Kabakongo

Toronto Made. Brooklyn Raised.

[Kabakongo @kabakongo]

Between maintaining a full-time hybrid job, managing demanding, but rewarding contracts and building a start-up and trying to secure funding, one of these have to go! Or I need to move to a remote full-time role. Also I may move into infra cause so many companies need that exp.

[Kabakongo @kabakongo]

@evgeniymikholap So it’s still messed up? I wondered why my views weren’t showing up.

[Symoné B. Beez @SymoneBeez]

Black Engineers are always OVERLY qualified lol

[Kabakongo @kabakongo]

Geez https://t.co/IRhHelh1Wj

[Symoné B. Beez @SymoneBeez]

Youngest Owner in NBA History previous Apple Employee and Founder of Ubiquity.

[Kabakongo @kabakongo]

Monday morning and AWS is down 😀

[Julian Goldie SEO @JulianGoldieSEO]

Docker just changed everything for Claude users.

No more manual MCP setup nightmares.

Here's the simple process:

→ Download Docker Desktop
→ Install MCP Toolkit extension
→ Toggle tools on/off instantly
→ Connect to Claude in seconds
→ Access 11Labs, Firecrawl, Perplexity instantly

Literally one-click access to premium tools. No coding required anymore.

Save this video, you'll save hours. 💻

Want the SOP? DM me. 💬

[Riley Brown @rileybrown]

Maximize Claude (MCP Full Tutorial)

Tools
@Docker MCP Toolkit
@NotionHQ MCP Tools
@heyglif MCP Tool
@WisprFlow for voice to text

TIME STAMPS:
00:00 - INTRODUCTION
03:13 - What MCP's are and ARE NOT
05:46 - Why do we need "Integration Token"
07:00 - Our Internal Database is FOR AGENTS.
08:42 - Using the Notion MCP Tools in Claude
13:25 - Creating Claude Projects for Specific MCP Tasks
15:58 - Adding an Image Generator Workflow Tool
20:24 - Conclusion

[Kabakongo @kabakongo]

@EcZachly Idle clusters are terminated after 120 minutes. Use serverless for most jobs instead of defining min/max workers and the cluster size (yes this is more “expensive” but why waste DBUs per hour when a job can be ran in 30 minutes on serverless?). Enable photon.

[Zach Wilson @EcZachly]

Building Data Pipelines has levels to it:

- level 0

Understand the basic flow: Extract → Transform → Load (ETL) or ELT

This is the foundation.
- Extract: Pull data from sources (APIs, DBs, files)
- Transform: Clean, filter, join, or enrich the data
- Load: Store into a warehouse or lake for analysis
You’re not a data engineer until you’ve scheduled a job to pull CSVs off an SFTP server at 3AM!

level 1

Master the tools:
- Airflow for orchestration
- dbt for transformations
- Spark or PySpark for big data
- Snowflake, BigQuery, Redshift for warehouses
- Kafka or Kinesis for streaming

Understand when to batch vs stream. Most companies think they need real-time data. They usually don’t.

level 2
Handle complexity with modular design:
- DAGs should be atomic, idempotent, and parameterized
- Use task dependencies and sensors wisely
- Break transformations into layers (staging → clean → marts)
- Design for failure recovery. If a step fails, how do you re-run it? From scratch or just that part?

Learn how to backfill without breaking the world.

level 3
Data quality and observability:
- Add tests for nulls, duplicates, and business logic
- Use tools like Great Expectations, Monte Carlo, or built-in dbt tests
- Track lineage so you know what downstream will break if upstream changes

Know the difference between:
- a late-arriving dimension
- a broken SCD2
- and a pipeline silently dropping rows

At this level, you understand that reliability > cleverness.

level 4
Build for scale and maintainability:
- Version control your pipeline configs
- Use feature flags to toggle behavior in prod
- Push vs pull architecture
- Decouple compute and storage (e.g. Iceberg and Delta Lake)
- Data mesh, data contracts, streaming joins, and CDC are words you throw around because you know how and when to use them.

What else belongs in the journey to mastering data pipelines?

[Kabakongo @kabakongo]

@melvinmonetary Need to learn this!!

[Kabakongo @kabakongo]

@melvinmonetary 👀👀

[Kabakongo @kabakongo]

@melvinmonetary @grok will this boost demand for kubeflow or is this still a niche skillset? E.g. kubeflow-Spotify

[arman @armankhon]

if you’re an employed software engineer, recognize how lucky you are.

[Kabakongo @kabakongo]

@Usoholic This is what would happen.

[Kabakongo @kabakongo]

@aaditsh @grok You are an expert summarizer. I want you to watch or analyze a video and summarize it using the following template:

Title: [Insert a clear, concise title that captures the main idea]
Key Topics:
(List as bullets)

Summary:
Key Takeaways:

[Kabakongo @kabakongo]

@aaditsh @AskPerplexity You are an expert summarizer. I want you to watch or analyze a video and summarize it using the following template:

Title: [Insert a clear, concise title that captures the main idea]
Key Topics:
(List as bullets)

Summary:
Key Takeaways:

[Kabakongo @kabakongo]

@SymoneBeez People been making it too hot especially on Reddit.

[Kabakongo @kabakongo]

@SymoneBeez This is so performative. I ain't selling my Tesla.

[Kabakongo @kabakongo]

Nah this mix is crazy