kirobreika

[Rishabh @Rixhabh__]

7 GitHub repos that can save you hundreds of dollars every year:

1. https://t.co/zBVSBNgAhw
Download videos from YouTube and hundreds of other sites in multiple formats. Supports audio extraction, playlists, subtitles, and more.

2. https://t.co/tbexdxldAN
OpenAI’s speech recognition model that transcribes audio and video into text with impressive accuracy across 99 languages.

3. https://t.co/mGKQbmO3Di
An open-source alternative to Calendly. Let people book meetings, self-host it if you want, and keep full control of your scheduling data.

4. https://t.co/6jftTSKFic
A free, open-source UI/UX design platform with real-time collaboration. A popular alternative to paid design tools.

5. https://t.co/K2T796Ofgr
A secure, open-source password manager. Store, sync, and manage passwords without being locked into proprietary software.

6. https://t.co/YHBvLakkdU
An open-source AI model trained on billions of financial data points to analyze market trends and price movements.

7. https://t.co/UmEXx1VmQV
Drop your raw footage into a folder, tell Claude Code what you want, and it automatically edits the video, removes filler words, adds subtitles, color grading, and exports a polished final video.

[HashiCorp, an IBM Company @HashiCorp]

Terraform MCP Server 1.0 is now GA. Connect AI assistants like GitHub Copilot, IBM Bob, and Claude Code to Terraform workflows to reduce manual effort, minimize context switching, and deliver infrastructure faster — with consistency and security built in. https://t.co/YiLxh8UaIh

[Ethan @ethanwith_AI]

How To Master Claude In One Week
Follow me (@ethanwith_AI

[Shubh @TheSuperEng]

These No BS engineering blogs are a goldmine for serious backend and infra engineers:

1. Netflix TechBlog
2. Uber Engineering
3. Engineering at Meta
4. Cloudflare Blog
5. Stripe Engineering
6. Slack Engineering
7. GitHub Engineering
8. Airbnb Tech Blog
9. Dropbox Tech Blog
10. DoorDash Engineering
11. Pinterest Engineering
12. LinkedIn Engineering
13. Spotify Engineering
15. Shopify Engineering
16. Datadog Engineering

[Vaibhav Sisinty @VaibhavSisinty]

A scientist in Denmark just open-sourced the smartest job application system I've seen. Built entirely on Claude Code. 🤯

He's a PhD geophysicist. Not a startup founder. Built it because he needed it himself.

You fork the repo, fill in your background once, and it runs a full pipeline for every job you apply to.

It reads the job posting and scores how well you fit. Drafts a tailored CV picking only the experience that matches.

Writes a cover letter framed around what you'd bring to the role.

Then a second AI agent reviews the first agent's work, finds weaknesses, and the first agent revises. Compiles everything into clean PDFs.

[Shubh @TheSuperEng]

"Effective Go" is the most powerful FREE resource on the internet to study Go. But it's too long. So I trimmed down the most important concepts:

1. Name things the Go way
- Package names should be short, lowercase, and simple.

Use:
> bufio.Reader
> https://t.co/nggyOF7dRl
> io.Reader

Not:
> bufio.BufReader
> ring.NewRing
> io.IReader

The package name is already part of the API.

2. Keep control flow flat
- In Go, readable code usually means early returns.
- Avoid deeply nested if/else chains.
- Handle the error. Return early.

3. Use multiple return values properly
- Go doesn't hide failures behind exceptions.
- Return both the value and the error.

Example:
> value, err := doSomething()
> if err != nil {
> return err
> }
> return value, nil

4. Use defer for cleanup
- Open a file? Defer the close.
- Lock a mutex? Defer the unlock.
- Acquire a resource? Defer the release.
- defer keeps cleanup close to setup, making code easier to maintain and harder to break.

5. Understand slices
- Slices are not arrays.
- They are lightweight descriptors that point to an underlying array.
- This means appending, passing, or modifying slices can affect the same underlying data.

Always write:
> s = append(s, x)

Not:
> append(s, x)

Because append can return a new slice header.

