Siphesihle Dube

“I’m very stingy, so I’m not in the mood for scammers or baddies.”

[Sama @tec_samax]

I JUST FINISHED READING Mark Manson’s The Subtle Art of Not Giving a F*ck.

Here are 10 lessons I took from the book.

[Ayaan 🐧 @twtayaan]

AWS just made it possible to run AWS services on your laptop for free, without an AWS account.

It’s called AWS Emulator, and it’s open source. You can use the AWS CLI or SDKs to test your app locally or in CI.

AWS says autonomous AI agents wrote every line of the emulator’s code.

Repo: https://t.co/hYVOSRrcLj

[Mansi 👩‍💻 @MansiCodez]

DO YOU KNOW HOW KAFKA WORKS INTERNALLY ?
BOOKMARK IT BEFORE YOUR NEXT INTERVIEW.

[beamnxw ./ @beamnxw]

THIS IS PURE GOLD

Anthropic engineer, Addy Osmani just shared how to run AI coding agents like a team - without babysitting every session

it shows how to give agents context, verify their work, set guardrails and decide what ships

context → plan → delegate → verify → decide

save the full playbook ↓

[Neo Kim @systemdesignone]

If you want to become good at system design (in 3 weeks), then learn these 15 case studies:

[Chen @ch3nweiii]

this Anthropic paper f*cking insane

it's basically the 9-step loop top AI engineers wrap around Claude Code before they let it near a repo.

every step, every formula, the full copy-paste template, all of it laid out.

paste it into Opus 5.5 once and your agent moves from guessing to planning, checking and fixing its own work.

the crazy part is anthropic has been recommending these exact pieces in their docs all along and 99% of people still simply type "fix this bug" and wonder why the agent breaks things.

bookmark it before this thread gets lost.

then read the full Graph Engineering guide below ↓

[marfin @marfinxx]

F*cking genius

Anthropic says Claude Code goes from 18% success in raw chat to 95% in an engineered harness

Set that up with one prompt, and turn Claude Code into a self-governing production machine

If the harness doesn't sign a verified receipt, git won't let the agent touch main

Here's the build:

step 1 → paste the prompt below into Claude Code on Opus 5.5

step 2 → Opus compiles your intent into a bounded task_contract.json before Sonnet generates token 1

step 3 → it spins up an isolated git worktree so the agent never modifies your active working branch

step 4 → Haiku 5.5 acts as a sub-second sensor hook, intercepting shell commands and blocking path leaks

step 5 → Sonnet 5.5 writes the code, but self-approval is physically disabled

step 6 → an adversarial skeptic subagent on Fable 5.5 attacks the diff and tries to break it under race conditions

step 7 → a pre-commit hook verifies real test runner outputs and cryptographically signs receipt.json

step 8 → any failure seen twice crystallizes into CLAUDE.md and regression evals on disk so it never repeats

Find the full prompt below

Then read the full Harness Engineering guide below on how to build unbreakable AI agents ↓

[Nhlanhla Hlabisa🇸🇿🇿🇦 @bab_hlabisa]

Yoh @ChrisExcel102 let’s find this young king sithi fafa ama R50 🙏🏽🙏🏽💪🏽🙌🏽

[Ja Leto @_falsi1ke]

I have been watching this every morning for 11 months now.

[Avid @Av1dlive]

if i were you... i'd spend a day teaching your agent system design before it writes a single line

here's everything you need: 7 rules + the 12-step prompt

[Yarchi @undefinedKi]

Lock yourself in just for 15 minutes and go through this site.

I promise you'll know more about ai agents than 95% of people.

https://t.co/TNypD7AlkZ

[🧚🏾‍♀️ @Thee_Cherri]

Medupi Power Station. Ntshepe!!!

[Swapna Kumar Panda @swapnakpanda]

You will be a WORLD-CLASS SOFTWARE ENGINEER once you read these 20 books.

Most people never finish even one.

[Yatharth Verma @yatharth170699]

Every backend engineer should build these 15 projects at least once.

Not another CRUD app. Projects that help you understand what's actually happening under the hood.

