook)"
├── LICENSE (MIT)
├── turbo.json # Pipelines: {"build": {"dependsOn": ["^build"], "outputs": ["dist/**"]}} for polyglot caching
├── package.json # Turborepo deps: {"devDependencies": {"turbo": "^2.0.0", "typescript": "^5.0"}}
├── pnpm-lock.yaml # Or yarn.lock (pnpm for TS/Go interop)
├── .github/workflows/ # CI: lang-specific (python-ci.yml: pytest + coverage; turbo-integrated)
│ ├── rust-ci.yml
│ ├── deploy.yml # Free Render/GCP on push (turbo run deploy)
│ └── issue-templates/ # Bug/feature
├── docs/ # Project visuals/guides (Mermaid for stars)
│ ├── architecture.mmd # ```mermaid graph TD; FastAPI --> Fiber --> Qdrant ```
│ └── api-specs/ # OpenAPI YAML (e.g., rag-openapi.yaml)
├── examples/ # Plug-n-play (forkable: 500+ forks like openai/openai-cookbook)
│ ├── quickstart.ipynb # Colab: Unsloth fine-tune + vLLM serve
│ └── demo.ts # TS playground: Query endpoint
├── apps/ # Turborepo apps: Entry points (e.g., UI/server)
│ └── api-server/ # Next.js/FastAPI wrapper (package.json: "dev": "turbo run dev --filter=api-server")
│ ├── src/ # App-specific (e.g., routes.ts)
│ └── next.config.js # If TS-heavy
├── packages/ # Core: Turborepo packages (workspaces; lang-specific)
│ ├── python-backend/ # RAG core (pyproject.toml/Poetry; turbo task: "build": "poetry build")
│ │ ├── src/
│ │ │ ├── rag/ # chain.py (LangChain fork: async retrieve)
│ │ │ └── agents/ # tool_call.py (CrewAI patterns)
│ │ ├── tests/ # test_chain.py (pytest-asyncio, mocks Qdrant)
│ │ └── examples/ # inline_finetune.py (Unsloth loader)
│ ├── go-backend/ # Async perf (go.mod; turbo: "build": "go build")
│ │ ├── cmd/server/ # main.go (Fiber router + Redis queue)
│ │ └── internal/ # queues/redis_queue.go (awesome-fastapi Go ex)
│ ├── java-backend/ # If needed (pom.xml/Maven; turbo: "build": "mvn compile")
│ │ └── src/main/java/com/project/kafka/ # Orchestrator.java
│ └── rust-web3/ # If needed (Cargo.toml; turbo: "build": "cargo build")
│ └── src/bot.rs # Anchor + tch-rs
├── infra/ # Project-shared (docker-compose.yml: Qdrant/Redis/Ray head; turbo deploy task)
│ ├── docker/compose.yml # Services: python-backend:ports 8000
│ ├── k8s/ # Optional Minikube manifests (free local K8s)
│ └── terraform/gcp-free.tf # e2-micro + Cloud Run
├── scripts/ # Utils (bash/Python/Go: High usability=stars)
│ ├── setup.sh # Lang inits + fork clones (e.g., git submodule add vllm-project/vllm)
│ ├── monitor-colab.py # Queue poller (smtplib alerts)
│ └── benchmark-locust.py # Distributed sim (k6 fallback; turbo: "benchmark": "python scripts/benchmark-locust.py")
└── .gitignore # Langs: __pycache__, target/, node_modules/; turbo-cache/
Why This Structure? Prod-ready: Turborepo caching (e.g., Rust Cargo/Python Poetry—2x faster rebuilds like Vercel/turborepo polyglot ex), CI per package (green builds=trust), examples=quick contribs (stars like huggingface/transformers: notebooks), docs=Mermaid (visual forks). Polyglot: turbo.json deps (e.g., "test": {"dependsOn": ["build"]}); gRPC/REST (infra); cross-repo: Publish artifacts (e.g., Phase 1 npm pkg). For capstone (Phase 8): Add submodules/ dir w/ git submodules to prior repos. Run npx turbo graph for dep viz.
- Fork the Project Repo: e.g.,
git clone yourfork/edge-rag-microservice(isolate per phase). - Add Value: Small PRs—e.g., "WASM edge hook in packages/go-backend" (lint via CI: gofmt/pytest/cargo fmt;
turbo run lint). - Test & Push:
npx turbo run test→git push→ Create PR (link to phase, e.g., "Phase 1: Async retriever"). - Star/Fork Cred: Tag in tweets ("Forked vLLM—Edge RAG live! #AIEngineering2025"); update central
docs/project-links.md.
See CONTRIBUTING.md for templates (e.g., "What trend? Free hack?"). Issues: Use .github/ISSUE_TEMPLATE (bug/feature/PR-review). Maintainers: Quick merges prioritized (e.g., 24hr CI feedback). Cross-repo: PRs to upstream forks (vLLM/Ray) from your project repos.
Top Industry Forks (Adapt patterns: e.g., vLLM's PagedAttention for quantized RAG; per-repo: Clone into packages/lang/src/forks/):
- AI Core: langchain-ai/langchain (RAG chaining—fork for async Go retriever); vllm-project/vllm (serving—add WASM hooks).
- Agents/Distributed: ray-project/ray (swarms—Java actors for Kafka); crewaiInc/crewai (reflection—TS tool-calling PR).
- Fine-Tuning: unslothai/unsloth (free LoRA—Colab speedups); huggingface/peft (adapters—ZK verify fork).
- Web3: coral-xyz/anchor (Solana contracts—gas opts); sendaifun/solana-agent-kit (bots—Grok oracle integration).
- Full Stack/Infra: alephmatic/full-stack-ai (Next.js AI—gRPC streaming); GoogleCloudPlatform/microservices-demo (polyglot—free GCP deploys).
- Turborepo Polyglot: Vercel/turborepo (caching ex); Nx/polyglot (inspo for Go/Rust tasks).
Trends (2025 Releases): Grok-2 API (xAI multimodal—free tier); Ray 3.0 (edge actors); Anchor 0.30 (ZK compression). Future-Proof: Rustdale (quantum-resistant from rust-crypto). Per-repo: Add docs/resources.md w/ phase-specific forks.
Inspired by: openai/openai-cookbook (examples). Thanks to xAI/Solana communities. Questions? Open issue—let's collab on PRs!
Depth. Ship Sequential. Network Integrated. Fine-Tune Prod. Land Staff Role.