6. Design around useful zero values
- Good Go types should work even when they are not explicitly initialized.
- The zero value should be useful whenever possible.

Examples:
> bytes.Buffer
> sync.Mutex
> empty slices
> zero-value structs

- This makes APIs simpler and reduces unnecessary constructors.

7. Keep interfaces small
- In Go, interfaces are usually tiny.
- Don't create large interfaces too early.
- Define behavior with the smallest possible method set.

Examples:
> io.Reader
> io.Writer
> fmt.Stringer
> http.Handler

- Accept interfaces. Return concrete types.

8. Don't panic for normal errors
- "panic" is not for regular failures.
- Use panic only when the program reaches a truly unrecoverable state.
- For normal errors, return an error.

Bad:
> panic("file not found")

Good:
> return fmt.Errorf("open config: %w", err)

Let the caller decide how to handle the failure.

9. Share memory by communicating
- Go's concurrency model is built around goroutines and channels.
- Don't communicate by manually sharing memory everywhere.
- Use channels when ownership and coordination matter.
- But don't spawn goroutines blindly.
- Every goroutine should have a clear purpose.
- Every channel should have a clear owner.

10. Use gofmt. Always.
- Don't waste time arguing about formatting.
- Don't manually align code.
- Don't debate tabs vs spaces.
- Don't create your own formatting style.

Go already solved this.

Run:
> gofmt

And move on.

Hey..... @TheSuperEng it is.
We discuss god tier software only.

[Rohit Ghumare @ghumare64]

I moved from DevOps into AI-native infrastructure.

Here is what I would learn first:

1. MCP

Not just what it is.

Understand why agents need a standard way to discover and call tools.

MCP is becoming the interface layer between agents and real systems.

2. Agent skills

Tools give agents access.

Skills give agents procedures.

This is where runbooks, debugging steps, deployment workflows, and review patterns become reusable.

3. Browser automation

A lot of real work still happens across messy web surfaces.

Dashboards.
Docs.
CRMs.
Cloud consoles.
Internal tools.

Agents that can safely use the browser will unlock many workflows APIs never covered.

4. Memory

Context windows are temporary.

Useful agents need project memory, environment memory, decision history, and user preferences.

Not everything should be in the prompt.

5. Evaluation

If an agent changes infra, writes code, opens PRs, or triggers workflows, you need feedback loops.

Tests.
Logs.
Traces.
Approvals.
Rollback paths.

Without evals, agents are just confident automation.

6. Permissions

This is the most underrated part.

What can the agent read?
What can it write?
What needs approval?
What gets logged?
What can be reverted?

AI-native infrastructure is not about giving agents unlimited access.

It is about giving them safe, discoverable surfaces.

7. Platform engineering

DevOps is not going away.

It is evolving.

The next platform team will not only build CI/CD, Kubernetes, observability, and internal tools.

They will build the surfaces agents use to operate those systems.

My take:

DevOps engineers are in a very good position right now.

You already understand systems, incidents, automation, infra, and developer workflows.

Now add agents, MCP, memory, skills, browser automation, and evals on top.

That is AI-native infrastructure.

[Muhammad Ayan @socialwithaayan]