1. Distributed Rate Limiter — Explore token buckets, sliding windows, Redis atomicity and distributed coordination.

2. High-Concurrency HTTP Server — Understand TCP sockets, event loops, async I/O, connection handling and backpressure.

3. API Gateway — Learn reverse proxies, request routing, load balancing, authentication and circuit breakers.

4. Message Queue (Mini Kafka) — Understand producers, consumers, partitioning, acknowledgements and delivery guarantees.

5. Distributed Job Scheduler — Implement worker pools, retries, exponential backoff, delayed jobs and idempotency.

6. Distributed Cache — Explore cache eviction, TTL, cache invalidation, replication and cache stampede prevention.

7. WebSocket Server — Handle persistent connections, heartbeats, broadcasting and thousands of concurrent clients.

8. Database Connection Pool — Understand connection lifecycle, pooling, resource exhaustion, timeouts and concurrency.

9. Mini Database / Storage Engine — Implement write-ahead logging, indexing, B-trees and crash recovery.

10. Distributed Key-Value Store — Explore consistent hashing, partitioning, replication and failure detection.

11. DNS Resolver — Understand DNS records, recursive resolution, UDP/TCP, TTL and caching.

12. Concurrent Task Scheduler — Work with threads, processes, locks, synchronization and worker pools.

13. Log Aggregation System — Build log ingestion, buffering, indexing, searching and retention.

14. Change Data Capture (CDC) System — Capture database changes and explore event streaming, ordering and checkpoints.

15. CLI Process Monitor — Understand OS processes, CPU and memory monitoring, signals and resource management.

The real learning comes from building these from scratch, testing failure scenarios, benchmarking performance and understanding the trade-offs.

Which one would you add to this list? 👇

[Hanako @hanakoxbt]

I am begging you to paste this into Claude Code before bed, it will definitely change your life...

Overnight it builds a harness around your agent on Opus 5.5 that plans, checks and fixes its own work 24/7.

Steal this before everyone starts using it:

[Nico Garcia | Ingeniero de IA @NicoGarcia_IA]

🔴 ALGUIEN HA FILTRADO ESTE PROMPT PARA CREAR AGENTES DE TRADING

Lo pegas en Claude Code y te monta el bot.

Sin programar.

Detecta si el mercado está tranquilo, lateral o en caída y cambia de estrategia.

Freno de mano: drawdown máximo del 15% y comprueba antes de cada orden.

Prueba la estrategia con datos reales y se niega a operar si no le gana al mercado.

Mientras duermes analiza qué falló y te deja mejoras.

Pegas, rellenas tus datos y Claude hace el resto.

[xsmryze @xsmryze]

THIS IS AN ACTUAL F*CKING GOLDMINE

Anthropic just shared one of the best tricks for Claude Code.

The idea: run Sonnet, Haiku 5.5 and Opus 5.5 at once, each one doing only the job it's best at.

Better results and way fewer tokens, because every task lands on the right model.

You just launch Claude Code like this:

claude --model sonnet --advisor opus

here's the split:

→ Sonnet 5.5 runs the session, writes the code and applies the fixes
→ Haiku 5.5 swarms the repo in parallel: search, grep and diff audits
→ Opus 5.5 stays on call as advisor for the big calls and signs off on the diff
→ you stop burning Opus context on work that doesn't need it

Opus only steps in at three moments:

→ before a plan locks
→ when the same error shows up twice
→ before calling it done

Sonnet builds. Haiku swarms. Opus reviews.

JEV engineering is the same move one layer down: the forks that need no thinker (which file, which tool, retry or stop) go to JEV in milliseconds, and the big models only see the ones that split

the full tree
> Sonnet 5.5 runs the main session and coordinates the work
> search maps the repo on Haiku 5.5, read-only
> grep finds call sites on Haiku 5.5 in its own context
> audit checks the diff on Haiku 5.5 in a throwaway worktree
> Opus 5.5 on call as advisor, reviews the synthesized diff before sign-off
> JEV routes micro-forks in milliseconds

paste the tree and this prompt into Claude Code ↓

"Reconfigure my Claude Code setup around this tree:
1. Run the main session on Sonnet 5.5 with Opus 5.5 as advisor.
2. Create three Haiku 5.5 subagents in .claude/agents: search (maps the repo), grep (finds call sites), audit (checks the diff).
3. Set isolation: worktree on audit so its checks never touch my working branch.
4. Add one rule to CLAUDE.md: delegate every repo search and test run to the Haiku 5.5 subagents to keep the main context small.
5. Route fast deterministic forks (tool choice, path selection, retries) through JEV.
Show me every change as a diff first. No edits until I say go."

↳ https://t.co/YqkjQiqRGv

save it, it'll come in handy.

[Khairallah AL-Awady @eng_khairallah1]

Paste this into Claude Opus 5.5 tonight, it will change your life...

it will build an entire AI team to handle it with AI agents, prompts, and workflows for you

Save this before it takes over your timeline:

[Podcast and Chill Network @podcastwithmacg]

Chillers, the elections kick off tomorrow! 🇿🇦

Tonight, we’re hanging out with community leaders and political representatives to unpack how immigration issues have taken centre stage ahead of the 2026 Local Government Elections.

📺 Join us LIVE on YouTube at 17:00.

Don’t miss it!

[Linda Mnisi @LindA_MniSii]

Got home yesterday and there was no electricity. Moments later, power was restored but then we had a water outage.

Woke up this morning and there’s no water and electricity. Yintoni le sikuyo @CityofJoburgZA @DadaMorero?