Mwangi

Software Engineer | AI Engineer | AI Automations

[Suraj Sharma @suraj_sharma14]

CANCEL your weekend plans.

You NEED to:

• Build a RAG system that cites sources with page numbers
• Implement hybrid search (dense + sparse) for better retrieval
• Add reranking with cross-encoders for top-10 accuracy
• Set up chunking strategies (500 tokens, 50 overlap minimum)
• Build query expansion for better recall
• Add metadata filtering for scoped retrieval
• Implement citation grounding to prevent hallucinations
• Create an eval harness with 50+ golden test cases
• Track retrieval metrics: hit rate, MRR, NDCG
• Add fallback to web search when confidence is low
• Build query rewriting for ambiguous questions
• Implement parent document retrieval for context
• Add embedding caching to reduce latency 80%
• Use colbert or late interaction for better accuracy
• Build a RAG dashboard showing retrieval quality
• Test with adversarial queries that should return nothing
• Document your chunking strategy and why it works
• Benchmark against naive RAG and show improvement

You have way too much to do.

Bookmark & Repost.

[Chess.com @chesscom]

Attack is the best form of defense. ♟️

[Anuj @anujcodes_21]

Claude FULL COURSE 1 HOUR (Build & Automate Anything)

[Justine Moore @venturetwins]

Me using Claude Opus 4.8 to rename a file

[Suraj Sharma @suraj_sharma14]

If you don't know where to start with AI, here's what you need to do:

> Learn Claude
> Master n8n workflows
> Set up a local LLM using Ollama
> Self-host n8n on Docker
> Learn AI agents inside n8n
> Build a personal AI assistant
> Get good at writing AI prompts
> Pick a niche you love
> Replicate a proven SaaS with AI
> Build 3 to 5 AI agent demos
> Start posting what you're building
> Build a lead gen machine with AI

(save it)

[Mwangi @joeeeazyy]

@ChelsTransfer Rudiger
Alvarez
Ndiaye

[ỌBA DÉLÉKÈ  👑 @ObaDeleke]

My project:

[Edison @CodeEdison]

Skills That Pay in the AI Era (2026)

AI/ML: Python, PyTorch, Transformers, Fine-tuning, Evaluation
AI Stack: RAG, Vector Databases, Embeddings, Prompt Engineering, Agents
Backend: Node.js, Go, Rust, API Design, System Design
Frontend: React, Next.js (for AI apps & dashboards)
APIs: REST, GraphQL, gRPC
Databases: PostgreSQL, Redis, Vector DBs
DevOps: Docker, Kubernetes, CI/CD, Terraform
Cloud: AWS/GCP/Azure, Serverless, Edge (Cloudflare, Vercel)
MLOps: Model serving, MLflow, Monitoring, Data pipelines
Security: Auth, API Security, Zero Trust
AI Productivity: Copilot, Cursor, Code review with AI
Core CS: Data Structures, Networking, OS, Scalability

[Elon Musk @elonmusk]

Full stack engineering

[Vaishnavi @_vmlops]

Roadmap to Become an Agentic AI Engineer in 2026

https://t.co/wgts1ttEqh

[Nav Toor @heynavtoor]

If I had to become an AI engineer in 90 days, I would not start with courses.

I would build projects from these 10 GitHub repos.

1. LangChain
The LLM application framework on almost every AI engineer JD. If you want to build production LLM apps, start here.
repo → https://t.co/alIh6rDDIu

2. LangGraph
Stateful agents as graphs. The repo JDs mean when they say "agentic workflows."
repo → https://t.co/bzVBn9uecV

3. LlamaIndex
The go-to framework for RAG and document agents. Every "retrieval pipeline" JD points here.
repo → https://t.co/m4oJ9FiCrX

4. CrewAI
Multi-agent teams with roles and tasks. Used in production by enterprises across the Fortune 500.
repo → https://t.co/0xohE065sD

5. Qdrant
A production vector database written in Rust. JDs name it alongside Pinecone, Chroma, and FAISS.
repo → https://t.co/ziSSXW2dzZ

6. Ragas
The standard framework for evaluating RAG pipelines. Hallucination, faithfulness, relevancy, all measurable.
repo → https://t.co/vgOInvREU5