35 WEBSITES GOOGLE DOESN'T WANT YOU TO KNOW

1. Evomap .ai — open source, self-hosted, and your data never leaves your own infrastructure.
https://t.co/oQEbudhJiD

2. NotebookLM — turns docs into podcasts
https://t.co/prs9AWkTFa

3. Napkin AI — turns text into diagrams
https://t.co/W14RHb2JZG

4. Ideogram — generates text in images perfectly
https://t.co/qRg1yfkZMC

5. Suno — makes full songs from a prompt
https://t.co/RtR8iK1wM4

6. HeyGen — clones your face into videos
https://t.co/V89yi3ymi2

7. Kling AI — best AI video generation
https://t.co/7U7lvYoYui

8. ElevenLabs — clone any voice instantly
https://t.co/DB46fO9jUU

9. Gamma — AI presentations in seconds
https://t.co/abgvkUxotm

10. Perplexity — AI search with real sources
https://t.co/lJNsbNb97N

11. Pika — animate any image into video
https://t.co/Y1ziroISrN

12. Runway — cinematic AI video generation
https://t.co/0V22FRYKDq

13. Cursor — AI code editor that builds for you
https://t.co/ZZ5a58hmjV

14. v0 — generate UI components with AI
https://t.co/AFa9p7nwkr

15. Lovable — turn ideas into working apps
https://t.co/TKYBXZ7zU1

16. Descript — edit video by editing text
https://t.co/YQUjUSEgzM

17. Opus Clip — auto cut long videos into shorts
https://opus.clip

18. Krea AI — real time AI image generation
https://t.co/pcm9ExwVf9

19. Magnific — upscale any image with AI
https://t.co/37zwz0b2Ix

20. Viggle — make characters move realistically
https://t.co/HXXEtfQc4w

21. tl;dv — record and summarize any meeting
https://t.co/IE8NQV7pzn

22. Fireflies — AI meeting notes automatically
https://t.co/dsbAnuUQji

23. Castmagic — turn audio into content pieces
https://t.co/GhGS0F2Szc

24. Replit — code and deploy from browser
https://t.co/dUCenYqW4U

25. Leonardo AI — generate images for free
https://t.co/7xTC7clZfl

26. Synthesia — AI avatar videos no camera needed
https://t.co/JUyPtbBN0S

27. Fliki — turn text into videos with AI
https://t.co/CVx4aAN2dj

28. Photoroom — AI product photography
https://t.co/uxxIAuajce

29. Invideo AI — turn prompts into full videos
https://t.co/RYGEc0aR5J

30. Consensus — search what science agrees on
https://t.co/0aiJRNQyS1

31. SciSpace — understand any research paper
https://t.co/YsTmVTOtiG

32. Tome — AI builds your pitch decks
https://t.co/AvedovUGHI

33. Beautiful AI — smart presentation design
https://t.co/zJmwoqyymm

34. Meshy — turn text into 3D models
https://t.co/C9NUi2f1RK

35. Vizcom — turn sketches into renders
https://t.co/sxrxTwcvgw

The AI revolution isn't coming.

It already happened and you missed half of it.

[David max @razib_ul47671]

Claude is used by 11+ million people every day.

Most users barely scratch the surface.

I put together a guide with 100 practical Claude skills that can save hours of work and unlock real results:

→ Writing better content
→ Automating repetitive tasks
→ Growing a business
→ Boosting productivity
→ Programming faster
→ AI workflows & prompting
→ E-commerce optimization
→ Finance analysis
→ Deep research
These are the same types of skills power users rely on daily.
Usually paid. Free for the next 24 hours.
Comment "CLAUDE" below or grab your copy now 👇

[Sick @sickdotdev]

For all the vibe coders out there: did you know that a few simple commands can fix all the errors in your code?

git add .env
git commit -m “”
git push

That’s it!

[Abhishek @be_mewadi]

Donald Trump 🤡

[kirobreika @bogsi]

@elonmusk Тиситъп

[kirobreika @bogsi]

@BulgariaDA Кво доверие, кви пет лева

[kirobreika @bogsi]

https://t.co/66C7vYHhB0

[kirobreika @bogsi]

@Skype Ewww, Teams is ugly and unfriendly.

[kirobreika @bogsi]

@Teslaconomics Biggest shit ever made. Drive yourself with your junks to the psychiatry

[kirobreika @bogsi]

@techyoutbe The answer is C

[HashiCorp, an IBM Company @HashiCorp]

Too often, platforms are built without the people who use them.

Platform engineering flips that. 🔄

By prioritizing developer experience, useful features, and real collaboration, teams can deliver platforms that actually work.

[kirobreika @bogsi]

https://t.co/x3HZsFkEZB

[Tech Fusionist @techyoutbe]

Kubernetes Concepts - Quick Guide 🔥