Meedun

Full stack developer | WFH | Silent Reader

[Meedun @SiMeeDun]

Indonesia vs EU internet regulation.
Two different models:
Indonesia focuses on platform compliance,
EU focuses on user rights and legal process.
#InternetGovernance #DigitalPolicy #PSE #GDPR #DSA #OpenInternet

[Meedun @SiMeeDun]

@lynxluna Setuju pakai banget...!

[Meedun @SiMeeDun]

@txtdrimedia Walah kebiasan markup

[ꦩꦸꦂꦠꦝ @MurtadhaOne1]

Siapa sih monyet2 ini?
urgentnya foto2 disana apa? Sedangkan truk2 pada disuruh berhenti diturunan...

[Meedun @SiMeeDun]

@Kappaemme1926 One funny workflow I often use with AI coding tools is this: I treat Kilo Code as the place for prototyping or drafting pseudocode, then use Codex as the final executor to produce clean code.😅

[Meedun @SiMeeDun]

@indepenSumatera Yang bermasalah kalau ada dugaan pelanggaran, bukan etnisnya. Membelokkan kasus jadi narasi suku itu tanda argumen lemah dan niatnya jelas provokasi.

[Meedun @SiMeeDun]

@gina_vivu Seandainya perempuan jadi presiden lagi, standarnya tetap sama: hasil kerja, jangan jual identitas, bawa bukti.

[Meedun @SiMeeDun]

@Kappaemme1926 keep using what gives you the best realworld results, and reassess when your needs change.

[Meedun @SiMeeDun]

@Kappaemme1926 There is nothing wrong with focusing on one provider. I think you made the right decision for your own needs. Only you can decide what fits your priorities best, regardless of the pros and cons of each AI provider.

[Meedun @SiMeeDun]

@orpheuskaze Data besar nggak otomatis bikin AI terbaik. Masalahnya ada di eksekusi model quality, arah produk, dan seberapa cepat mereka benerin hal yang dipakai user tiap hari.
Google kuat di data, tapi itu belum tentu jadi pengalaman AI yang paling enak dipakai.

[Meedun @SiMeeDun]

Model commoditizes. Execution doesn't.
If your "agent strategy" is still just "plug in the latest model," you are already behind.
The stack now matters more than the headline benchmark.
Agree or disagree?

[Meedun @SiMeeDun]

Code gives agents something most business workflows don’t: clear feedback loops.
It compiles or it fails. It ships or it breaks. It can be reviewed, tested, traced.
That makes software the perfect training ground for agent systems.

[Meedun @SiMeeDun]

Hot take:
the AI agent era will not be won by whoever makes the smartest model.
It will be won by whoever makes the most reliable system around the model.

[Meedun @SiMeeDun]

Without that, “agent” is mostly branding.
The new moat is shifting:
from model access to workflow reliability.
From raw intelligence to operational trust.
From one-shot answers to repeatable outcomes.
That is also why coding agents are exploding first.

[Meedun @SiMeeDun]

Real agents are not “chatbots that can call tools.”
Real agents need:
1. planning
2. execution
3. memory
4. verification
5. fallback paths
6. governance

[Meedun @SiMeeDun]

This is why so many early agent frameworks faded.
They were built like showcases, not like production systems.

[Meedun @SiMeeDun]

Most “AI agent” products still break on:
- messy context
- stale docs
- bad tool calling
- no rollback
- no traceability
- fake autonomy

[Meedun @SiMeeDun]

They’ll be the teams that solve:
- orchestration
- permissions
- observability
- human handoff
- cost control
- deterministic recovery

[Meedun @SiMeeDun]

The market is slowly realizing something uncomfortable:
better models alone do not fix weak systems.
The winners won’t be the apps with the flashiest demo.

[Meedun @SiMeeDun]

AI agents are entering their brutal phase.
2024 was about demos. 2025 was about wrappers. 2026 is where people learn the hard part:
an “agent” is only as good as its tools, memory, guardrails, and ability to recover from failure.

[Meedun @SiMeeDun]

The AI agent bubble is entering its first reality check.
Smart model? Not enough.
2026 belongs to teams that can make agents reliable, auditable, and hard to break.