7. Ollama
Run open-source LLMs locally in one command. JDs ask for local inference for cost and privacy reasons.
repo → https://t.co/gyZhUdzsnZ

8. Awesome MCP Servers
Model Context Protocol is the newest skill on JDs. This repo indexes every production MCP server out there.
repo → https://t.co/ejVOgkRJDX

9. Awesome LLM Apps
100+ end-to-end templates for RAG, agents, multi-agent teams, voice agents, and MCP. Real working code.
repo → https://t.co/oXrD5A8K6a

10. AI Agents for Beginners
Microsoft's free 12-lesson curriculum covering the full AI agent stack. No paywall, no signup.
repo → https://t.co/7dNsDw6bTj

AI engineer job descriptions in 2026 keep asking for the same things: RAG, agents, vector databases, evals, MCP.

These 10 repos teach all of it.

Pick one. Build one project. Push it to GitHub. That's how you start.

100% free. 100% open source.

[Snake @sssnakeInCrisis]

how long did it take you to type that out?

[Moe @moneyacademyKE]

Four Kenyan startups have been selected for the Google for Startups Accelerator Africa cohort from nearly 2,600 applicants across the continent.

They include
— Coamana
— Duck
— ReportsAI
— VunaPay

[Anupam @Anupam_Devops]

Your Docker image is 2.1GB. A colleague's similar image is 180MB. What are 5 techniques they might be using that you're not?

[Smart👨‍💻 | Software Engineer @smartnakamoura]

If you are a software engineer who wants to upskill in system design, bookmark these 10 sites:

[kapilansh @kapilansh_twt]

A junior dev asked his Senior: "What separates a $100k engineer from a $300k one?"
The senior didn't say React. He didn't say AI tools. He opened MIT 6.824 Distributed Systems and said - "Start here"
This course will break your brain in the best way:
• How Raft consensus keeps systems alive when servers die
• How Google File System stores data at a scale most devs can't imagine
• Why your app survives or collapses - under real pressure
• The consistency vs availability decision that every big system loses sleep over

Framework devs are everywhere

Engineers who understand why systems fail and how to stop it are not

That's the gap. That's the salary difference

[Jaydeep @_jaydeepkarale]

Do this:

1. Open AWS and create an account.

2. Go to EC2, spin up an instance, generate a key pair, and SSH into it from your local system. Just play around install Nginx, deploy a Node app, break things, fix them.

3. Decide to launch something? Go to Security Groups open ports for HTTP (80), HTTPS (443), and SSH (22).

4. Grab your instance’s public IP, open it in your browser, and you’ll see your app running on the cloud.

5. Start scaling ? create another EC2 instance and set up an Application Load Balancer to route traffic.

6. Tired of adding instances manually? Use Auto Scaling Groups (ASG) define min/max instances, attach a launch template/AMI of your app, and AWS will scale automatically based on CPU or request load.

7. Getting millions of requests and your DB is choking? Use Kafka or SQS for buffering high-throughput workloads. Learn more about async

8. Store images, videos, or backups? Use S3 connect it from your app via the SDK, and make a file uploader.

9. Use RDS for managed databases (MySQL/Postgres). AWS handles backups, scaling, and maintenance.

10 Use CloudWatch to monitor your instances, logs, and metrics. Set up alerts when CPU spikes or memory usage is high.

11. For networking, explore VPCs subnets, route tables, gateways. This is where you learn how AWS isolates traffic securely. You will learn really well about networking here. Just create a vpc and play around

12. Once you’re comfortable, try Terraform to automate infra because that's 100X easier to manage state.

Stage 13: Say Fuck AWS for stealing money and buy your own VPS, set up Docker, or use Coolify for one-click PaaS setups.

[David Maraga @dkmaraga]

I will face corruption head on, head on.

[Ciru Muriuki 🇰🇪🪬 @CiruMuriuki]

And suddenly someone decided Christians were being persecuted and he needs to save them. 🤭

[mailler @_mailler]

So, M-Tiba got hacked and according to the hackers, Kazu, the data leak contains 17,158,105 files and is 2.15TB in size.
They have provided a sample of ~2GB that contains patients diagnosis data by the health providers, and PII leak for Kenyans who use that.
Here's a thread.
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